A review on machinery diagnostics and prognostics implementing condition-based maintenance

Staff members at Los Alamos National Laboratory (LANL) produced a summary of the structural health monitoring literature in 1995. This presentation will summarize the outcome of an updated review covering the years 1996 2001. The updated review follows the LANL statistical pattern recognition paradigm for SHM, which addresses four topics: 1. Operational Evaluation; 2. Data Acquisition and Cleansing; 3. Feature Extraction; and 4. Statistical Modeling for Feature Discrimination. The literature has been reviewed based on how a particular study addresses these four topics. A significant observation from this review is that although there are many more SHM studies being reported, the investigators, in general, have not yet fully embraced the well-developed tools from statistical pattern recognition. As such, the discrimination procedures employed are often lacking the appropriate rigor necessary for this technology to evolve beyond demonstration problems carried out in laboratory setting.

A review of structural health monitoring literature 1996-2001

Fault diagnosis of machines via parameter estimation and knowledge processing: tutorial paper

Financial support for this research was provided in part by the National Science Foundation (NSF) under NSF grants CMS 03-01140 and CMS 06-00433 (Dr. S. C. Liu, Program Manager). The first author was supported by a Vodafone-U.S. Foundation Graduate Fellowship. This support is gratefully acknowledged.

http://www.ideals.illinois.edu/bitstream/handle/2142/3521/NSEL.Report.001.pdf?sequence=4

Structural Health Monitoring Using Smart Sensors

Vibration signals extracted from rotating parts of machineries carries lot many information with in them about the condition of the operating machine. Further processing of these raw vibration signatures measured at a convenient location of the machine unravels the condition of the component or assembly under study. This paper deals with the effectiveness of wavelet-based features for fault diagnosis of a gear box using artificial neural network (ANN) and proximal support vector machines (PSVM). The statistical feature vectors from Morlet wavelet coefficients are classified using J48 algorithm and the predominant features were fed as input for training and testing ANN and PSVM and their relative efficiency in classifying the faults in the bevel gear box was compared.

Fault diagnosis of spur bevel gear box using artificial neural network (ANN), and proximal support vector machine (PSVM)

