Publications

The MFPG was formed primarily to provide a mechanism for effective interchange of technical information among segments of the scientific and engineering communities in order to gain a better understanding of the processes of mechanical failures.

A Quick Introduction to Bearing Envelope Analysis

Abstract: Bearing envelope analysis (BEA) is a powerful technique for the detection of bearing faults. The improper selection of the envelope window frequency and window bandwidth can render the analysis ineffective. This can reduce the ability to perform condition monitoring to correctly identify a degraded bearing. This paper is an analysis of how BEA works in the detection of damage bearings. A description of the BEA is given, methods for window selection, such as spectral kurtosis, is described, and example algorithms are given to facilitate experimentation.

Keywords: Bearing Analysis, Envelop, Heterodyne, Condition Monitoring Systems

Author: Eric Bechhoefer

Full-Text PDF: A Quick Introduction to Bearing Envelope Analysis

Robot Manipulator Drive Fault Diagnostics Using Data-Driven and Analytical Modelling

Abstract: Belt-driven mechatronic systems are popular for a range of applications. A modified robotic manipulator was adapted to allow different belt-drive faults to be incorporated into the mechanism, with additional sensors to characterize the compromised kinematics. Different data-driven models were used studied to detect anomalies in motor power consumption and end-effector motion; and a physics-based, lumped-parameter dynamic model was used to identify different faults. Comparative assessment metrics were sdused to compare the performance of different fault models from sets of laboratory test data.

Keywords: Machinery diagnostics; fault detection; machine learning; modelling; robotics; analytics; belt drives, time-varying systems.

Author: Michael Lipsett, Anthony Maltais, Mohammad Riazi, Nicolas Olmedo, Osmar Zaiane

Full-Text PDF: Robot Manipulator Drive Fault Diagnostics Using Data-Driven and Analytical Modelling

Aerial Manipulation For Remote Robotic Machinery Diagnostics

Abstract: There is a growing trend of using unmanned aerial vehicles (UAVs, or drones) for inspection of industrial facilities and infrastructure. The types of inspections currently done entail remote sensing using cameras: qualitative assessment and photogrammetry using standard cameras, as well as temperature monitoring using thermal imaging cameras. The benefits of using drones are to reduce risk to inspection personnel near operating equipment, reduced cost, and improved auditability of archived data. Machine condition monitoring can benefit from this enabling technology provided that vibration monitoring and lubricant analysis can also be done remotely. Laser vibrometers can be used for remote monitoring of equipment that does not have permanently mounted, dedicated vibration monitoring sensors; but this sensing method is capital intensive, requires a laser head and controller with a typical mass of over 5 kg, and must be pointed from an appropriate direction, which may not be accessible. Lubricant analysis requires access to a lubricant sampling port and a means for collecting and analyzing the sample. A system is described for deploying a drone with a manipulator that engages the equipment of interest for vibration data collection and employs a more versatile payload for drop-tube vacuum sampling of lubricant by inserting a tube through a fill port or dip stick port and withdrawing an oil sample from the sump cavity. The key technical challenges are collision-free navigation and hovering, followed by control of dynamic deployment of the payload that connects to the machinery. A proof-of-concept system is described with very preliminary experimental results.

Keywords: Aerial manipulation; automated sampling; contact inspection; inspection; lubricant sampling; remote diagnostics; robotics; unmanned aerial vehicle

Author: MG Lipsett, Rijesh Augustine and Mark Sherstan

Full-Text PDF: Aerial Manipulation For Remote Robotic Machinery Diagnostics

Towards Replacement Of Failed Parts On The Battlefield Via Metal Casting In 3D-Printed Desert Sand Molds

Abstract: The research was performed to show the feasibility and scale-up potential of production of replacement parts for long lead time DoD critical components utilizing a sand 3D-printer with indigenous desert sand to produce casting molds from a digital drawing of the actual part. Replacement and/or spare parts could then theoretically be manufactured by pouring molten metal into these molds. Success was achieved in producing parts in a laboratory setting by pouring molten aluminum into 3D-printed desert sand molds of smaller components, but scale-up proved difficult, as the fine desert sand did not fully adhere to itself, and the mold strength was less than optimal. Lessons learned could potentially be utilized to further this effort in the use of different sand, for example beach sand, which may be easier to process.

Keywords: 

Author: Marc Pepi, Jerry Thiel, Nathaniel Bryant, Brandon McWilliams, Andelle Kudzala Jennifer Sietins

Full-Text PDF: Towards Replacement Of Failed Parts On The Battlefield Via Metal Casting In 3D-Printed Desert Sand Molds

Piezoelectric VS MEMEs: Future Of The Vibration Sensors

Abstract: The paper presents a detail comparison between the traditional piezoelectric and MEMs based vibration sensors. The future prognoses of what technology and where will be used in the future is discussed.

Keywords:

Author:George Zusman, Ph.D., D.Sc.

Full-Text PDF: Piezoelectric VS MEMEs: Future Of The Vibration Sensors 

Design Approach for a PHM System: Dual Set of Electromechanical Actuator Subsystems

Abstract: This paper describes a design for an example of a Prognostic Health Monitoring (PHM) system that is able to detect a state of degraded health and make an accurate prediction of when a resulting future failure in the system is likely to occur in a dual set of electromechanical actuators (EMA) subsystems, each comprising a switch-mode power supply (SMPS) and two identical EMAs. Examples of considerations in a design of a PHM system include the following: (1) What is the framework for the PHM system? (2) What units (targets) are to be prognostic enabled? (3) What failure modes are to be monitored? (4) What kind of data conditioning is necessary to isolate and extract condition indicators and/or leading indicators of failure from noisy condition-based data (CBD)? (5) Do special methods of data processing need to be developed and, if so, how? (6) What are the prognostic accuracy requirements? (7) What alerts and alert levels are required to support prognoses? (8) What are the requirements related to starting, stopping, resuming, and recovery of the system? (9) What architecture approach is going to be used to define the target system to the PHM system?
*RotoSense and ARULEAV are trademarks of Ridgetop Group, Inc

Keywords: Condition-based data; CBD; electromechanical actuator; EMA; prognostic health monitoring; PHM; Accelerometer; gear; MEMS; rolling stock; RotoSense; signal quality; train; wheel hub

Author: James P. Hofmeister, Erik Sandberg, Wyatt Pena, and Robert S. Wagoner

Full-Text PDF: Design Approach for a PHM System: Dual Set of Electromechanical Actuator Subsystems

Analyzing The Center Of Mass Of Athletes Performing Both an Open and Closed Skill Exercise

Abstract: In looking into the components of human monitoring systems, there are three main elements that comprise a system: sensors; data acquisition and communication; and data processing and analytics. Sensors that function with the purpose of sensing body movements or collecting specific physiological or biological parameters of an individual are typically known as wearables. Wearables used for capturing body movements are primarily inertial measurement units (IMUs) which utilize sensor fusion to combine the technology of an accelerometer, gyroscope, and magnetometer. Data obtained from these wearables may provide important insight into subtle differences in body movements that influence performance outcomes. The long-term goal of our work is to develop approaches that enable the prediction of an individual’s performance in an open-skilled environment. The specific aim of this research was to determine how data from a full body IMU-based system could be used in detecting subtle movement differences in the execution of a pre-planned agility test versus a reactive agility test

Keywords: Human monitoring systems, Reactive Agility, Pre-planned Agility

Author: Amanda Delaney, Kimberly Bigelow, Mark Derriso, Christine Kabban-Schubert, Ed Downs

Full-Text PDF: Analyzing The Center Of Mass Of Athletes Performing Both an Open and Closed Skill Exercise

Full Circle Mechanical Dynamic Characterization Including Experimental Modal Analysis and Finite Element Analysis

Abstract: During operation, it was observed that a specific mechanical system experienced undesirable vibration and it became necessary to understand and mitigate this phenomenon. This document investigates the tools, methodology, and results of the dynamic characterization of the system. The characterization makes use of the experimental modal analysis (EMA) methods of single input multiple output (SIMO) and single input single output (SISO). The validity of the theory of reciprocity is confirmed to minimize measurement error, cost, and time of repeat testing. Finite element analysis (FEA) is used in choosing transducer and modal impact locations to adequately characterize the system. Single degree of freedom (SDOF) and multiple degree of freedom (MDOF) curve fitting is used to fully characterize the system’s mode shapes and natural frequencies. The EMA characterization results are used to modify and validate the FEA model so that FEA can be used to model potential structural modifications to the system to mitigate the undesirable vibration. Structural modifications are chosen, implemented, and their effectiveness is quantified using EMA. A qualitative evaluation of the methodology of FEA validation by EMA and tuning of the model to match the experimental results is discussed.

Keywords: Case Study, Non-destructive Testing, Signal Analysis

Author:  Jason Cook, Thomas Hazelwood, Clay Jordan, and Blake Van Hoy

Full-Text PDF: Full Circle Mechanical Dynamic Characterization Including Experimental Modal Analysis and Finite Element Analysis

Optimal Attachment Methods For Accelerometers

Abstract: Vibration detection on stationary surfaces of machinery, such as bearing housings, is typically accomplished with accelerometers. Modern accelerometers have been engineered to have a very wide frequency range with strong sensitivity of voltage to surface acceleration. However, in order to implement this capability, the bottom surface of the accelerometer must faithfully track the actual motion of the surface that it is attached to. The ideal method would be a tight metal-to-metal connection, such as can be achieved with a well-torqued screw joint. However, this is often not practical (e.g. no surface modification allowed), or is very inconvenient (e.g. an Operating Deflection Shape requires measurements at hundreds of locations, or walk-around machinery monitoring routes on many uninstrumented machines in large plants). In such cases, diagnosticians use temporary attachment methods, such as a simple hand-pressure attachment, a magnetic base, two-sided tape of various thicknesses, a thin layer of wax, or glue-cement. The authors have studied the fidelity of each of these methods in a series of controlled experiments, and determined that all methods, up to about 1500 Hz, are adequate for characterization of machines over the typical range of significant dynamic excitation forces. For frequencies to over 10 kHz, an unexpected result was that double-sided tape provided some of the best results. All methods provided similar looking amplitude vs. frequency spectra up to about 5 kHz.

Keywords: Accelerometer Attachment; Vibration Measurement; Operating Deflection Shape; Turbomachinery; Machinery Diagnostics

Author: William D. Marscher and Maki M. Onari

Full-Text PDF: Optimal Attachment Methods For Accelerometers

Bathtub, Failure Distribution, MTBF, MTTF, and More: They Are Related

Abstract: This paper describes the relationship between a bathtub curve, failure distributions, and commonly used metrics: mean-time-before failure (MTBF), mean-timebetween failure (MTBF), and mean-time-to failure (MTTF) – metrics that are often misunderstood and misused. A bathtub curve is a statistical depiction of the failure rate over the lifetime of a population of products and is related to a failure-distribution curve: they can be combined to form a continuous curve. A bathtub curve graphically relates three types of failure: early, random, and wear out. Manufacturing and material defects typically result in early, rapid failure of products: that region of a bathtub curve is called infant mortality. After the infant-mortality region, there is a constant-failure region during which a low number of failures occur that are often referred to as random failures that are characterized as having a mean-time-between failures (MTBF). In-use products are subjected to stresses and strains that are cyclic in nature, plastic work, and which eventually causes irreversible damage and the onset of degraded operation. Damage accumulates until the product is no longer capable of operating within specifications and is said to have functionally failed – it has worn out. Such functional failures are characterized by a failure distribution having two common metrics: mean-time-before failure (MTBF) and meantime-to failure (MTTF). Associated with bathtub and failure distribution curves are other metrics, including the following: failure rate, prognostic trigger point, prognostic distance (PD), failures-in-time (FIT), and useful life. Those metrics and how they are related are the focus of this paper.

Keywords: Bathtub; degradation; failure; metrics; prognostics; trigger; useful life

Author: Thomas Heiser and James P. Hofmeister

Full-Text PDF: Bathtub, Failure Distribution, MTBF, MTTF, and More: They Are Related

Selection of Thermal Isolator For A Propylene Transfer Pump - A Case Study

Abstract: In a Petrochemical Complex, liquid Propylene as a product is transferred by a transfer pump from storage tanks for ship loading / other required facilities. Liquid Propylene has a boiling point of minus 47.7 degree C, hence operating fluid must be kept below minus 47.7 degree C during complete pumping operation and storage. To protect concrete from such a cold temperature exposure a thermal isolator was selected. In addition, isolator was supposed to tolerate pump dead weight, provide proper anchorage during dynamic motion, shall not fail even at high stresses generated during a trip due high vibration or a short circuit. Most importantly, it was supposed to isolate high vibration and dynamic forces thus ensuring smooth operation of other pumps of similar type. The case study provides outline how such objectives were achieved by inhouse detailed engineering and calculations.

Keywords: API VS6 pump, unbalance force, transmissibility, isolation, cold transfer

Author: Mantosh Bhattacharya

Full-Text PDF: Selection of Thermal Isolator For A Propylene Transfer Pump – A Case Study

Devices For Insitu Tuning Of Machinery Structures To Minigate Resonance

Abstract: For on-shore and grout less design applications, the support structure for a rotating machine consists of a base-frame (base plate) normally known as skid. Most of the time these structures show up with high vibration on machine bearing cap due to structural resonance, unidentified cracks. Detection and mitigation of such anomaly is time consuming job. The paper proposes a blueprint of active and passive resonance control at location without removal of base frame from foundation / main support and any structural modification which requires any hot work.

