Condition Monitoring and Diagnostic Engineering Management (eBook)

Front Cover 1
Condition Monitoring and Diagnostic Engineering Management 4
Copyright Page 5
Contents 10
Preface 8
Chapter 1. Bearing diagnostics in helicopter gearboxes 18
Chapter 2. Cost impact of misdiagnoses on machinery operation 30
Chapter 3. Detection of rotor-stator rubbing in large rotating machinery using acoustic emissions 38
Chapter 4. Condition monitoring of very slowly rotating machinery using AE techniques 46
Chapter 5. Monitoring low-speed rolling element bearings using acoustic emissions 54
Chapter 6. Condition monitoring of rotodynamic machinery using acoustic emission and fuzzy c-mean clustering technique 66
Chapter 7. Monitoring sliding wear using acoustic emission 74
Chapter 8. Intelligent condition monitoring of bearings in mail processing machines using acoustic emission 84
Chapter 9. Health management system design: development, simulation and cost/benefit optimization 92
Chapter 10. Optimisation of SANC for separating gear and bearing signals 106
Chapter 11. A review of fault detection and isolation (FDI) techniques for control and monitoring systems 114
Chapter 12. A monitoring and diagnostic tool for machinery and power plants, based on chaos theory 120
Chapter 13. Novelty detection using minimum variance features 128
Chapter 14. Intelligent signal analysis and wireless signal transfer for purposes of condition monitoring 136
Chapter 15. Condition monitoring for a car engine using higher order time frequency method 144
Chapter 16. An investigation into the development of a condition monitoring/fault diagnostic system for large reversible Francis type Pump-Turbines 152
Chapter 17. Application of vibration diagnostics and suppression by using the Campbell diagram 160
Chapter 18. A novel signal processing approach to eddy current flaw detection based on wavelet analysis 170
Chapter 19. The wavelet analysis applied for fault detection of an electro-hydraulic servo system 178
Chapter 20. Advanced fault diagnosis by vibration and process parameter analysis 186
Chapter 21. Partially blind source separation of the diagnostic signals with prior knowledge 194
Chapter 22. Comparison of simple multi-attribute rating technique and fuzzy linguistic methods in multi-attribute decision making 202
Chapter 23. Reasoning approaches for fault isolation: a comparison study 210
Chapter 24. Migration to advanced maintenance and monitoring techniques in the process industry 218
Chapter 25. Introducing value-based maintenance 226
Chapter 26. Vibration-based maintenance costs, potential savings and benefits: a case study 234
Chapter 27. Balanced scorecard concept adapted to measure maintenance performance: a case study 244
Chapter 28. Design, development and assessment of maintenance system for building industry in developing countries 252
Chapter 29. Using modeling to predict vibration from a shaft crack 260
Chapter 30. An investigation of abnormal high pitch noise in the Train 2 compressor motor 268
Chapter 31. An approach to the development of condition monitoring for a new machine by example 280
Chapter 32. Condition monitoring and diagnostic engineering – a data fusion approach 292
Chapter 33. Teaching the condition monitoring of machines by understanding 300
Chapter 34. A successful model for academia's support of industry's maintenance and reliability needs 308
Chapter 35. Certification in condition monitoring – development of an international PCN scheme for CM personnel 314
Chapter 36. The exploitation of instantaneous angular speed for condition monitoring of electric motors 328
Chapter 37. Discriminating between rotor asymmetries and time-varying loads in three-phase induction motors 336
Chapter 38. Asymmetrical stator and rotor fault detection using vibration, per-phase current and transient speed analysis 346
Chapter 39. New methods for estimating the excitation force of electric motors in operation 362
Chapter 40. The development of flux monitoring for a novel electric motor 370
Chapter 41. European projects - payback time 378
Chapter 42. The use of the fieldbus network for maintenance data communication 384
Chapter 43. A distributed data processing system for process and Condition monitoring 392
Chapter 44. The physical combination of control and condition monitoring 400
Chapter 45. The design and implementation of a data acquisition and control system using fieldbus technologies 408
Chapter 46. A non-linear technique for diagnosing spur gear tooth fatigue cracks: Volterra kernel approach 416
Chapter 47. Detection of gear failures using wavelet transform and improving its capability by principal component analysis 428
Chapter 48. Dynamic analysis method of fault gear equipment 436
Chapter 49. Diagnosis method of gear drive in eccentricity, wear and spot flaw states 444
Chapter 50. Gear damage detection using oil debris analysis 450
Chapter 51. The generalized vibration spectra (GVS) for gearing condition monitoring 458
Chapter 52. Use of genetic algorithm and artificial neural network for gear condition diagnostics 466
Chapter 53. Fault detection on gearboxes operating under fluctuating load conditions 474
Chapter 54. Detection and location of tooth defect in a two-stage helical gearbox using the smoothed instantaneous power spectrum 482
Chapter 55. Securing the successful adoption of a global information delivery system 490
Chapter 56. Design of a PIC based data acquisition system for process and condition monitoring 498
Chapter 57. Applications of diagnosing of naval gas turbines 506