1 Failure types, investigation and occurrences.- 1.1 Introduction.- 1.2 System failure and component failure.- 1.3 Failure decisions.- 1.4 Failure classifications.- 1.5 Types of failure.- 1.6 Failure investigations.- 1.7 Failure case studies.- 1.8 Human factors in failure incidents.- 2 Causes of failure.- 2.1 Introduction.- 2.2 Service failures.- 2.3 Fatigue.- 2.4 Excessive deformation.- 2.5 Wear.- 2.6 Corrosion.- 2.7 Blockage, sludges.- 2.8 Blockage in cooling systems.- 2.9 Design, manufacturing and assembly causes of failure.- 3 Fault detection sensors.- 3.1 Introduction.- 3.2 Contaminant monitoring.- 3.3 Corrosion monitoring.- 3.4 Force monitoring.- 3.5 Gas leakage monitoring.- 3.6 Air pollution monitoring.- 3.7 Liquid contamination monitoring.- 3.8 Non-destructive testing techniques.- 3.9 Optical examination.- 3.10 Temperature sensing.- 3.11 Particle testing.- 3.12 Proximity monitors.- 3.13 Sound monitoring.- 3.14 Vibration transducers.- 3.15 Telemetry.- 4 Data processing and analysis.- 4.1 Introduction.- 4.2 Fourier analysis.- 4.3 Frequency analysis techniques.- 4.4 Derived functions.- 5 Vibration analysis.- 5.1 Introduction.- 5.2 Vibration-simple harmonic motion concept.- 5.3 Vibration signature of active systems.- 5.4 Vibration monitoring equipment.- 5.5 System monitors and vibration limit detectors.- 5.6 Vibration monitoring experience.- 5.7 Critical vibration levels.- 6 Sound monitoring.- 6.1 Introduction.- 6.2 Sound frequencies.- 6.3 Sound loudness measurement.- 6.4 Acoustic power.- 6.5 Sound measurement.- 6.6 Magnetic tape recorders.- 6.7 Sound level meters.- 6.8 Sound analysers.- 6.9 Sound signal data processing.- 6.10 Sound monitoring.- 7 Discrete frequencies.- 7.1 Introduction.- 7.2 Simple vibrations.- 7.3 Transverse vibrations of bars - approximate frequency calculations.- 7.4 More precise evaluations - overtones.- 7.5 Torsional oscillation of flywheel-bearing shafts.- 7.6 Belt drives.- 7.7 Whirling of marine line shafting.- 7.8 Gear excitation.- 7.9 Rolling element bearing.- 7.10 Blade vibration.- 7.11 Cam mechanism vibration.- 8 Contaminant analysis.- 8.1 Introduction.- 8.2 Contaminants in used lubricating oils.- 8.3 Carrier fluid degradation.- 8.4 Contaminant monitoring techniques (wear processes).- 8.5 Oil degradation analysis.- 8.6 Abrasive particles in lubricating oil.- 8.7 Abrasive particles in bearings.- 8.8 Abrasive particles in hydraulic systems.- 8.9 Dissolved gas fault monitoring.- 9 SOAP and other contaminant monitoring techniques.- 9.1 Introduction.- 9.2 Spectrometric oil analysis procedure.- 9.3 Magnetic chip detectors.- 9.4 'Ferrograph' particle precipitation.- 9.5 STM control kit.- 9.6 Used oil blotter test.- 9.7 Thin-layer chromatography.- 9.8 Capacitative oil debris monitor.- 9.9 X-ray fluorescence detection of contamination (XRF).- 9.10 X-ray photoelectron spectrometry.- 9.11 Particle classification.- 10 Performance trend monitoring.- 10.1 Primary monitoring - performance.- 10.2 Primary and secondary performance parameters.- 10.3 Performance trend analysis.- 10.4 Turbine gas path performance monitoring thermodynamics.- 10.5 Steam turbine performance analysis.- 10.6 Case studies in performance monitoring.- 10.7 Performance monitoring systems.- 11 Static testing.- 11.1 Introduction.- 11.2 Visual testing.- 11.3 Liquid penetrant inspection.- 11.4 Thermal methods.- 11.5 X-ray photography.- 11.6 Sonics.- 11.7 Ultrasonics.- 11.8 Stress wave emission.- 11.9 Magnetic testing methods.- 11.10 Electrical NDT techniques.- 11.11 Eddy current testing.- 11.12 NDT selection.- 12 Monitoring systems in operation.- 12.1 Introduction.- 12.2 Marine monitoring systems.- 12.3 Marine condition monitoring requirements.- 12.4 Marine diesel engine monitoring.- 12.5 Marine turbine monitoring systems.- 12.6 Shipboard vibration monitoring.- 12.7 Spectrometric oil analysis programme - marine.- 12.8 Monitoring integrity verification.- 12.9 Aircraft condition monitoring.- 12.10 Condition monitoring - generating plant.- 12.11 Automotive diagnostic equipment.- 12.12 Systematic fault monitor selection.- 13 Fault analysis planning and system availability.- 13.1 Introduction.- 13.2 Availability.- 13.3 Failure prediction/reliability assessment.- 13.4 Hazard rate curve.- 13.5 Complex system reliability - Monte Carlo simulation.- 13.6 Hazardous chemical plants - high integrity protective systems (HIPS).- 14 Reliability/failure concepts.- 14.1 Introduction.- 14.2 Probability of reliability and failure.- 14.3 Failure pattern-exponential distribution.- 14.4 Load and strength - statistical distribution.- 14.5 Reliability assurance -1 Failure types, investigation and occurrences.- 1.1 Introduction.- 1.2 System failure and component failure.- 1.3 Failure decisions.- 1.4 Failure classifications.- 1.5 Types of failure.- 1.6 Failure investigations.- 1.7 Failure case studies.- 1.8 Human factors in failure incidents.