Keywords: 

Author: Mantosh Bhattacharya

Full-Text PDF: Devices For Insitu Tuning Of Machinery Structures To Minigate Resonance

Fault Diagnosis Of Excessive Pipe Vibration Due to Beating Phenomenon

Abstract: This paper presents a case study in diagnosing an excessive pipe vibration due to beating phenomenon. The outdoor process pipes in a sewage plant were found to vibrate viciously and resulted in emitting loud hamming noise that affecting the surrounding community. The process pipes were connected to two identical blower units, each driven by a motor via belt and pulley system. Besides the loud noise, the excessive pipes vibration had also posed a concern to the plant personnel that a possibility of premature machine failures may occur if the problem persists any longer. A comprehensive vibration investigation was conducted to map-out the vibrations of the entire machine train that includes pipes, blowers, motors, skid, plinth and floor slab of the blower house. Vibration investigation found that pipes vibration was most severe when the two units of blowers were operated simultaneously. It was found that the root cause of the excessive pipe vibration was caused by beating phenomenon of which two adjacent machines operated under slightly different speeds. In this case, the two blowers were operated at 41.88Hz and 41.72Hz respectively. Beating is a phenomenon of constructive and destructive interference of two identical waveforms with slightly different frequency. As such, the remedy measure undertaken was thus to fine tune the operating speed of the two blowers. It was found that pipes vibration had subsided considerably when the two blowers’ speeds were adjusted to be 7.5 Hz apart. As a result, the loud humming noise emitted from the pipes was noted to be completely mitigated with the remedial action taken.

Keywords: Pipe; beating; vibration

Author: Meng Hee Lim, Kar Hoou Hui, and Mohd Salman Leong

Full-Text PDF: Fault Diagnosis Of Excessive Pipe Vibration Due to Beating Phenomenon

Motion Magnified Video Application To Machinery Diagnosis

Abstract: Vibration detection can be performed by a meter, or a single channel spectrum analyzer. The former has quantified vibration amplitude levels since the 1950’s, while the latter was able to implement the Fast Fourier Transform (FFT) since the 1960’s to break vibration down into its frequency components. Multiple channel FFT analyzers enabled the process of Operating Deflection Shape (ODS) determination, which has been an important tool in visualizing the vibration of the machine and its system, including the foundation and piping networks. The input for ODS is the phase-linked signal set from a group of accelerometers, moved over often hundreds of test points. The data is superimposed onto a CAD model, and then scaled-up vibrations are animated at frequencies of interest. This process provides valuable insights, but is time-consuming and therefore expensive each time it is applied by experts, and it is error-prone. An alternative method has been developed that is based on evaluation of high resolution/ high speed videos. The method provides information equivalent to a high-sensor-count ODS, by treating each pixel as an accelerometer, using the pixel’s light intensity modulation to translate information embedded in the video into vibration motion able to be observed and interpreted by human investigators. This method is known by some as Motion-Magnified Video (MMV).

Keywords: Motion Magnification; Video Amplification; Operating Deflection Shape; Turbomachinery; Machinery Diagnostics; Predictive Health Management

Author:William D. Marscher and Chad Pasho

Full-Text PDF: Motion Magnified Video Application To Machinery Diagnosis

Condition Monitoring Of A Cycloid Gearbox

Abstract: A cycloid drive for gearboxes allows for high reduction ratio and zero or very low backlash. The cycloid gear design is based on compression, whereas most gear interactions are based on shear. Further, the contract of a cycloid gear is typically subject to rolling forces vs. sliding, which are seen in traditional gearboxes. These features of a cycloid gearbox allow for high shock load capacity, high torsional stiffness, and quiet operation. This paper details the modeling required for correct configuration to perform analysis on the cycloid gearbox and then is demonstrated on a 51:1 ratio, run to failure test. This paper documents the sensitivity of standard condition indicators for gear/bearing during the run to failure test.

Keywords: Cycloid; Smart Sensor; vibration diagnostics; Resonance; Spectral Estimation; Model Bases Dynamics;

Author: Eric Bechhoefer

Full-Text PDF: Condition Monitoring Of A Cycloid Gearbox

Development Of An Accelerated Degradation Testbed For Integrated Vibration Monitoring And Online Oil Analysis Of Vehicle Differential Bearings

Abstract: This project, sponsored by the Office of Naval Research, integrates oil and vibration analysis to develop a more complete diagnostic and prognostic model for monitoring bearing degradation and performance in the field. The results of this project will be used to optimize repair schedules and minimize the risk of catastrophic failure of machine components for military personnel during a mission through enhanced conditionbased maintenance. Each test bearing is first introduced with an outer race fault. The fault’s degradation is accelerated by running the bearing under overloaded conditions in the boundary lubrication regime within a large test rig designed for these conditions. Accumulated damage to the bearing is characterized in another clean, low-noise test rig to collect vibration signatures. Finally, the bearing is implemented into the differential for insitu testing to emulate data in the field. Dynamic characterization of the designed test machines was performed by long runs spanning multiple hours under rated conditions to determine any wear-in effects and ramp-up tests to distinguish order-based bearing frequencies and structural resonances. Modal analyses were performed on the static system to provide additional evidence of structural resonances within the machines. This paper will discuss the design challenges and solutions for creating a test bed to monitor bearings in accelerated-degradation conditions and in realistic operating conditions.

Keywords: Bearings; boundary lubrication; diagnostics; frequency response function; health monitoring; prognostics;

Author:Cody M. Walker, Alec B. Salakovich, David K. Irick, Jamie B. Coble, and Cyrus Smith

Full-Text PDF: Development Of An Accelerated Degradation Testbed For Integrated Vibration Monitoring And Online Oil Analysis Of Vehicle Differential Bearings

Deliberations On Foundation Design Methods For Rotating Machinery.

Abstract: For on-shore applications, the support structure for a rotating machine consists of a block foundation and base-frame (base plate) normally known as skid. Adequate dynamic analysis of support structures for rotating equipment is necessary to safeguard other machinery in the vicinity of the subject rotating machine, as well as ensure good conditions for the operation of the supported machine. The present method tries to achieve an under-tuned support structure which considers the machine mass and block foundation mass as one entity. The design procedure assumes that the assume that all vibrations are transferred to machinery foundation irrespective to the type of machine. This paper endeavours to highlight that how and why current design procedures for support structures of rotating machinery should consider the stiffness ratio of the bearing support (casing) and the rotor – bearing system, With the advent of foundation damping methods, the size of foundation can be lowered with a correct deliberation on subject.

Keywords: 

Author: Mantosh Bhattacharya

Full-Text PDF: Deliberations On Foundation Design Methods For Rotating Machinery.

Advances in Comprehensive Fluid Analysis

Abstract: We describe advanced forward deployed comprehensive fluid analysis for wear debris and fluid condition of lubricating oil, hydraulic oil and fuel. Examples from mechanical systems are given for detection of wear-related and fluid condition-related faults.

Keywords: 

Author: J. Reintjes, J. E. Tucker, P. F. Henning, Paul Howard

Full-Text PDF: Advances in Comprehensive Fluid Analysis

The Case Of The Missing Bearing Fault Frequency

Abstract: During testing on a small gas turbine, frequencies related to the power turbine shaft and a bearing were observed. The frequencies of the fault were not associated with any known bearing on the power turbine shaft. This paper is an investigation of why the observed bearing fault frequency of 6% higher than anticipated. It will be shown that because the faulted bearing was a worn thrust bearing, the contact angle and pitch diameter of the roller element had changed. This is an infrequently observed phenomenon, which can lead to missed fault detection on a critical component. A mitigation strategy for this type of failure is discussed.

Keywords: Spectral Kurtosis; vibration diagnostics; resonance; performance testing; hardware testing

Author: Eric Bechhoefer

Full-Text PDF: The Case Of The Missing Bearing Fault Frequency

Low Power Wireless Triaxial Vibration Sensor Design - Prototype Review

Abstract: Attend a maintenance or reliability conference today and you can’t fail to miss the many vendors offering wireless sensors for condition monitoring. Wireless sensor networks offer a way to expand the practice of CBM by making more condition data from more machines available for analysis. The recent advancements of MEMS accelerometers, energy harvesting techniques, and low power wireless communication facilitate the development of specialized vibration sensors for machine maintenance applications. This presentation describes a low power MEMS accelerometer based vibration sensor with energy harvesting and wireless communication capabilities.

Keywords: Accelerometer; MEMS; Sensor; Vibration; Wireless; Energy harvesting; TEG; Low power

Author: Shannon Jelken, Joel Bland, Haibo Wang, Ed Spence

Full-Text PDF: Low Power Wireless Triaxial Vibration Sensor Design – Prototype Review

Rapid Impact™ Testing Of Any Size Structure

Abstract: One of the limitations of conventional modal testing using a roving impact hammer is that the reference sensor (usually an accelerometer) must remain fixed throughout the test. Since the accelerometer must typically be connected by a wire to the data acquisition system. a very long wire may be required when testing a large structure. Furthermore, better quality signals are possible if each impact force is applied closer to the response accelerometer. Because it does not require a fixed reference sensor throughout the test, a Rapid Impact™ test is faster and easier to perform on any size structure.

Keywords: Experimental Modal Analysis (EMA); Frequency Response Function (FRF); Impulse Response Function (IRF); Curve Fitting; Modal Residues; UMM Mode Shape; Multi-Input Multi-Output (MIMO) Modeling & Simulation; Modal Participation.

Author: Brian Schwarz, Patrick McHargue, Mark Richardson

Full-Text PDF: Rapid Impact™ Testing Of Any Size Structure

Bearing Faults Detection And Identification Using Relational Data Clustering With Composite Differential Evolution Optimization

Abstract: Bearing faults in machinery are among the most critical faults that require attention by maintenance personnel at early stages of fault initiation. In many cases it is difficult to directly and accurately identify the fault type and its extent under varying operating conditions. This work demonstrates a novel procedure for bearing fault detection and identification in an experimental set-up. Three seeded faults, in the rotating machinery supported by the test ball bearing, include inner race fault, outer race fault and one roller fault. The rotor is run at different speeds and with small level of rotating mass unbalance. Accelerometer based vibration signals are analyzed for the different bearing faults’ signatures using statistical features, frequency spectra and wavelet coefficients. The composite differential evolution technique is proposed for parameter estimation when the system response is known a-priori. The algorithm is compared to five other differential evolution algorithms using conventional crossover and mutation operators. The objective is to correlate bearing faults to the extracted vibration features. The results of this analysis will be extended for applications in real time bearing condition monitoring system.

Keywords: Bearing fault; Condition monitoring; diagnostics; differential evolution; evolutionary algorithms; parameter identification; vibration; wavelets.

Author: Issam Abu-Mahfouz and Amit Banerjee

Full-Text PDF: Bearing Faults Detection And Identification Using Relational Data Clustering With Composite Differential Evolution Optimization

Motion Magnified Video Application To Machinery Diagnosis

Abstract: Vibration detection can be performed by a meter, or a single channel spectrum analyzer. The former has quantified vibration amplitude levels since the 1950’s, while the latter was able to implement the Fast Fourier Transform (FFT) since the 1960’s to break vibration down into its frequency components. Multiple channel FFT analyzers enabled the process of Operating Deflection Shape (ODS) determination, which has been an important tool in visualizing the vibration of the machine and its system, including the foundation and piping networks. The input for ODS is the phase-linked signal set from a group of accelerometers, moved over often hundreds of test points. The data is superimposed onto a CAD model, and then scaled-up vibrations are animated at frequencies of interest. This process provides valuable insights, but is time-consuming and therefore expensive each time it is applied by experts, and it is error-prone. An alternative method has been developed that is based on evaluation of high resolution/ high speed videos. The method provides information equivalent to a high-sensor-count ODS, by treating each pixel as an accelerometer, using the pixel’s light intensity modulation to translate information embedded in the video into vibration motion able to be observed and interpreted by human investigators. This method is known by some as Motion-Magnified Video (MMV).

Keywords: Motion Magnification; Video Amplification; Operating Deflection Shape; Turbomachinery; Machinery Diagnostics; Predictive Health Management

Author: William D. Marscher and Chad Pasho

Full-Text PDF: Motion Magnified Video Application To Machinery Diagnosis

Electrically Improving a MEMS Sensor for Rolling Stock

Abstract: This paper describes work related to improving the electrical performance of an accelerometer-based sensor, RotoSense™, used for monitoring rolling stock: the locomotives and cars used in trains. At the 2018 MFPT conference, a paper, “Improved RotoSense™ for Rolling Stock: Locomotives and Cars,” focused on physical improvements to the shaft-mounted, wireless sensor, although there were improvements in signal performance. This paper describes subsequent improvements to that sensor, with focus on signal quality and battery life. The original version of the sensor described in this paper is the first and, still, only known to survive, intact, three days of testing at the National Test Track Center in Pueblo, Colorado, including a 10-hour, non-stop, 400-mile test run. The rationale, the methods, and the results of those electrical improvements are the focus of this paper. *RotoSense is a trademark of Ridgetop Group, Inc.

Keywords: Accelerometer; gear; MEMS; rolling stock; RotoSense, signal quality; train, wheel hub

Author: James P. Hofmeister, Wyatt Pena, Erik Sandberg, and Robert S. Wagoner

Full-Text PDF: Electrically Improving a MEMS Sensor for Rolling Stock

Electromechanical Actuator Case Study: Multivariable Analysis Of Phase Currents To Detect Three Types Of Faults

Abstract: This paper describes a multiple-variable analysis (MVA) methodology to detect and prognose three types of faults associated with an electromechanical actuator (EMA): (1) loading faults, such as friction, on the shaft of an EMA motor, (2) shorting faults in the stator windings of the EMA motor, and (3) on-resistance faults in one or more powerswitching transistors used to convert direct voltage/current into alternating current. The presented methodology overcomes difficulties associated with typical multivariate analysis (as opposed to multiple-variable analysis) methods such as the following examples: solving simultaneous equations and performing a statistical-based analysis such as K-nearest neighbor (KNN) regression and other Euclidean-based distance methods. Examples of those difficulties are the following: (1) analysis methods that produced information suitable for classification rather than diagnosis or prognosis; (2) noisy data; (3) dependent data, rather than independent data; and (4) difficulty in processing test data to identify, extract, and use leading indicators of failure for prognostic purposes. The primary MVA solution methods included (1) noise mitigation, (2) a unique root-mean-square (RMS) of quantifying phase current values, and (3) a combination of nearest neighbor and distance methods of processing phase-current data to unequivocally identify and isolate faults and to prognose a future time at which functional failure is likely to occur. *ARULEAV is a trademark of Ridgetop Group, Inc.

Keywords: Diagnostics; electromechanical actuator; EMA; IVHM; multiple-variable analysis; MVA; prognostics; PHM

Author: James P. Hofmeister, Robert S. Wagoner, Douglas L. Goodman

Full-Text PDF: Electromechanical Actuator Case Study: Multivariable Analysis Of Phase Currents To Detect Three Types Of Faults

Intelligent Fault Identification Of Planet Bearings Using Discriminative Dictionary Learning Based Sparse Representation Classification Framework

Abstract: Planet bearing fault identification is an attractive but challenging task in numerous engineering applications, such as wind turbine and helicopter transmission systems. However, traditional fault characteristic frequency identification and impulsive feature extraction based diagnosis strategies are not sufficient to resolve the problem of planet bearing fault detection, due to complex physical configurations and modulation characteristics in planetary gearboxes. In this paper, a novel discriminative dictionary learning based sparse representation classification (SRC) framework is proposed for intelligent planet bearing fault identification. Within our approach, the optimization objective for discriminative dictionary learning introduces a label consistent constraint called ‘discriminative sparse code error’ and incorporates it with the reconstruction error and classification error to bridge the gap between the classical dictionary learning and classifier training. Therefore, not only the reconstructive and discriminative dictionary for signal sparse representation but also an optimal universal multiclass classifier for classification tasks could be simultaneously learnt in the proposed framework. The optimization formulation could be efficiently solved using the well-known K-SVD dictionary learning algorithm. The effectiveness of the proposed framework has been validated using experimental planet bearing vibration signals. Comparative results demonstrate that our framework outperforms the state-of-the-art K-SVD based SRC method in terms of classification accuracy for intelligent planet bearing fault identification.

Keywords: Planet bearing; Fault identification; Discriminative dictionary learning; Sparse representation classification; K-SVD; Orthogonal matching pursuit.

Author: Yun Kong, Tianyang Wang, Fulei Chu

Full-Text PDF: Intelligent Fault Identification Of Planet Bearings Using Discriminative Dictionary Learning Based Sparse Representation Classification Framework

Motion Amplified Video Application To Machinery Diagnosis

Abstract: Vibration detection can be performed by a meter, or a single channel spectrum analyzer. The former has quantified vibration amplitude levels since the 1950’s, while the latter was able to implement the Fast Fourier Transform (FFT) since the 1960’s to break vibration down into its frequency components. Multiple channel FFT analyzers enabled the process of Operating Deflection Shape (ODS) determination, which has been an important tool in visualizing the vibration of the machine and its system, including the foundation and piping networks. The input for ODS is the phase-linked signal set from a group of accelerometers, moved over often hundreds of test points. The data is superimposed onto a CAD model, and then scaled-up vibrations are animated at frequencies of interest. This process provides valuable insights, but is time-consuming and therefore expensive each time it is applied by experts, and it is error-prone. An alternative method has been developed that is based on evaluation of high resolution/ high speed videos. The method provides information equivalent to a high-sensor-count ODS, by treating each pixel as an accelerometer, using the pixel’s light intensity modulation to translate information embedded in the video into vibration motion able to be observed and interpreted by human investigators. This method is known by some as Motion-Amplified Video (MAV).

Keywords: Motion Amplification; video; Operating Deflection Shape; Turbomachinery; diagnostics; health management

Author: William D. Marscher and Chad Pasho

Full-Text PDF: Motion Amplified Video Application To Machinery Diagnosis

Universal Vibration Sensor Mount

Abstract: The present paper describes universal vibration sensor mount devices for attaching sensors to the machinery. Some types of machinery vibration sensors need to be mounted in a particular orientation relative to the machine being monitored. One example is twoaxis and three-axis MEMS accelerometers used to detect machine-critical acceleration vector components. Another example is sensors with side connectors or cables whose orientation is restricted by space limitations. In many instances, vibration machinery sensors constructed as could be mounted using a central bolt that going throw the sensor body threads into a bore on the machine body. Such sensors are usually more expensive that similar sensors with solid body. In some cases, proper sensor orientation is achieved by simply gluing the sensor to the machine body. This makes it difficult to remove the sensor if it needs to be replaced. There are also proprietary sensor mounts designed for specific sensors, but these lack versatility. We designed the universal sensor mount that can be used to mount a wide variety of machinery sensors at precise orientations. The idea here is that sensor module mounting member is locked in a selected rotational position using the adjustable locking member as shown on the Figure 1. The sensor module is attached to the universal sensor mount by threading the sensor module onto the sensor module mounting member until tight. A determination is made whether the sensor module is substantially aligned with one or more reference axes of the machine. If not, the sensor module is detached from the universal sensor mount. The sensor module mounting member is unlocked and rotated to another selected rotational position that will substantially align the sensor module with the one or more machine reference axes as shown on Figure 2. The sensor module mounting member is then relocked in another selected rotational position and sensor module is reattached to the universal sensor mount.

Keywords:

Author: George Zusman, Ph.D., D.Sc.

Full-Text PDF: Universal Vibration Sensor Mount

Bolted Structural Connections In Fiberglass Materials

Abstract: This paper compares several methods of connecting fiberglass reinforced pultruded plastic (FRP) structural members to tubular sections using bolted designs that are commonly used in the cooling tower industry. The study compares theoretically predicted values with full-scale actual laboratory test results. The geometry of the structural members studied herein are representative of the diagonal bracing typically found in cooling towers, but the results are not limited to just those members, nor only to the FRP structures found in cooling towers.

Keywords: Bearing Analysis, Envelop, Heterodyne, Condition Monitoring Systems

Author: Mark Martich

Full-Text PDF: Bolted Structural Connections In Fiberglass Materials

Gas Turbine Fault Detection Using A Self-Organising Map

Abstract: Turbomachinery condition monitoring and fault detection in the Malaysian oil and gas industry is currently done by monitoring the parameters of the equipment, such as a gas turbine, based on limits provided by the original equipment manufacturer. This is performed in an attempt to avoid any unscheduled downtime and catastrophic failure of the machinery. However, this method has proven to be insufficient and ineffective in providing early information or warning regarding machine faults. This paper presents a case study of a gas turbine that developed a blade fault in an oil and gas plant despite operating within its original equipment manufacturer limits. The parameters used for machinery condition monitoring were then analysed using a self-organising map; a two-dimensional graphical layout consists of neurons arranged in contact with one another. The results demonstrate that such a map is efficient in providing early warning regarding turbomachinery’s health conditions.

Keywords: Gas turbine; condition monitoring; fault detection; self-organising map

Author: Kar Hoou Hui, Ching Sheng Ooi, Meng Hee Lim, Mohd Dasuki Yusoff, and Mohd Salman Leong

Full-Text PDF: Gas Turbine Fault Detection Using A Self-Organising Map

Vibration Sensor with Two-Wire Interface and Bias Used for Measure Temperature

Abstract: A sensor with integrated mechanical transducing and temperature monitoring capability is described. The sensor includes housing containing a transducer, a temperature sensor with associated bias, a summing circuit, and a two-wire cable connector. The transducer is operable to output a dynamic transducer waveform that corresponds to dynamic mechanical perturbations sensed by the transducer. The temperature sensor is operable to output a quasi-static temperature waveform that corresponds to temperatures sensed by the temperature sensor. The summing circuit is operable to combine the transducer waveform and the temperature waveform into a composite modulated voltage bias output signal or modulated current bias output signal. The two-wire cable standard connector is accessible on an outside of the housing and is connectable to a two wire cable that delivers power to the sensor from a power source and delivers the composite output signal from the sensor to a remote data acquisition circuit.

Keywords: Vibration, temperature, sensors, two wire interface

Author: George Zusman

Full-Text PDF: Vibration Sensor with Two-Wire Interface and Bias Used for Measure Temperature

Rolling Bearing Fault Feature Extraction of Casing Vibration Signal

Abstract: The health of rolling bearing plays an important part in the operation of rotating machinery like gas turbine engine. Health monitoring and fault diagnosis of rolling bearings based on vibration signals have been through great development these years. But when sensors are set on the casing instead of the bearing pedestal, and the surrounding structure is very complex, the diagnosis problem becomes much more complicated, which brings more challenges to the signal processing. In this paper, a set of signal processing methods are used to enhance and extract the impact features from casing vibration signals, and to realize the detection of rolling bearing faults. A self-adaptive decomposition method called intrinsic time-scale decomposition (ITD) is applied to decompose the vibration signal into a series of proper rotation components and a monotonic trend, helping to extract dynamic features of the signal. Teager-Kaiser energy operator is a simple algorithm calculating the energy of a signal and is very sensitive to transient impact faults. As the fault feature transmitted to the casing is relatively week, autoregressive model (AR) and minimum entropy deconvolution (MED) are to enhance the non-stationary impact components. Experiments are taken on the rotor-bearing-casing test rig with minor defects in the main shaft bearing. Testing on the casing vibration signal, this fault feature enhancing and extracting method shows its remarkable ability in rolling bearing fault diagnosis.

Keywords: Casing vibration; fault diagnosis; feature extraction; rolling bearing.

Author: Yizhou Yang and Dongxiang Jiang

Full-Text PDF: Rolling Bearing Fault Feature Extraction of Casing Vibration Signal

Misalignment Fault Detection in Dual-Rotor System Based on Time Frequency Techniques

Abstract: In order to improve the energy efficiency and compact structure, the dual-rotor structure including low- pressure rotor and high-pressure rotor has been widely used in aero-engine. Misalignment is one of the most common faults in dual-rotor system, which will causes malfunctions. It is a significant task for rotor dynamics personnel to monitor and defect faults in dual-rotor system. In the paper, the dual-rotor vibration signals are applied to solve the fault identification problem by utilizing time frequency techniques. Numerical simulations are carried out through finite element analysis of dual-rotor system with misalignment fault. Two signal processing tools namely Short Time Fourier Transform (STFT) and Continuous Wavelet Transform are used to detect the misalignment fault and compared to evaluate their diagnosis performance. The effect of addition of Signal to Noise (SNR) on three frequency techniques is presented. Experiments are carried out to obtain the vibration data of dual-rotor test rig and the results from the work show that the technique can be used for the monitoring of misalignment, which will have applications in the condition monitoring and maintenance of various types of rotating machinery.

Keywords:

Author: Nan-fei Wang, Dong-xiang Jiang, Te Han

Full-Text PDF: Misalignment Fault Detection in Dual-Rotor System Based on Time Frequency Techniques

Failure Analysis of A Reactor Cooling Pump Using Modal and Vibration Analysis

Abstract: Two 75 HP pumps redundantly supply cooling water to the reactor pool of the High Flux Isotope Reactor (HFIR) at the Oak Ridge National Laboratory (ORNL). Due to a recent history of premature bearing failures, one of these pumps has undergone maintenance to deal with possible issues of misalignment and base looseness. Vibration analysis and modal analysis including steady state spectrum, operational deflection shape, run up and down order tracking, and modal impact have been utilized to verify the effectiveness of the maintenance and identify possible remaining failure modes. The studies conclude that the pump is, after the maintenance, in an overall good conditional state as per ISO 10816, but a few failure modes remain. These modes consist of some shaft unbalance, considerable shaft misalignment intensified by piping movement, possible motor ground fault, hydrodynamic issues such as cavitation with modal interaction, and base looseness. These failure modes and their supporting data have been used to make suggestions for future maintenance, to verify the effectiveness of the previous maintenance, and to provide a base on which to check future data. This report will cover the testing setup, methodology, analysis results, and maintenance suggestions.

Keywords: Condition monitoring; diagnostics; failure prevention; fault analysis; signal analysis

Author: Thomas J. Hazelwood, Larry D. Phillips, and Blake W. Van Hoy

Full-Text PDF: Failure Analysis of A Reactor Cooling Pump Using Modal and Vibration Analysis

Practical Rotor Dynamics for Users

Abstract: Following a brief overview of the history of the development of key aspects of rotor dynamic technology, this paper describes ways to estimate critical speeds, and cipher them from resonances and other vibration phenomena. The influence of various bearing types on a rotor’s synchronous and non-synchronous dynamics is reviewed. Target audiences for this material are those most likely to be making and interpreting vibration measurements – in other words, machinery users and maintainers.

Keywords: Bearings; critical speed maps; damping; diagnostics; health management; prognostics; rotor dynamics; vibration assessment

Author: Thomas J. Walter

Full-Text PDF: Practical Rotor Dynamics for Users

An Analysis of the Different Aspects of Intelligence in Machines

Abstract: The purpose of this research paper is to technically and philosophically analyze the behaviors of the current intelligent machines and try to think about an eventual artificial evolution. Will Artificial Intelligence (AI) bring us more advantages or more disadvantages? The paper analyzes the different types of intelligent technologies and sees how they are used in security controls, medical researches, military operations, house holding, and maintenance. It will take a look also at the cybernetic and robotic aspects of the topic, and see how they affect the military conflicts taking as points of reference the cyberterrorism and the design of new war-robots. The research will explain how everything started, how everything is quickly developing, and how the technological progress is affecting the human being. How will we react to this new intelligent machines in the future? Will they ever be able to overcome the human intelligence with an eventual artificial consciousness, more advanced learning skills and faster times of execution? Is it really coming up a new era? Are we really creating our successors or it is just science fiction?

Keywords: Intelligent machines, artificial intelligence

Author: Gabriele Veltre, Vukica Jovanovic, Anthony W. Dean, and Charles Daniels

Full-Text PDF: An Analysis of the Different Aspects of Intelligence in Machines

Calibrating Cyber Security Risks

Abstract: Hardly a day goes by anymore without hearing about a cyber security event in the news. In this paper/session, we will analyze the risk associated with smart devices, calibration, and maintenance that could compromise the cyber security status of operations and possibly our entire companies. As a nuclear power plant operator and electronic technician, we never considered the security risk of having an instrument calibrated by a third party. Today however, things have changed significantly and it is common to find microprocessors in virtually everything including the instruments we are using in our plants. The microprocessor has made significant impacts in performance and communications and consequently might be weakening your organization’s security. Analysis presented will discuss the real risk associated with different types of instrumentation and devices, network topologies, and technologies used in smart devices and systems. Additionally, we will analyze the possible effects on safety systems and how to compensate for them and how to protect your systems.