- 2 Causes of failure.- 2.1 Introduction.- 2.2 Service failures.- 2.3 Fatigue.- 2.4 Excessive deformation.- 2.5 Wear.- 2.6 Corrosion.- 2.7 Blockage, sludges.- 2.8 Blockage in cooling systems.- 2.9 Design, manufacturing and assembly causes of failure.- 3 Fault detection sensors.- 3.1 Introduction.- 3.2 Contaminant monitoring.- 3.3 Corrosion monitoring.- 3.4 Force monitoring.- 3.5 Gas leakage monitoring.- 3.6 Air pollution monitoring.- 3.7 Liquid contamination monitoring.- 3.8 Non-destructive testing techniques.- 3.9 Optical examination.- 3.10 Temperature sensing.- 3.11 Particle testing.- 3.12 Proximity monitors.- 3.13 Sound monitoring.- 3.14 Vibration transducers.- 3.15 Telemetry.- 4 Data processing and analysis.- 4.1 Introduction.- 4.2 Fourier analysis.- 4.3 Frequency analysis techniques.- 4.4 Derived functions.- 5 Vibration analysis.- 5.1 Introduction.- 5.2 Vibration-simple harmonic motion concept.- 5.3 Vibration signature of active systems.- 5.4 Vibration monitoring equipment.- 5.5 System monitors and vibration limit detectors.- 5.6 Vibration monitoring experience.- 5.7 Critical vibration levels.- 6 Sound monitoring.- 6.1 Introduction.- 6.2 Sound frequencies.- 6.3 Sound loudness measurement.- 6.4 Acoustic power.- 6.5 Sound measurement.- 6.6 Magnetic tape recorders.- 6.7 Sound level meters.- 6.8 Sound analysers.- 6.9 Sound signal data processing.- 6.10 Sound monitoring.- 7 Discrete frequencies.- 7.1 Introduction.- 7.2 Simple vibrations.- 7.3 Transverse vibrations of bars - approximate frequency calculations.- 7.4 More precise evaluations - overtones.- 7.5 Torsional oscillation of flywheel-bearing shafts.- 7.6 Belt drives.- 7.7 Whirling of marine line shafting.- 7.8 Gear excitation.- 7.9 Rolling element bearing.- 7.10 Blade vibration.- 7.11 Cam mechanism vibration.- 8 Contaminant analysis.- 8.1 Introduction.- 8.2 Contaminants in used lubricating oils.- 8.3 Carrier fluid degradation.- 8.4 Contaminant monitoring techniques (wear processes).- 8.5 Oil degradation analysis.- 8.6 Abrasive particles in lubricating oil.- 8.7 Abrasive particles in bearings.- 8.8 Abrasive particles in hydraulic systems.- 8.9 Dissolved gas fault monitoring.- 9 SOAP and other contaminant monitoring techniques.- 9.1 Introduction.- 9.2 Spectrometric oil analysis procedure.- 9.3 Magnetic chip detectors.- 9.4 'Ferrograph' particle precipitation.- 9.5 STM control kit.- 9.6 Used oil blotter test.- 9.7 Thin-layer chromatography.- 9.8 Capacitative oil debris monitor.- 9.9 X-ray fluorescence detection of contamination (XRF).- 9.10 X-ray photoelectron spectrometry.- 9.11 Particle classification.- 10 Performance trend monitoring.- 10.1 Primary monitoring - performance.- 10.2 Primary and secondary performance parameters.- 10.3 Performance trend analysis.- 10.4 Turbine gas path performance monitoring thermodynamics.- 10.5 Steam turbine performance analysis.- 10.6 Case studies in performance monitoring.- 10.7 Performance monitoring systems.- 11 Static testing.- 11.1 Introduction.- 11.2 Visual testing.- 11.3 Liquid penetrant inspection.- 11.4 Thermal methods.- 11.5 X-ray photography.- 11.6 Sonics.- 11.7 Ultrasonics.- 11.8 Stress wave emission.- 11.9 Magnetic testing methods.- 11.10 Electrical NDT techniques.- 11.11 Eddy current testing.- 11.12 NDT selection.- 12 Monitoring systems in operation.- 12.1 Introduction.- 12.2 Marine monitoring systems.- 12.3 Marine condition monitoring requirements.- 12.4 Marine diesel engine monitoring.- 12.5 Marine turbine monitoring systems.- 12.6 Shipboard vibration monitoring.- 12.7 Spectrometric oil analysis programme - marine.- 12.8 Monitoring integrity verification.- 12.9 Aircraft condition monitoring.- 12.10 Condition monitoring - generating plant.- 12.11 Automotive diagnostic equipment.- 12.12 Systematic fault monitor selection.- 13 Fault analysis planning and system availability.- 13.1 Introduction.- 13.2 Availability.- 13.3 Failure prediction/reliability assessment.- 13.4 Hazard rate curve.- 13.5 Complex system reliability - Monte Carlo simulation.- 13.6 Hazardous chemical plants - high integrity protective systems (HIPS).- 14 Reliability/failure concepts.- 14.1 Introduction.- 14.2 Probability of reliability and failure.- 14.3 Failure pattern-exponential distribution.- 14.4 Load and strength - statistical distribution.- 14.5 Reliability assurance - BS 9000 system.- 15 Reliability data sources.- 15.1 Introduction.- 15.2 Systems Reliability Service (SRS).- 15.3 Failure data.- 15.4 Environmental influences on instrument failure rates.- 15.5 Failure data-confidence level.

Mechanical fault diagnosis and condition monitoring

Mechanical vibrations, their calculation, measurement, effects and suppression

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Mechanical fault diagnosis and condition monitoring

Mechanical vibrations, their calculation, measurement, effects and suppression