Keywords: Calibration Risks, Calibration Cybersecurity Risks, Malware Insertion

Author: James McGlone

Full-Text PDF: Calibrating Cyber Security Risks

A Comparative Study On Anomaly Detection Of The Combustion System In Gas Turbines

Abstract: Due to the fact that the combustion system, the core component of gas turbines, works in the highly adverse environmental conditions of high temperature and high pressure, it frequently faces malfunctions, causing catastrophic accidents. Hence, anomaly detection plays an important role in helping the combustion system run safely and economically. In recent decades, some methods have been published on anomaly detection of the gas turbine combustion system. However, there are few studies that compare these methods. The aim of this paper is to review and provide analytical results of the anomaly detection methods. An overall assessment of the merits or weaknesses of the generic methods is provided by testing the methods with actual gas turbine operating data. Additionally, some possible research development of the anomaly detection of the gas turbine combustion system is presented in this comparative study.

Keywords: Anomaly detection; gas turbine; combustion system; health management

Author: Jiao Liu, Myeongsu Kang, Jinfu Liu, Zhongqi Wang, Daren Yu, Michael G. Pecht

Full-Text PDF: A Comparative Study On Anomaly Detection Of The Combustion System In Gas Turbines

Shelf Life Evaluation Method for Electronic and Other Components using a Physics-of-Failure (POF) Approach

Abstract: Shelf lives are not well understood in the electronics industry. Despite the existence of recommended shelf lives for some units from standards or manufacturers’ documents, many electronic parts are stored well beyond their recommended shelf lives for different reasons. In many cases, ‘expired’ parts are found to work fine after many years of extended storage, which gives extra motivation for parties along the supply chain, typically part user companies, to extend storage of their parts and to evaluate the ‘actual shelf lives’ of their components. The combination of motivations to extend shelf life, inadequacies in recommended shelf lives, and the lack of knowledge and guidelines to shelf life determination often results in arbitrary storage periods and conditions of electronic components in the industry. In this article, common pitfalls of recommended shelf lives are identified. Then, a physics of failure (PoF) approach to evaluate shelf lives overcoming such pitfalls is proposed. The philosophy we introduce in this approach applies to most storage-induced effects for electronic parts and the approach is described with an electrolytic capacitor in this article.

Keywords: Shelf life; Storage

Author: Nga Man Li, Diganta Das, Michael Pecht

Full-Text PDF: Shelf Life Evaluation Method for Electronic and Other Components using a Physics-of-Failure (POF) Approach

A Novel Approach for Machinery Health Prognostics Using Statistical Tools

Abstract: Condition based maintenance of machinery is being much talked about in the engineering sector of defense and commercial industry. A lot of expenditure is generally incurred on condition monitoring of machinery to avoid unexpected downtimes and failures vis-à-vis optimizing machinery operation. The concept is ever evolving due to technological advancements as well as with the emergence of unique nature of defects. Vibration Analysis is a potent tool of condition monitoring for prediction and diagnostics of machinery failures. Presently, time and frequency spectra are being widely used for defect diagnostics of machinery. However, they require signal conditioning to eliminate noise and to enhance resolution of spectrum. Extensive research in the area of signal processing has been undertaken to refine time and frequency spectra. Notwithstanding application of statistical tools for analysis of various defects in machinery using condition monitoring data can be a viable option. Research in this area, where statistical models have been applied, revealed encouraging results. In this paper, we have modeled bearing vibration data by applying time varying Markov Switching Auto Regressive method which was found very helpful in estimating RUL of machinery.

Keywords: Autoregressive; Defect frequency; Forecasting; Markov switching; Prognostics; Regime, Time variant

Author: Murtaza Hussain, Asif Mansoor, Qaisar Ali

Full-Text PDF: A Novel Approach for Machinery Health Prognostics Using Statistical Tools

Review of Data-Driven Prognostics and Health Management Techniques: Lessons Learned from PHM Data Challenge Competitions

Abstract: Machine learning and statistical algorithms are receiving considerable attention during the past decade in prognostics and health management (PHM). However, there is a lack of consensus and methodology on algorithm selection in different scenarios, which renders the random implementation of machine learning algorithms and inefficient development processes. PHM Data Challenge, an open data competition specialized in PHM, includes diverse issues in industrial data analytics and thus provides abundant resource for study and appropriate approach development. In this work, we first summarize the problems and datasets of PHM Data Challenge competitions. According to their objectives, the 9 problems can be classified into 3 categories, health assessment, fault classification and remaining useful life prediction. Second, common issues and unique challenges have been clearly pointed out for each problem and each category. Then, we analyze all solutions regarding what type of strategy a particular solution took, what algorithms it used and how it overcame the challenges. At last, insights in PHM solution strategies have been summarized to conclude the paper.

Keywords: Diagnostics; Prognostics; Health Assessment; Data Challenge Competition; Fault Classification; Remaining Useful Life Prediction

Author: Bin Huang, Yuan Di, Chao Jin and Jay Lee

Full-Text PDF: Review of Data-Driven Prognostics and Health Management Techniques: Lessons Learned from PHM Data Challenge Competitions

Risk Assessment of Transition to Lead-Free Electronics Assembly

Abstract: The European Union’s Restriction on Hazardous Substances (RoHS) Directive, imposed on electronics manufacturers in 2006, banned the use of certain toxic substances such as lead and cadmium in components and assemblies. Removal of lead which was used in solder, die attaches and surface finishes has introduced reliability risks such as thermo- mechanical fatigue, tin whiskers, tin pest, electro-chemical migration, and corrosion. Due to these concerns, certain reliability-critical industries such as medical, defense, and automotive were either exempted or excluded from these restrictions. Since the commercial electronics sectors have switched to lead-free materials, few suppliers now produce lead- based solders and surface finish boards. Hence there is a growing supply chain pressure on these exempted and excluded industries to switch to lead-free materials. However, they are hesitant to transition to lead-free due to previously said reliability concerns remaining with lead-free assemblies. This study analyses possible failure modes and mechanisms to assess these reliability risks in this transition. The critical failure mechanisms included thermal and mechanical fatigue and tin whiskers. Simulation was conducted using CalcePWA software to compare the reliability between tin-lead and SAC305 solder under temperature cycling and vibration loading in addition to assessing the risk due to tin whiskers. The discussion is mainly focused on concerns about the changes in manufacturing practices, effects of storage and handling conditions on manufacturing defects, while susceptibility to other failure mechanisms are briefly discussed. The study provides assessment and important factors to be considered and monitored during lead-free transition.

Keywords: Lead-free, ENIG, Reliability, RoHS, Transition

Author: Guru Prasad Pandian, Diganta Das, Michael Osterman, and Michael Pecht

Full-Text PDF: Risk Assessment of Transition to Lead-Free Electronics Assembly

Novel Micro, Wireless, MEMS-Based Condition Monitoring System for Modern Machine Tools with Limited Access

Abstract: Currently available condition monitoring systems (CMS) offer many types of tools, including stationary systems, portable on-site instrumentation and finally wireless, autonomous systems. However, for a particular group of modern machine tools with limited access, like lathes, milling or grinding machines, none of this tools could be used due to limited access, space constraints and cabling restrictions. Firstly, stationary CMS use wires connecting vibration sensors with data acquisition unit (DAQ), which are prohibited by both, safety and topological reasons because of sealed door. Secondly, portable systems could not be used, because modern mining machinery is entirely closed, and a diagnostic engineer is not allowed to be present inside the machine housing while operating. Moreover, some of machines perform open lubrication, which makes supervised monitoring impossible due to constant lubricant splashes. Tertiary, currently available leading wireless sensors are characterized by relatively significant size, ca. 1.5 by 4 inch, and close to 10 oz. weight; therefore, introducing significant volume and mass to the machine spindle. Moreover, the rapid characteristics of the spindle movement would generate a significant inertia to the sensor causing extra vibrations and possible detriment to sensor mounting. For these reasons, modern machine tools are generally not equipped with external CMS systems. Recently developed MEMS technology made it possible to design a novel, small-size unit, which is capable to work autonomously in environments with limited accessibility, where volume and weight matter. In contrast to commonly used piezoelectric accelerometers, MEMS vibration sensors need much less operational power, which is a major concern in wireless designs. Moreover, latest MEMS sensors are characterized by comparable frequency response to accelerometers. The short range wireless communication can be applied to avoid connecting cabling. The paper shows a prototype of a micro-size unit for data acquisition, data processing, data storage, and transfer. The prototype is evaluated on industrial lathe.

Keywords: Condition monitoring system; diagnostics; microelectromechanical sensors; micro data acquisition system; portable machine health management tools; wireless vibration sensors

Author: Wojciech Staszewski, Adam Jablonski and Tomasz Barszcz

Full-Text PDF: Novel Micro, Wireless, MEMS-Based Condition Monitoring System for Modern Machine Tools with Limited Access

Local Fault Diagnosis of Non-Stationary Gearbox Based on Order Envelope Analysis

Abstract: Tooth root crack is a common fault in gear system, it’s of significance to detect the crack fault during the operation process of the gearbox. However, the gearbox usually working in a non-stationary condition, namely speed or load are time varying, which increases the difficulty of fault diagnosis since the statistic features and spectrum vary by time. In this paper, an order envelope analysis method is proposed for fault diagnosis of a two stage gearbox with local crack fault under non-stationary working conditions. Firstly, an accelerometer and an encoder are mounted on the gearbox to acquire non-stationary vibration data and rotating speed, respectively. After that, the angle domain signals are derived from the non-stationary vibration data by interpolation algorithm. Then envelope analysis is employed for the angle domain signals to detect the crack characteristic frequency components in envelope spectrum. Finally, the proposed approach is assessed by seeded tooth root crack fault in different working conditions, results show that the new method can effectively detect the tooth cracks in various non-stationary working conditions.

Keywords: Fault diagnosis; non-stationary; order envelope analysis; tooth crack

Author: Liming Wang, Yimin Shao, Pan Sun, Fang Guo and Jing Liu, Chaokun Gu and Ben Zhou

Full-Text PDF: Local Fault Diagnosis of Non-Stationary Gearbox Based on Order Envelope Analysis

A Failure Polymorphism Theory for System Reliability Modeling Considering Failure Mechanisms Correlativity

Abstract: There is a ‘polymorphism’ phenomenon in biology, which means individuals evolve to two or more clearly different phenotypes in the same population of a species, as a result of internal species gene and external environment condition. A similar ‘failure polymorphism’ phenomenon exists in complex systems. The failure modes in a complex system originate from different failure mechanisms. Failure mechanism is the root cause of product failure, and experts are used to paying attention to failure dependence problem by studying the failure behavior, few researches is conducted from the failure mechanisms correlation perspective. In this paper, polymorphism related concepts are incorporated into reliability field, new definitions of failure polymorphism are discussed, and Bayesian framework is introduced to tackle the problems of uncertainty factors and dynamic evaluation. Based on physics of failure (PoF), the paper presents a system-level reliability evaluation method considering the mechanisms correlativity.

Keywords: failure polymorphism; failure mechanisms correlativity; physics of failure; Bayesian framework

Author: Chaojie Qi, Yufeng Sun and Yaqiu Li

Full-Text PDF: A Failure Polymorphism Theory for System Reliability Modeling Considering Failure Mechanisms Correlativity

Reducing The Impact Of Test Bench Component On The Thrust Margin Measurement

Abstract: Turbofan main performance characteristics is its thrust. The engine is sold for a given thrust and cannot be deliver under a minimum threshold. Hence it is fundamental to evaluate thrust with precision. However, reception tests when all engine functions are verified before delivering to each airline company are realized in different bench test cells, under different weather conditions, with different pilots, and so on. All those context variations implies that the measurement is far to be normalized. Moreover, the certification process propose computation of a marginal thrust (𝑀) which is the relative difference between standard thrust (𝑇̅) and a specified value (𝑇0): 𝑀 = (𝑇̅ − 𝑇0)/𝑇0. The standard thrust is obtained from the measurement in the bench test reported to normal standard ISO conditions. This is computed for each rating proposed for each type of engine. The ratings correspond to the ability to power a given aircraft but in this first study we only consider the most restrictive rating. Even after releasing the acquisition context constraints we still observe that the thrust margin is widely dispersed due to the test conditions. The dispersion of the thrust margin results from the complexity of the test conditions such as: complementary technical adaptations (ATC), benches and sites. Thus, it has been found that the measurement of the thrust margin is particularly influenced by certain important components such as secondary nacelle and the bench itself. One of our objectives is to make the thrust margin independent of the test conditions and to reduce its dispersion. This task is complicated by the fact that engine parts comes from different providers and we also try to follow the production trends of each part supplier independently. The resolution technique consists of two steps. During the first step we describe the evolution of the thrust margin independently of the absolute level resulting from one or more components of the bench, we proceed as follows: we associate each measure of thrust margin to a stable period where the test conditions are constants. A mean value is attributed to each stable period. Then we identify the gap between the evolution of the measured thrust margin and the mean value independent from the measure conditions. Once the average model evolution of the margin of thrust is set up. The second step is to identify the average bias introduced by each component of the bench. 2 Concretely, the application of this method has made it possible to reduce by about a factor of 2 the dispersion of the thrust margin, hence achieving a gain in accuracy of the measure by 50% and allowing us to ensure a continuous and accurate monitoring of the calibration of the benches and components based on operational measures, characterize the trends quality of the FAN blades provided by the suppliers, make measures of thrust margin more robust against the evolutions of the test conditions.

Keywords: Turbofan Engine Performance; Thrust; Normalization; Bench Test Cells; Fabrication Process

Author: Mohammed Meqqadmi and Jérôme Lacaille

Full-Text PDF: Reducing The Impact Of Test Bench Component On The Thrust Margin Measurement

Thermal Degradation of Polyimide Insulation and its Effect on Electromagenetic Coil Impedance

Abstract: The failure of insulation in electromagnetic coils is a significant cause of coil failure and can have severe implications for the system in which the coil is used. Impedance monitoring of coils has emerged as a promising avenue for evaluating the insulation health of electromagnetic coils in-situ. Due to its excellent mechanical properties and ability to endure high temperatures, polyimide is widely used as an insulator in the electromagnetic coil manufacturing industry. However, little information is known about the electrical behavior of polyimide insulation when subjected to the variety of stresses experienced when used as electromagnetic coil insulation, casting uncertainty on the use of impedance monitoring when monitoring polyimide insulation health. This paper presents an experimental analysis of how the insulation electrical parameters evolve over time, and their consequent effect on the coil impedance spectrum, thus providing useful empirical evidence for impedance monitoring for electromagnetic coil insulation health monitoring.

Keywords: Condition monitoring, electromagnetic coil insulation, insulation health monitoring, impedance measurement, insulation capacitance, insulation resistance, polyimide thermal degradation

Author: N. Jordan Jameson, Michael H. Azarian, and Michael Pecht

Full-Text PDF: Thermal Degradation of Polyimide Insulation and its Effect on Electromagenetic Coil Impedance

Detection of Lubrication Starvation in Ball Bearings and Preload Effects

Abstract: Detection of lubricant starvation in ball bearings is essential to maximize their lifetime. The lack of lubrication introduces impulses in the vibration signal related to fundamental train and ball spin frequencies. The phenomenon is attributed to the lack of a damping to dissipate the impacts of the balls when entering to the load zone together with the gap increase between bearing components, previously filled by lubricant. This work presents an experimental vibration analysis to study the effect of preload as a mean to decrease the extra clearance in dry conditions and eliminate the source of impulses that characterize lubrication starvation. Furthermore comparison between RMS, Crest Factor and Kurtosis reveals that an increase in preload indeed reduces the signal impulsivity and kurtosis proves to be an effective method to detect lubricant starvation. Finally, the application of fast-kurtogram algorithm is used as a pre-processing method to improve the performance of kurtosis in detecting of lubrication starvation.

Keywords: Ball bearing; crest factor; fast-kurtogram; kurtosis; lubrication starvation, RMS.

Author: Jorge A. Mijares, Bryan P. Rasmussen and Alexander G. Parlos

Full-Text PDF: Detection of Lubrication Starvation in Ball Bearings and Preload Effects

Research into Reliable, Intelligent and Cost Effective Use of Accelerometers for the Condition Monitoring of Rotating Machines

Abstract: This paper presents fundamental work being carried out on designing and building an intelligent monitoring system based on vibration measurements The vibration sensor, e.g. the accelerometer, is the main element in the condition monitoring system and all the signal processing and decision-making depend upon its performance. Unfortunately, the high cost of accelerometers limits their usage, especially, when simple electronic circuitry interfacing is essential and the bulky and costly additional charge amplifiers are unsuitable, particularly in smart and wireless vibration measurement systems. MEMS-based accelerometers offer an alternative solution owing to their low cost and small size. However, MEMS accelerometers are delicate and cannot stand harsh industrial environments, although no thorough investigation into their performance within such an environment has been carried out. In this paper, three newly-developed MEMS accelerometers, from different manufacturers, were packaged in-house and their performances were examined and compared with a well- known piezoelectric accelerometer. A 1.1 kW three phase induction motor test rig was purposely designed and built for this research to undertake vibration measurements and condition monitoring testing. MEMS accelerometers performance testing was carried out under different motor speeds and load conditions. Two types of common faults were also introduced, namely, phase imbalance, an electrical fault, and misalignment for the mechanical type of fault. It was concluded that the performance of one of the MEMS accelerometers was improved by the packaging strategy; reasonable and comparable results were achieved.

Keywords: intelligent, condition monitoring, MEMS, induction motor

Author: Rmdan Shnibha

Full-Text PDF: Research into Reliable, Intelligent and Cost Effective Use of Accelerometers for the Condition Monitoring of Rotating Machines

Fault Detection in Bearings Using Autocorrelation

Abstract: Autocorrelation is a special case of cross-correlation wherein a signal is correlated with a time-lagged version of itself – the resulting signal comprises only the periodic information from the original signal whilst eliminating noise. This property of autocorrelation can be particularly useful in analyzing bearing faults since vibration data from a bearing, with local faults/defects, consists of cyclostationary acceleration signals usually contaminated with noise from sensors and other environmental factors. This study introduces a method which provides early failure warning in rolling element bearings by applying an autocorrelation operation to vibration data. The Sequential Probability Ratio Test (SPRT) is used to detect anomalies indicative of incipient failure. The results from the autocorrelation analysis are compared with results from a simple moving-RMS analysis of the acceleration data. The developed method is shown to provide an earlier warning of failure than the RMS-based method. This method can detect early stages of degradation in bearings – which in turn allows earlier scheduling of maintenance and the avoidance of system failures.

Keywords: Autocorrelation; bearings; diagnostics; health management; prognostics; SPRT;

Author: Rushit N. Shah, Michael H. Azarian and Michael G. Pecht

Full-Text PDF: Fault Detection in Bearings Using Autocorrelation

Repair of Simulated Battle Damaged Aluminum Using Cold Spray Technology

Abstract: The US Army Research Laboratory was asked by the US Army Tank Automotive Research, Development and Engineering Center (TARDEC) to research the feasibility of cold-spray repairing aluminum armor panels that were shot at with 20-mm fragment simulating projectiles. The through-holes were filled using the CGT4000 cold-spray equipment. The repairs were deemed successful, since the objective was to provide protection against anticipated chemical, biological, radiological, and nuclear exposure, and to make the armor air and water tight. This result puts cold-spray technology on par with the current hull and metal component repair requirement which states, “Hull patches do not provide any additional ballistic protection; they are designed to maintain hull integrity (air/water tight).”

Keywords:

Author: Carl Paxton, Dennis Miller, Blake Barnett, Victor Champagne, Marc Pepi

Full-Text PDF: Repair of Simulated Battle Damaged Aluminum Using Cold Spray Technology

Reliability Modeling of Complex Multi-State System Based on Bayesian Networks

Abstract: Traditional reliability analysis methods are not suitable for some systes with multi-state probability. In this paper, a Bayesian Network based multi-state reliability model is built according to the state relationship between the system and its constituting components. Universal generating function is used to build the conditional probability table of the non-root nodes. Based on this, a method of computing the system failure state’s probability is proposed. The algorithm of the importance of each component in the system is inferred. Combined with an example of a typical natural gas pipeline compressor zone system is given. The result shows that this method in this paper provides a simple and intuitive measure to deal with the reliability analysis of natural gas pipeline compressor zone system with multi- state property. The reliability level can be evaluated and the affection of each component to the system reliability can be confirmed effectively.

Keywords: Multi-state reliability; universal generating function; Bayesian Network

Author: Fangfang Shao, Yaqiu Li and Yufeng Sun

Full-Text PDF: Reliability Modeling of Complex Multi-State System Based on Bayesian Networks

Performance Monitoring of Soccer Players using Physiological Signals and Predictive Analytics

Abstract: With the rapid advancement in wearable sensor technologies and predictive analytics, college and professional sports teams are facing new opportunities of leveraging such technologies and at the same time challenges of maintaining their competency. In professional sports today, the margin between winning and losing is narrow although its impact can be massive. Effective use of predictive analytics along with the implementation of advanced sensors can bring about a deeper understanding of players’ physical condition and performance potential throughout individual games or the entire season, and help sports medicine personnel get the most from available resources while keeping players healthy and minimizing their risks of injury. This paper presents a predictive analytics framework for analyzing and predicting soccer players’ performance data. The data consists of GPS and physiological measurements, collected from female soccer players during both practices and games using Zephyr Bioharness device. The proposed framework consists of data cleaning, filtering, visualizations and analytics modules to provide deeper insights into the data. The preprocessing modules automatically remove outliers using intelligent tools and determine first half, second half and potential overtime RISKS based on data patterns. Furthermore, comparison-based metrics have been developed to analyze the performance of players from different aspects including their activity level, fitness and consistency. For instance, Kolmogorov-Smirnov (KS) test was utilized to extract performance metrics based on players’ Heart Rate and Speed, or a Neural Network-based approach was utilized to analyze the Heart Rate recovery rate of the players and quantify their recovery rate, which is important for effective play. At the end, different visualization tools were used to combine players’ 2 running patterns and speed profiles, along with various metrics. Potentially clinically relevant trends related to objective performance parameters could be observed for players during individual games and the entire season which can provide the athletic training staff with a better understanding of player’s performance and inclines or declines in their performance. Future work could validate the methodology for return to play, safe play and pull from play decision tools for the coaching and training staff. The tools used for analyzing biological signals can also be expanded for other applications involving human performance monitoring.

Keywords: Sports analytics; physiological signal analysis; human performance monitoring; soccer; wearable sensors;

Author: Sampurna Ravindranathan, Hossein Davari Ardakani, Andrew Pimental, and Jay Lee, Robert Mangine. PT, ATC, Joseph F. Clark

Full-Text PDF: Performance Monitoring of Soccer Players using Physiological Signals and Predictive Analytics

Health and Usage Monitoring: Critical Components Analysis

Abstract: The following paper is centered on the premise the Intelligent Transportation Systems (ITS), the self-driving automobile and the environment in which it operates will require the automobile to have an on-board Health and Usage Monitoring Systems (HUMS) to operate safely on roadways. HUMS are in their early stages of use to monitor vehicle components and critical structures to prevent routine and catastrophic failures. Vehicle health monitoring, prognostics, diagnostics and condition-based maintenance are the central tenants of a proposed HUMS for autonomous automobiles. Over the past decade, autonomous vehicles have been studied and developed for a real-world application. It is essential to understand the critical assets that need to be monitored in those systems to conduct safe operations in ITS. This paper identifies the components that possibly would be required to monitor and some methods that would be employed to monitor those components.

Keywords: Health and Usage Monitoring Systems, Prognostics, Autonomous Systems, Automobile

Author: Ankit Patel and Dr. John M. Lacontora

Full-Text PDF: Health and Usage Monitoring: Critical Components Analysis

An Approach to Processing Condition-Based Data for use in Prognostic Algorithms

Abstract: Modern Prognostic Health Maintenance/Monitoring (PHM) and Integrated Vehicle Health Monitoring (IVHM) systems use algorithms to process Condition-based Data (CBD) to provide prognostic information and actionable imperatives to support Condition-based Maintenance for the system. Prognostic information comprises the following: estimates of remaining useful life (RUL); estimates of state-of-health (SoH); estimates of prognostic horizon (PH) – also called time-to-failure (TTF) or end-of-life (EOL) estimates. Algorithms, such as Kalman Filtering, are used to condition CBD for further processing to accurately project a future time when data reaches an amplitude level indicative of failure. This paper discusses techniques and methods to first transform CBD into a Degradation Progression Signature (DPS) and then into a Functional Failure Signature (FFS): the latter is particularly amenable to processing by prognostic algorithms to produce estimates, such as RUL, that rapidly converge to alpha ( accuracy bounds of ten percent or better with a convergence efficiency () of at least 50% of the prognostic distance (PD).

Keywords: Prognostics; health management; prognostic distance; alpha accuracy; condition-based data; degradation-progression signature; functional-failure signature; remaining useful life.

Author: James P. Hofmeister, Ferenc Szidarovszky, and Douglas L. Goodman

Full-Text PDF: An Approach to Processing Condition-Based Data for use in Prognostic Algorithms

Prediction of Sensor System Reliability

Abstract: This paper summarized influencing factors to the sensor system reliability used in Oil and Gas industry. A management plan based on criticalities of influencing factors to the overall system is proposed. Prediction of sensor system reliability will be especially useful in the situation where sensor systems can degrade over time in service. A modeling approach has been carried out in this paper to combine the Bayesian network modeling and “Analytical Redundancy relations” methodology for assessing sensor reliability in a digital downhole application.

Keywords: Sensor; Reliability; FMECA; Bayesian network; Digital downhole.

Author: Shan Guan, Christopher Taylor, and Narasi Sridhar

Full-Text PDF: Prediction of Sensor System Reliability

Fault Detection and Estimation in a Class of Distributed Parameter Systems

Abstract: In this paper, the problem of fault detection and isolation in a class of distributed parameter systems (DPS) will be investigated. The behavior of distributed parameter systems is best described by partial differential equation (PDE) models. However, due to complex nature of DPS, a PDE model is traditionally transformed into a finite set of ordinary differential equations (ODE) prior to the design of control or fault detection schemes by using significant approximations thus reducing the accuracy and reliability of the overall system. By contrast, in this paper, the PDE representation of the system is directly utilized to design the fault diagnosis scheme for DPS. Faults that can occur anywhere in the domain of the DPS (referred to as state faults) are considered, rather than only actuator and sensor faults. State faults are significantly more complicated to deal with in the case of DPS since they can be initiated anywhere within a continuous range of space, while in practice sensors are only available at limited locations which in many cases only include the input and/or output sides of the DPS. This problem is tackled by using an observer structure, which includes input, and output filters directly based on the PDE model of the system. A fault is detected by comparing the detection residual, which is the difference between measured and estimated outputs, with a predefined detection threshold. Once the fault is detected, an online approximator is activated to learn the fault function. An update law is introduced for updating the unknown parameters of the online approximator. The stability of the observer along with the online approximator will be discussed analytically in the paper. It is shown that one sensor is satisfactory for fault detection and approximation if the fault function has only one unknown parameter or can be expressed as linear in the unknown parameters. However, additional sensors are required for fault approximation or isolation in the general case. For example, a leakage fault in a pipeline has magnitude and location as unknown parameters and these parameters cannot be approximated by using one sensor. An algorithm is designed to approximate the location of a state fault with unknown magnitude by using multiple sensors. The distributed parameter systems considered in this paper are modelled by parabolic partial differential equations with Neumann or Dirichlet boundary conditions. Heat transfer systems and fluid pipelines are examples of systems in this class of DPS. The scheme is verified in simulations on the aforementioned systems.

Keywords: Diagnostics; prognostics; distributed parameter systems

Author: Hasan Ferdowsi

Full-Text PDF: Fault Detection and Estimation in a Class of Distributed Parameter Systems

How Sensor Mounting Significantly Affects Vibration Measurements

Abstract: Sensor mounting can significantly affect the measured amplitudes of both overall vibration and spectral (FFT) data. This paper shows how the frequency response of a sensor system (accelerometer plus mount) is significantly different than the factory specified frequency response of the accelerometer itself. The sensor system frequency response, using various common mounting methods, such as stud, 2-rail (curved surface) magnet, and flat magnet, were measured under controlled laboratory conditions and then correlated with actual data collected on machinery in the field. The paper also shows the dramatic effect that mounting has on commonly used high frequency measurements such as Spike Energy™ and PeakVue® that are used for early warning of bearing and gear faults. Finally, it explains and shows generically, step-by-step how high frequency demodulation is calculated (e.g., Spike Energy spectrum and PeakVue spectrum).

Keywords: Accelerometer; bearing analysis; demodulation; high- frequency; mounting; sensors; frequency response

Author: David A. Corelli

Full-Text PDF: How Sensor Mounting Significantly Affects Vibration Measurements

Peculiar Cases of Pinion Vibration in Parallel Shaft Double Helical Gear Units - Identification and Mitigation

Abstract: Speed increasing parallel shaft double helical gear units are commonly used in centrifugal compressors and high energy pump applications. Such turbo-gears are API 613 compliant (Titled as -Special Purpose Gear Units for Petroleum, Chemical, and Gas Industry Services) and have horizontal offset transmission line, with journal bearings on the high speed shaft and low speed shaft. When a full load full speed complete unit test is carried out, pinion dynamic behavior is found to be different than what observed during full speed no load condition as mandated in API 613 . During this test, gear box high speed pinion may show up with high vibration or combination of both during certain load and speed combination in spite of proper balancing and alignment. Since full load full speed test is kept as an option in API 613 , hence these type of vibration may not be detected during a no load test in gear box manufacturer’s premises. These types of vibration patterns are not explicitly addressed in API 613 . The first objective of this paper is to cover analytical, design and diagnostic aspects which can be helpful to mitigate above issues before it is towed out from manufacturer’s premises. The second objective of the paper is to suggest installation /innovation / design modification on high speed pinion as a pre-emptive approach which can save time to mitigate if encountered during any certain speed –load combination.

Keywords: Sub -synchronous , relief , super-synchronous , tuning , nodes, FEM

Author: Mantosh Bhattacharya

Full-Text PDF: Peculiar Cases of Pinion Vibration in Parallel Shaft Double Helical Gear Units – Identification and Mitigation

Improving the Safety Management System through HFDM

Abstract: Helicopter Flight Data Monitoring (HFDM) is an integral part of the service provider’s safety management system. By capturing operational information about aircraft activities, the service provider can: identify safety hazards, initiate remedial action to maintain safety performance, facilitate monitoring and assessment of technical interactions between the crew and the aircraft, and facilitate continuous improvement of the safety management system. We wish to improve HFDM by providing aircraft metrics via automation of data download and reporting. Automation is achieved by formalizing the concept of a flight operation, exceedance monitoring and improving the HFDM architectural design to allow for the seamless movement of data. In the extreme, this model for HFDM provides protection of data even in the event of a mishap that would usually only available from crash survivable memory. This paper discusses the formalized concept of a flight operation, how regime recognition is used to support the function of an operation in order to improve the robustness of a HFDM program automated downloading and processing of data.

Keywords: HFDM; regime recognition; HUMS; exceedance monitoring; automated reporting

Author: Eric Bechhoefer and Michael Augustin

Full-Text PDF: Improving the Safety Management System through HFDM

The Flint Water Crisis: Timeline of Events, Evaluation of Technical and Human Factors, and Why it Matters

Abstract: The lead contamination of the Flint, Michigan drinking water supply had its easiest specific “point source” in the economic downturn, which resulted in financial problems for the city, as well as the individual residents, and the eventual appointment of an Emergency Manager by the Governor of The State of Michigan. Bewilderingly, this seemingly well qualified financial manager acted as if he had no legal obligation to consider scientific facts related to enforcement of the Federal Safe Drinking Water Act, and repeatedly ignored warnings given by those with technical backgrounds. He prohibited the City of Flint from continuing their long-term practice of purchasing Lake Huron water from Detroit, and then refused to approve the $137.00 daily cost for the corrosion prevention chemical to be used in the new water supply, taken from the historically polluted Flint River. The combined result of these major factors was a drinking water supply that, at least once, fell within the Federal range for hazardous waste. The most significant physical root cause of the lead contamination was the low pH of the untreated water, which attacked the protective layer of lead oxide which builds up in properly maintained lead and leaded brass water lines. These are an unknown fraction of the total services lines that constituted much of the piping system that delivered the water to the individual homes in Flint. At this time, it is unclear to the writer if the low pH was related to the inherent nature of the water drawn from the river, or to the chlorine compounds used to sterilize it, or both, or other factors. The water was so corrosive that General Motors was forced to stop using it for lubrication in their machining operation, due to corrosion of their engine blocks. [1] Members of Governor Rick Snyder’s inner circle urged the governor’s office to request the Emergency Manager to return the system to the original Detroit source. Yet, the residents of Flint continued to get untreated corrosive water for another year after General Motors switched to a new supply. [2] Almost two years after a local pediatrician started diagnosing multiple infants and children with lead poisoning, two State of Michigan and one City of Flint employee were served with criminal indictments. The City of Flint employee, who, early on, tried to blow the whistle on the situation, has made a plea deal. Potential sources of the severity of the crisis, including the low-ranking science education in the USA, political divisiveness, and lack of critical thinking, will be explored. The human costs of lead poisoning will be summarized.

Keywords: Civil Rights, Corrosion, Crime Rates, Critical Thinking, Department of Environmental Quality, Drinking Water, Educational Outcomes, Environmental Protection Agency, Failure of Democracy, Flint River, Lead Contamination, Lead and Copper Rule, Lead Oxide, Social Justice, Systemic Discrimination, Water Safety

Author: Debbie Aliya

Full-Text PDF: The Flint Water Crisis: Timeline of Events, Evaluation of Technical and Human Factors, and Why it Matters

PHM/IVHM: Checkpoint, Restart, and Other Design Considerations

Abstract: An often overlooked set of services associated with Prognostics Health Monitoring and/or Management (PHM)/Integrated Vehicle Health Management (IVHM) are those associated with Checkpoint and Restart (Save and Restore), which is necessary to save and restore operational states. The design of a framework for a PHM system includes consideration of services and support for resource management, such as the following: (1) “What are the considerations for checkpoint/restart?” (2) “How often should nodes be sampled?” (3) “What are the accuracy and precision requirements? (4) “What are the prognostic distance and horizon requirements?” And (5) “How much noise filtering and mitigation is needed to meet requirements?” The answers to these questions and others are especially important for a PHM system using condition-based data (CBD) to support condition-based maintenance (CBM) solutions. In this paper we present concepts and considerations to provide the reader with basic tools and knowledge as a basis to design the framework of a PHM system.

Keywords: PHM systems; framework for checkpoint (save) and restart (restore); sampling rate; remaining useful life; prognostic accuracy and precision; prognostic distance; prognostic horizon; noise filtering and mitigation.

Author: James P. Hofmeister, Douglas L. Goodman, and Ferenc Szidarovszky

Full-Text PDF: PHM/IVHM: Checkpoint, Restart, and Other Design Considerations

Framework for PHM in the Smart Manufacturing Context: Integration of Different Approaches

Abstract: The technology has advanced at an exponentially high rate since the advent of Internet in the early 90s. The concepts like e-Maintenance, Internet of Things, Industry 4.0 are linked to this advancement in technology. All these have stimulated great potentials in industries and manufacturing. This will boost Prognostics and Health Management capabilities that will need to rely not only on consolidated algorithms and IT architectures, but also on new paradigms related with distributed computing, modularization of tools and development of new services. The paper will address such approach proposing a reference framework to highlight how predictive maintenance can be interpreted according to the new paradigm of Smart Manufacturing. The framework will be supported by an industrial case.

Keywords: Condition based maintenance, Prognostics and Health Management, Smart Manufacturing, Reliability centered maintenance.

Author: Luca Fumagalli and Marco Macchi

Full-Text PDF: Framework for PHM in the Smart Manufacturing Context: Integration of Different Approaches

Condition Monitoring Based on FMECA: A Case Study of Sensor Specifications for Maritime

Abstract: For Maritime, one technical challenge associated with ship machinery condition monitoring is to select the best suitable sensors technology as ship owners always desires an economically viable, maintenance-free while technically reliable monitoring system. In this case study, condition monitoring of a tunnel thruster based on Failure Mode, Effects and Criticality Analysis (FMECA) was chosen to demonstrate the basic approach to overcome this challenge. Based on potential failure modes, four types of condition monitoring technologies including Vibration Monitoring, Acoustic Emission Monitoring, Wear Debris and Water in Oil Monitoring, and Thermal Monitoring are recommended. Out of these technologies, the sensor specification for a reliable vibration monitoring is discussed in detail as an example.

Keywords: Condition Monitoring, Sensor, Vibration, Failure Modes.

Author: Shan Guan, Knut Erik Knutsen, and Øystein Åsheim Alnes

Full-Text PDF: Condition Monitoring Based on FMECA: A Case Study of Sensor Specifications for Maritime

Comparison Between Two Very Efficient Signal Processing Approaches for Vibration-based Condition Monitoring of Rolling Element Bearings: The MED-SK and CS-Based Approaches

Abstract: This paper compares the most efficient signal processing approaches used for vibration-based condition monitoring of rolling element bearings. The first is based on pre-processing the vibration signal through the maximum entropy deconvolution method (MED) followed by the spectral kurtosis (SK), before analyzing the spectrum of the signal envelope. The MED aims at maximizing the signal impulsivity by deconvolving the system transfer function through an optimization approach that maximizes the kurtosis of the output. Then, the spectral kurtosis (SK) is applied to conceive the optimal filter to be applied before computing the envelope spectrum. The second approach is based on a cyclostationary modeling of the bearing signal. It applies the spectral coherence to the signal with a special attention on setting the estimation parameters. The spectral coherence is a bi-variable map of the cyclic frequency, α, and the spectral frequency, f. The former variable describes the cyclic content of the modulations, while the former describes the properties of the carrier. The improved envelope spectrum is then computed by simply projecting its squared-magnitude with respect to the f-variable. These methods are evaluated according to their potentiality to detect the fault in its earliest stage. The comparison is be made on real bearing vibration signals in run-tofailure tests.

Keywords: Condition monitoring; spectral coherence; cyclostationarity; improved envelope spectrum; incipient fault detection; minimum entropy deconvolution; spectral kurtosis

Author: Dany Abboud and Mohammed Elbadaoui, Univ Lyon

Full-Text PDF: Comparison Between Two Very Efficient Signal Processing Approaches for Vibration-based Condition Monitoring of Rolling Element Bearings: The MED-SK and CS-Based Approaches

Analysis and Bearing-Damper Redesign for a $100 Million High Pressure Compressor Failure

Abstract: The Kaybob compressor failure of 1971 was an excellent historic example of rotordynamic instability and the design factors that affect this phenomenon. In the case of Kaybob, the use of poorly designed bearings produced unstable whirling in both the low and high pressure compressors. This required over five months of vibration troubleshooting and redesign along with over 100 million modern U.S. dollars in total costs and lost revenue. The problems began with the use of inadequate five-pad tilting pad journal bearings which produced large ratios of bearing stiffness to shaft stiffness that contributed heavily to the instability. Subsequent designs included attempts at using bearing asymmetry and squeeze film dampers to improve the stability of the machine, however these solutions produced little improvement. The ultimate solution, a redesign of the compressor to a shorter, stiffer machine, resulted in the significant costs incurred as a result of these failed bearing designs. Another reason for the costly nature of this project was a lack of accurate bearing and rotordynamic analysis tools that could have identified the instability during the design process and aided in the redesign of the fluid film bearings supporting the machine. Since the 1970s, a wide range of bearing and rotordynamic analysis tools have been developed that accurately predict the performance of fluid film bearings and rotordynamic systems via the use of practical lubrication theory, finite element analysis, and simple relationships derived as a result of the physical insights gained from using these methods. In this paper, the history of the Kaybob compressor failure is discussed in detail including a discussion of the ineffective bearing designs that were considered. Modern bearing and rotordynamic analysis tools are then employed to study both designs that were considered along with new designs for the bearings that could have ultimately restored 2 stability to the machine. These designs include four-pad, load-between-pad bearings and squeeze film dampers with a central groove. Simple relationships based on the physics of the system are also used to show how the bearings could be tuned to produce optimum bearing stiffness and damping of the rotor vibration, producing insights which can inform the designer as they perform more comprehensive analyses of these systems.

Keywords: Compressor failure; stability failure; compressor design; rotordynamics; fluid film bearings; squeeze film dampers

Author: Edgar J. Gunter, Brian K. Weaver

Full-Text PDF: Analysis and Bearing-Damper Redesign for a $100 Million High Pressure Compressor Failure

Comparative Analysis Of Bearing Health Monitoring Methods For Machine Tool Linear Axes

Abstract: The study of rotating machinery ball bearing diagnostics and prognostics is quite mature and an abundance of methods/algorithms are available to perform these functions. However, extending these algorithms to other ball bearing applications is challenging and may not yield usable results. This work used a linear axis testbed to study the ability of an inertial measurement unit to measure changes in geometric error motions. Faults were introduced on the recirculating ball bearings of one carriage truck with increasing severity. The inertial measurement unit data was analyzed using a variety of methods proposed and used in the rotating machinery community, including auto-regressive filtering, minimum entropy deconvolution, and spectral kurtosis. The results reveal an ineffectiveness of the methods for the induced faults, for this one experiment, which have low signal-to-noise ratio and/or weaker periodicity than faults in rotating machinery.

Keywords: Linear axis, ball bearing, degradation, diagnostics, smart manufacturing

Author: N. Jordan Jameson and Gregory W. Vogl

Full-Text PDF: Comparative Analysis Of Bearing Health Monitoring Methods For Machine Tool Linear Axes

New Possibilities Of Redundant Data Transmission For Intelligent Sensor Networks

Abstract: Condition monitoring systems (CMS) that are currently available offer many types of tools, such as stationary monitoring systems, portable on-site instrumentation, and finally wireless, autonomous systems. Nowadays, the technology related to electronic systems is developing rapidly resulting in the overall improvement within division of data processing (clock speed and number of processing cores), data transfer (speed and power efficiency of communication), and energy consumption. Unfortunately, this development is not being transferred into Condition Monitoring Systems, probably because the complexity of installation and cost of such systems is holding its manufacturers from introducing significant changes in its architecture. A potential point where all modern technologies will culminate is in a technology initiative that is already underway – this is the “Industry 4.0”. It leverages existing and emerging technologies to improve the efficiency, effectiveness, and service that need to be provided in order to be competitive in the future. Recently developed MEMS technology, ongoing trend to create smaller, more energy efficient electronics, followed by rapidly growing tendency for nontraditional devices being connected to the Internet (IoT) made it possible to design novel, small-size measurement units, which are capable of working autonomously as an individual device or in a set of connected devices, as a distributed system. Such a system might utilize ordinary smart phone device as a part in data transmission chain, as enduser device that allows monitoring current state of machine or as a gateway that can transmit measurements further, into the cloud system. Introducing redundant data transmission for such a device allows creating autonomous CMS, which can react to changes in machines operation and changes of the condition of the device itself. The redundant data transmission allows developing different scenarios including priorities for: extending operation time on battery source, maximizing measurement rate or data transmission rate, prolonging the range of sensors network. Ultimately, these new possibilities might lead to self-learning distributed system and intelligent sensors network.

Keywords: Distributed condition monitoring system; diagnostics; IoT; micro data acquisition system; portable machine health management tools; wireless vibration sensors

Author: Wojciech Staszewski, Adam Jablonski And Tomasz Barszcz

Full-Text PDF: New Possibilities Of Redundant Data Transmission For Intelligent Sensor Networks

Comprehensive Condition Monitoring Analysis For Power Plant Boiler Circulator Pumps

Abstract: The boiler circulator pump (BCP) is an integral part of the power plant operations in both conventional (coal/gas fired steam plant) or nuclear plants. The BCP moves super heated water under pressure to the steam generator. These pumps are glandless, megawatt induction power pumps. If the pump fails, the power plant must be removed from service to replace the pump. In many applications, these pumps serve power plant providing the base load power requirements of a community. The failure of a pump requires the operator to buy power from other generating plants at much higher rates. Glandless BCP pose a difficult problem for automated analysis, as there is no way to introduce a tachometer to measure pump speed. Further, while a relatively simple machine, the failure modes include: out of balance/bearing wear that is best measured by vibration, and rotor bar/opens/shorts/eccentricity that is best measured by current. Further, these machines are asynchronous and typically very well balanced, so that is difficult to determine shaft RPM from vibration. This paper discusses the analysis of BCP using both vibration and current analysis methods and the processing needed to automate fault detection, diagnostics, and prognostics.

Keywords: CBM; Diagnostics; Induction Motor; Impact Detection: Rotor Bar;

Author: Eric Bechhoefer and Ed Spence

Full-Text PDF: Comprehensive Condition Monitoring Analysis For Power Plant Boiler Circulator Pumps

Video Motion Amplification Vs. Operating Deflection Shapes For Machinery Diagnosis

Abstract: Operating Deflection Shapes (ODS) has been an important tool in visualizing the vibration of the machine and its system, including piping networks. The input for ODS is the phase-linked signal set from a group of accelerometers, moved over often hundreds of test points. The data is superimposed onto a CAD model, and then scaled-up vibrations are animated at frequencies of interest. This process is time-consuming and therefore expensive each time it is applied by experts, and is error-prone. An alternative method has been developed that is based on evaluation of high resolution/ high speed videos. The method provides information equivalent to a high-sensor-count ODS, by treating each pixel as an accelerometer, using the pixel’s light intensity modulation to translate information embedded in the video into vibration motion able to be observed and interpreted by human investigators.

Keywords: Motion Amplification; video; Operating Deflection Shape; Turbomachinery

Author: William D. Marscher, P.E. & Maki M. Onari

Full-Text PDF: Video Motion Amplification Vs. Operating Deflection Shapes For Machinery Diagnosis

Slow Rollrun Out Problem Of Rotor – Genuine Or Benign

Abstract: The issue of Rotor “run-out” which causes high overall vibration (displacement) readings on rotor has always been a point of concern during spin test and site acceptance test of turbo-machines. Rotor run-out is sub-divided to TIR (total indicated run out) commonly known as Mechanical run out and electrical run out. While API ( American Petroleum Institute ) standards have mandated a certain limit of Slow roll run out, the proposed paper discusses to find which of contributing factors of high runout should be considered as genuine or benign during machinery health assessment and monitoring as its main objective .Proposed paper differentiates rotor bow and slow roll run out , effect of run out during rotor balancing and to points out the lacunae of understanding exits for point / stage of such measurement. A short case study is presented to explain the issue and delays caused for repeated repair works due to such misunderstanding .The paper discusses the feasibility and overall technical effectiveness of eddy current probe, capacitance probe and other devices used . The proposed paper suggests the use of various diagnostic tools such as band and envelope spectrums for creating pre-alarm set up , using shape identification algorithm in diagnostic system based on reference data captured by initial slow roll measurement with a detailed set up .

Keywords: Mechanical run out, electrical run out rotor bow and slow roll eddy current probe, capacitance probe, laser triangulation

Author: Mantosh Bhattacharya

Full-Text PDF: Slow Rollrun Out Problem Of Rotor – Genuine Or Benign

Rotor Design Considerations To Prevent Impeller And Premature Bearing Failures In Centrifugal Fans

Abstract: Centrifugal Fans are subjected to blade-pass pulsation and mass imbalance forces as part of normal operation. Fan impellers have several n-nodal diameter modes of natural frequency that can be sensitive to blade-pass pulsation forces. Excitation of these modes can lead to catastrophic failure. The principal flexural mode of a fan rotor is sensitive to mass imbalance force, and if excited, can result in amplified stresses in the shaft and amplified force transmission to the bearings. In the case of SWSI fan rotors, where the 1-nodal diameter mode of the impeller couples with the flexural mode of the shaft, excitation of the rotor mode can lead to catastrophic failure of the impeller.

Keywords: Blade-pass pressure pulsation, centrifugal fan, critical speed, fan rotor, fan wheel, finite element analysis (FEA), natural frequency, mode shapes, nodal diameter modes, rotor dynamics.

Author: Robert J. Sayer, PE

Full-Text PDF: Rotor Design Considerations To Prevent Impeller And Premature Bearing Failures In Centrifugal Fans

The Dynamic Response Of A Planetary Gear Train In The Presence Of A Spalling Fault

Abstract: Planetary gear trains (PGTs) are widely used in industrial applications. Failure often occurs under working conditions. Tooth surface spalling is one of the most common defects in a PGT system; it seriously affects the reliability and safety of the mechanical transmission system and may even cause serious incidents. However, research into the faults of planetary gear trains is insufficient, especially with respect to the response characteristics of a PGT in the presence of a spalling defect. The paper designs spalling cases with different localized distributions to demonstrate their influence on the dynamic performance of the planetary gear set. The research provides a theoretical basis for health diagnosis and early fault detection for a PGT system.

Keywords: Planetary gear train; spalling defect; dynamic performance;

Author: Keming Zhang, Yimin Shao , Diego Galar

Full-Text PDF: The Dynamic Response Of A Planetary Gear Train In The Presence Of A Spalling Fault

Modeling and Simulation Analysis of Dual-Rotor Vibration System with Multiple Faults

Abstract: Dual-rotor system is an important rotor form in rotating machinery like gas turbine engine. Its complex structure results in rich dynamical behaviors and more probability to failure. The modeling and simulation of the dual-rotor system can help to understand its dynamic characteristics and provide theoretical support for the design, operation and maintenance. In this paper, a dynamic model of a dual-rotor system with multiple rotor faults is established. The dual-rotor vibration model without any fault is built by finite element method, where the two shafts are connected by an inter-shaft bearing and nonlinear models of rolling element bearing and squeeze film damper are considered. The numerical integration method of Newmark-β is used to obtain the steady-state vibration response of the system. Then rotor faults are introduced to the system model, including unbalance, misalignment, looseness and rub-impact. The steady-state responses of single faults in the dual-rotor system are analyzed and typical fault features are obtained. Then coupling characteristics between different rotor faults, and the influences of the squeeze film dampers on the dynamic characteristics and fault features of the system are studied.

Keywords: dual-rotor system, modeling and simulation, rotor faults, rolling element bearing, squeeze film damper.

Author: Yizhou Yang, Chao Liu, Dongxiang Jiang and Wenguang Yang

Full-Text PDF: Modeling and Simulation Analysis of Dual-Rotor Vibration System with Multiple Faults

Pump Vibration Analytics Case Study and the Need for More Deployable Instrumentation

Abstract: Emerging technologies are expanding the implementation of Condition Monitoring to markets and applications not previously practical or economically feasible. This trend is particularly observable as Industrial OEMs develop CBM programs for their own hardware. Data driven analytic approaches to CBM can result in the development of additional monitoring tools and expanded suite of condition indicators using both existing and new instrumentation, augmenting traditional approaches developed for rotating/reciprocating equipment. Transferring learning from the lab to the field introduces challenges and obstacles to deployment that can be overcome by leveraging the convergence of IIoT technologies. The paper will highlight a pump condition monitoring case study, which used data driven analytics to develop new health indicators from vibration signals.

Keywords: Bearing Analysis, Envelop, Heterodyne, Condition Monitoring Systems

Author: Ed Spence, David Siegel

Full-Text PDF: Pump Vibration Analytics Case Study and the Need for More Deployable Instrumentation

Optomized Testing Campaign And Creating Onerous Baseline Data For A Centrifugal Compressor - A Proposal To Manufacturer

Abstract: This paper proposes an optimized testing agenda for centrifugal compressor with a compact manufacturing and testing schedule. As API mandates to conduct mechanical run tests (MRT) of all compressors of similar deign and geometry, it takes a good amount of time to conduct these tests on OEM test bed particularly if numbers of compressors are large. This paper proposes to conduct only one Full load Full speed (FLFS) test as mechanical run test at vendor works among the full lot of same model and design. The intention of the paper is to classify the criticality of compressors and then deliberate on the extent / type of tests taking account of OEM test bed capability and schedule of delivery of machines and then optimize the test agenda .To supplement the FLFS test, the paper proposes to undertake extensive design audit activities in terms of rotor-dynamics, aerodynamics taking account of case histories of past failures which can raise the confidence level of the end user. Assurance of dimensional repeatability in terms of metrology backed by latest methodology of fault identification of multi-layered manufacturing process with PQM, which can avoid multiple tests of similar machines, may avoid multiple third party inspection at various stages thus saving time. In No load MRT site conditions such as influence of process parameters such as gas pressure / density, foundation dynamics are not replicated. The MRT do not identify the region of incipient surge, effect of aerodynamic cross coupling instability as well. The paper proposes to introduce various instruments and sensors to detect the above instability region for the proposed extensive test .With the rotor-dynamic data taken from the proposed test set up, it shall be easy to further enhance the base line data after site performance test .The same can be used for pre-alarm configuration based on zone wise amplitudes in vibration spectrum which can be very useful for reliability engineer engaged in diagnostic and prognostics. For critical machines located in hostile environment, anomaly detection may be carried out with shape identification of plot / spectra.

Keywords: MRT , Full Load test , optimizarion of schedule, rotor-dynamic data

Author: Mantosh Bhattacharya

Full-Text PDF: Optomized Testing Campaign And Creating Onerous Baseline Data For A Centrifugal Compressor – A Proposal To Manufacturer

Improved RotoSense™ for Rolling Stock: Locomotives and Cars

Abstract: This paper describes work related to improving an accelerometer-based sensor, RotoSense™, used for monitoring rolling stock: the locomotives and cars used in trains. At the 2016 MFPT conference, the authors presented a paper, “Accurate Vibration and Speed Measurement on Rotating Shafts using MEMS and IoT Single Wireless Triaxial Sensor,” That sensor was capable of measuring shaft speeds of up to 5500 RPM: two example applications were described: (1) a helicopter gearbox, and (2) conditioning monitoring of a railroad track. This paper describes subsequent improvements to that sensor, in terms of ruggedizing and signal quality, to meet requirements of a manufacturer of rolling stock. The sensor described in the previous paper was the first (and only known) to survive, intact, three days of testing at the National Test Track Center in Pueblo, Colorado, including a 10-hour, non-stop, 400-mile test run. Even so, a manufacturer of rolling stock wanted more ruggedizing and better signal quality. The rationale, the methods, and the results of those improvements are presented in the paper.

Keywords: 

Author: James P. Hofmeister, Wyatt Pena, Robert Wagoner, and Matthew Nielsen

Full-Text PDF: Improved RotoSense™ for Rolling Stock: Locomotives and Cars

Generation Of Tachometer Signal From A Smart Vibration Sensor

Abstract: The tachometer plays an important role in the quality of a vibration-based diagnostic. Because of the bandwidth limits of the machine controller, most machines have a slight change in speed over time. This change in speed necessitate the resampling of the data, based on a tachometer signal, to facilitate shaft, gear and bearing analysis of the machine. This is because a change in shaft rate changes the spectral content of the signal, upon which vibration analysis is dependent. Unfortunately, there may be cases, such as glandless pumps, where due to heat and pressure it is impractical or infeasible to install a tachometer sensor. In other situation, such as monitoring gas turbine engine, interfacing with the existing tachometer for the power turbine or compressor turbine, may change certification requirements (adding cost) or increase system cost and weight. These issues may make adding a tachometer impractical. Using a novel, two step process, we were able to generate a high quality tachometer signal from the vibration data. The first step uses an idealized bandpass filter to remove extraneous vibration signal such that the cyclic rate of the shaft can be constructed. The second step then removes any extraneous jitter in the tachometer signal. The resulting tachometer signal is usually of higher quality than that achievable from a traditional tachometer sensor. The tachometer signal is then used for the time synchronous average or time synchronous resampling algorithms, which are the basis for modern shaft, gear and bearing analysis. We demonstrate the efficacy of the technique on two data sets, showing that the resulting condition indicators are indistinguishable from a system using a traditional tachometer signal as an input.

Keywords: CBM; TSA, Demodulation, Fourier Transform;

Author: Eric Bechhoefer and Ed Spence

Full-Text PDF: Generation Of Tachometer Signal From A Smart Vibration Sensor

Failure Analysis of a Primary Reactor Cooling Pump Using Modal and Vibration Analysis

Abstract: Four pumps redundantly supply primary cooling water to the reactor of the High Flux Isotope Reactor (HFIR) at the Oak Ridge National Laboratory (ORNL). All four pumps underwent maintenance during a recently scheduled downtime. During preliminary evaluation following maintenance, one pump, PU-1A, exhibited higher vibration levels compared to the other three pumps. The pump, being a safety class item, underwent further performance testing to rule out potential damage resulting from the higher vibration. Vibration analysis and modal analysis including steady state spectrum, operational deflection shape, run up transients, and modal impact have been utilized to identify dynamic characteristics that could contribute to the increased vibration levels. This report will cover the testing setup, methodology, analysis results, and recommendations.

Keywords: Condition monitoring, fault analysis, failure prevention, signal analysis, diagnostics

Author: Thomas J. Hazelwood and Blake W. Van Hoy

Full-Text PDF: Failure Analysis of a Primary Reactor Cooling Pump Using Modal and Vibration Analysis

Degradation Modeling from Condition-based Data to Functional Failure Signature Data

Abstract: This paper presents approaches to degradation modeling starting with condition-based data (CBD) and progressing to functional-failure signature (FFS) data: FFS data forms a transfer curve that is very amenable to processing by prediction algorithms in support of a Prognostic Health Monitoring (PHM) system. The approach uses degradation signal models that are previously developed, validated, and presented: for example, an MFPT 2018 paper “Degradation Signal Modeling.” Degradation signal modeling transforms curvilinear, CBD-based signature data into signature data that is much more linearized, which increases the accuracy of prediction information such as remaining useful life (RUL) and state of health (SoH). The focus of this paper is transforming CBD signatures into fault-to-failure progression (FFP) signatures, degradation-progression signatures (DPS), and then into FFS [1]-[3].

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Author: James P. Hofmeister, Douglas L. Goodman, and Ferenc Szidarovszky

Full-Text PDF: Degradation Modeling from Condition-based Data to Functional Failure Signature Data

Crack Propagation In A Compact Tension Specimen Subjected To Gaussian Random Vibrations With Occasional Overloads

Abstract: It is well known that cracks in structural components subjected to overloads manifest delayed growth for some period of time, slowly reverting to the initial rate on a crack-growth rate versus stress-intensity-factor-range curve thereafter. Frequently, constant amplitude fatigue tests with occasional programmed overloads are used to demonstrate the phenomenon. However, in response to random loading in which the sequence of loads is uncertain, different growth rates result from various spectra, even if the distributions from which the loads are taken are identical. This paper examines variations in the number of fatigue cycles necessary for a crack to pass through the plastic zone after a single overload. A Monte-Carlo simulation generates a single initial overload on a compact-tension specimen, creating a large plastic zone, or enclave, ahead of the crack. Following the overload, both minimum and maximum random loads are generated from Gaussian distributions. The Forman equation is used to calculate linear crack growth, i.e., without any retardation, and the Generalized Willenborg retardation model is used to calculate the reduction in the crack-driving potential, KR. The Forman equation is then modified to use the effective stress intensity factor range, ∆Keff, and the effective load ratio, Reff, to calculate the reduced growth rate, which is compared to the linear result. This procedure is repeated for each load cycle until the crack passes through the overload zone, and the number of cycles is recorded. The entire process is then repeated a total of 1,000 times. Using standard hypothesis testing, the resulting crack-growth data are analyzed to determine which distributions cannot be excluded from consideration at the 5% significance level. 95% two-sided confidence intervals are determined for the distribution parameters. The best candidate distributions are overlaid on a histogram to provide graphical results. Finally, the first four 2 statistical moments calculated from the simulation data are compared to those derived using the distribution’s parameters. It was found that lognormal and Birnbaum-Saunders distributions are good fits. The underlying basis of the Willenborg model is that large compressive residual stresses, which reduce the effect of applied tensile loads, exist in the vicinity of the crack tip after an overload. Finite Element Analysis was performed to demonstrate the magnitude and extent of that compressive stress distribution. Normal stress and effective plastic strain results are discussed.

Keywords: Finite element analysis; fracture; Gaussian white noise; Monte Carlo simulation; probabilistic crack growth; statistical analysis; variable amplitude fatigue; Willenborg retardation

Author: Julian Raphael and Peter Liaw

Full-Text PDF: Crack Propagation In A Compact Tension Specimen Subjected To Gaussian Random Vibrations With Occasional Overloads

A Subspace Clustering Chart Using a Reference Model for Featureless Bearing Performance Degradation Assessment

Abstract: The health index (HI) of machine condition must be sensitive and robust in complex working conditions. A systematic HI will assess machine performance automatically, reliably, and in a timely manner without intervention. This paper proposes a subspace clustering HI in a model using reference data on component health. Unlike the conventional HIs empirically learned from raw feature sets, a subspace clustering HI aims to automatically describe the migration and variation of the condition clustering distribution in a series of two-class subspace models derived from the raw data. First, in a featureless process, a covariance-driven Hankel matrix is directly constructed from the raw time-domain signal, and principal component analysis is used to separate the feature subspace and noise null-space. Second, in the index construction process, the reference health subspace data (from healthy data) and the monitored subspace data (from monitored data) are combined to construct a referenced model. Thus, a new spatial clustering HI with kernel operation is implemented to assess the current bearing performance and reveal discriminative features. The effectiveness of the proposed subspace clustering HI for the detection of abnormal condition is evaluated experimentally on bearing test-beds, using a mobile mapping mode. A novel subspace clustering chart, CUSUM-based spatial clustering HI, is developed to depict the real bearing performance degradation. Compared to the regular HI (e.g., root mean square), the proposed approach provides a more accurate and reliable degradation assessment profile with an early fault occurrence alarm. The experimental results show the potential of the proposed spatial clustering analysis to assess bearing degradation.

Keywords: Bearing health monitoring; spatial clustering analysis; subspace clustering chart; featureless process; performance degradation assessment

Author: Xiaoxi Ding, Yimin Shao and Qingbo Heb Diego Galar

Full-Text PDF: A Subspace Clustering Chart Using a Reference Model for Featureless Bearing Performance Degradation Assessment

Towards Point-Of-Need Manufacturing To Replace Failed Components On The Battlefield

Abstract: The DoD is intrigued with “point of need” manufacturing as a means of being able to produce parts “on-demand” in extreme environments such as on a forward operating base, or on a ship, to increase our operational readiness, and reduce our huge military logistics tail. Additionally, research is being performed to determine whether recycled, reclaimed and/or indigenous materials can be utilized as feedstock for these components. However, there are technical challenges that need to be overcome to fully achieve this capability in the future. One such challenge is part quality, and whether such parts can provide a true replacement for military components.

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Author:Marc Pepi, Nicole Zander, Ian Jaqua, Bill Gleason, and Courtney Young

Full-Text PDF: Towards Point-Of-Need Manufacturing To Replace Failed Components On The Battlefield

A Novel Approach for Stress Cycle Analysis based on Empirical Mode Decomposition

Abstract: In real industrial stress/strain analysis applications, calculating equivalent constant amplitude cycles is important. Rainflow counting is a process to obtain equivalent constant amplitude cycles. The method is designed to count reversals in accordance with the material’s stress/strain relationship including hysteresis loops. However, Rainflow counting needs to identify the peaks/valleys in the collected sensor signal and it is sensitive to noise. In this paper, a novel approach is proposed to count the fatigue cycles. The approach first uses empirical mode decomposition method to decompose the signal adaptively. Then a systematic count method is developed to calculate the cycles based on the decomposed signal components. The effectiveness and the performance of this method are compared with the Rainflow counting algorithm on simulated data with different frequencies and levels of noise.

Keywords: Rainflow count, Empirical mode decomposition, Stress cycle analysis, fatigue analysis

Author: Ruoyu Li, Ali Marzban, Jing Ping, Jae Yoon, and Gilbert Chahine

Full-Text PDF: A Novel Approach for Stress Cycle Analysis based on Empirical Mode Decomposition

An Application Of Pattern Anomaly Detection Methods To Fleet-Wide Asset Level Diagnostics

Abstract: Centralized monitoring techniques have become more widely used as business demands and budgetary cuts for companies require streamlined operation and maintenance of a company’s assets. These assets may be located at a single site where the monitoring is taking place, or they may be located all over a state, country or the world. Local data collection with consolidated servers allows a central maintenance center to pool big data for fleet-wide monitoring purposes. Advanced pattern recognition (APR) software solutions have been on the forefront of managing big data for dealing with a multitude of assets. APR techniques can provide evidence that a machine is not operating as expected, but the condition detected could indicate many possible underlying faults. The root cause may still be unknown. Causal network analysis has been widely used in providing differential diagnosis in the medical field when a set of symptoms are known. This method is based on Bayesian probability which can handle uncertainty in the data, both input and output, and has a good theoretical foundation. This paper discusses methods to utilize pattern anomalies as symptoms for a causal network to diagnose asset conditions and to mitigate failures for predictive maintenance programs.

Keywords: Advanced Pattern Recognition; causal networks; asset condition diagnostics; health management; condition-based maintenance; predictive maintenance; centralized monitoring; fleet-wide monitoring; diagnostics; prognostics

Author: Chance M. Kleineke, Nilimb Misal and Michael T. Santucci

Full-Text PDF: An Application Of Pattern Anomaly Detection Methods To Fleet-Wide Asset Level Diagnostics

Machinery Best Practice For Teg Pumps

Abstract: In Oil & Gas industry, before treated gas is exported or supplied to end user, impurity such as water vapor must be removed which helps to prevent hydrate formation and to prevent corrosion in downstream system. The Glycol Dehydration Unit system (GDU System) used for this application includes glycol re-circulation pump which is used to circulate glycol in the glycol contactor. The glycol circulation pump typically operates with low flow and high head. Many package suppliers use reciprocating pump for this application due lower at CAPEX. As compared to rotary pumps, reciprocating pump may have higher OPEX due to high wear and tear and are also prone to pulsation related issues. The accumulator used to dampen pulsation are also prone to failures, if it not selected correctly. Due to low operating speeds, the system may be prone to base frame related resonant excitations. This article aims to discuss the plausible options for the glycol re-circulation pump selection (Centrifugal/Rotary). This article explores the possibilities and benefits to use centrifugal/rotary pump and gives brief insight about the necessary precautions to be taken care to avoid above mentioned issues for reciprocating pumps when selected

Keywords: Glycol pump, dehydration package, reciprocating pump, screw pump, pulsation

Author: Ramkumar Thiraviam & Nirav Doshi

Full-Text PDF: Machinery Best Practice For Teg Pumps

Electromechanical Actuator a Case Study: Multivariate Analysis of Phase Currents to Detect Three Types of Faults

Abstract: This paper describes a multivariate-analysis (MVA) methodology to detect and prognose three types of faults associated with an electromechanical actuator (EMA). The faults are the following: (1) loading faults, such as friction, on the shaft of an EMA motor, (2) shorting faults in the stator windings of the EMA motor, and (3) on-resistance faults in one or more power-switching transistors used to convert direct voltage/current into alternating current. The presented methodology overcomes difficulties associated with typical MVA methods such as the following examples: solving simultaneous equations and performing a statistical-based analysis such as K-nearest neighbor (KNN) regression and other Euclidean-based distance methods. Examples of those difficulties are the following: (1) analyses methods that produced information suitable for classification rather than diagnosis or prognosis; (2) noisy data; and (3) dependent data, rather than independent data (4) difficulty in processing test data to identify, extract, and use leading indicators of failure for prognostic purposes. The primary MVA solution methods included (1) noise mitigation, (2) a unique root-mean-square (RMS) of quantifying phase current values. And (3) a combination of nearest neighbor and distance methods of processing phase-current data to unequivocally identify and isolate faults and to prognose a future time at which functional failure is likely to occur.

Keywords: Diagnostics; electromechanical actuator; EMA; IVHM; multivariate analysis; MVA; prognostics; PHM

Author: James P. Hofmeister, Robert Wagoner, Douglas Goodman

Full-Text PDF: Electromechanical Actuator a Case Study: Multivariate Analysis of Phase Currents to Detect Three Types of Faults

A Quick Introduction to Bearing Envelope Analysis

Abstract: Bearing envelope analysis (BEA) is a powerful technique for the detection of bearing faults. The improper selection of the envelope window frequency and window bandwidth can render the analysis ineffective. This can reduce the ability to perform condition monitoring to correctly identify a degraded bearing. This paper is an analysis of how BEA works in the detection of damage bearings. A description of the BEA is given, methods for window selection, such as spectral kurtosis, is described, and example algorithms are given to facilitate experimentation.

Keywords: Bearing Analysis, Envelop, Heterodyne, Condition Monitoring Systems

Author: Eric Bechhoefer

Full-Text PDF: A Quick Introduction to Bearing Envelope Analysis