Chapter 58. Diagnosing of naval gas turbine rotors with the use of vibroacoustic parameters 512
Chapter 59. Computer image analysis of dynamic processes 520
Chapter 60. Inverse method of processing motion blur for vibration monitoring of turbine blade 530
Chapter 61. Artificial neural network performance based on different pre-processing techniques 538
Chapter 62. Fault accommodation for diesel engine sensor system using neural networks 548
Chapter 63. The application of neural networks to vibrational diagnostics for multiple fault conditions 554
Chapter 64. Applying neural networks to intelligent condition monitoring 562
Chapter 65. Data mining in a vibration analysis domain by extracting symbolic rules from RBF neural networks 570
Chapter 66. Application of componential coding in fault detection and diagnosis of rotating plant 578
Chapter 67. Bearing fault detection using adaptive neural networks 588
Chapter 68. Analysis of novelty detection properties of autoassociators 594
Chapter 69. Condition monitoring of a hydraulic system using neural networks and expert systems 602
Chapter 70. Multi-layer neural networks and pattern recognition for pump fault diagnosis 610
Chapter 71. Development of an automated fluorescent dye penetrant inspection system 616
Chapter 72.Non-destructive fault induction in an electro-hydraulic servo system 626
Chapter 73. Identification of continuous industrial processes using subspace system identification methods 632
Chapter 74. Life cycle costing as a global imperative 642
Chapter 75. Six sigma initiatives in the field of COMADEM 650
Chapter 76. Monitoring exhaust valve leaks and misfire in marine diesel engines 658
Chapter 77. Combining vibrations and acoustics for the fault detection of marine diesel engines using neural networks and wavelets 666
Chapter 78. Condition diagnosis of reciprocating machinery using information theory 674
Chapter 79. Experimental results in simultaneous identification of multiple faults in rotor systems 680
Chapter 80. Thermodynamic diagnosis at steam turbines 690
Chapter 81. On-line vibration monitoring for detecting fan blade damage 698
Chapter 82. A hybrid knowledge-based expert system for rotating machinery 706
Chapter 83. Monitoring the integrity of low-speed rotating machines 714
Chapter 84. Detecting and diagnosing faults in variable speed machines 726
Chapter 85. ARMADA CMS – advanced rotating machines diagnostics analysis tool for added service productivity 734
Chapter 86. Condition monitoring and diagnosis of rotating machinery by orthogonal expansion of vibration signal 742
Chapter 87. Comparison of approaches to process and sensor fault detection 750
Chapter 88. The neural network prediction of diesel engine smoke emission from routine engine operating parameters of an operating road vehicle 758
Chapter 89. Early detection of leakage in reciprocating compressor valves using vibration and acoustic continuous wavelet features 766
Chapter 90. Inertial sensors error modelling and data correction for the position measurement of parallel kinematics machines 774
Chapter 91. On-line sensor calibration verification: 'a survey' 782
Chapter 92. The applicability of various indirect monitoring methods to tool condition monitoring in drilling 798
Chapter 93. A palm size vibration visualizing instrument for survey diagnosis by using a hand-held type triaxial pickup 810
Chapter 94. Development of an on-line reactor internals vibration monitoring system (RIDS) 818
Chapter 95. Truncation mechanism in a sequential life testing approach with an underlying two-parameter inverse weibull model 826
Chapter 96. Maintenance functional modelling centred on reliability 834
Chapter 97. An implementation of a model-based approach for an electro-hydraulic servo system 842
Chapter 98. Stochastic Petri net modeling for availability and maintainability analysis 850
Chapter 99. The dynamic modelling of multiple pairs of spur gears in mesh including friction 858
Chapter 100. The modelling of a diesel fuel injection system for the non-intrusive monitoring of its condition 866
Chapter 101. Use of factorial simulation experiment in gearbox vibroacoustic diagnostics 874
Chapter 102. Online fault detection and diagnosis of complex systems based on hybrid component models 882
Chapter 103. Measures of accuracy of model based diagnosis of faults in rotormachinery 890
Chapter 104. Failure analysis and fault simulation of an electrohydraulic servo valve 898
Chapter 105. A multiple condition information sources based maintenance model and associated prototype software development 906
Chapter 106. Plant residual time distribution prediction using expert judgements based condition monitoring information 916
Chapter 107. Optimising complex CBM decisions using hybrid fusion methods 926
Chapter 108. Diagnostics of honeycomb core sandwich panels through modal analysis 936
Chapter 109. Assessment of structural integrity monitoring systems 942
Chapter 110. Experimental validation of the constant level method for identification of nonlinear multi degree of freedom systems 952
Chapter 111. A comparative field study of fibre bragg grating strain sensors and resistive foil gauges for structural integrity monitoring 960
Chapter 112. The application of oil debris monitoring and vibration analysis to monitor wear in spur gears 970
Chapter 113. Identification of non-metallic particulate in lubricant filter debris 976
Chapter 114. Influence of turbine load on vibration pattern and symptom limit value determination procedures 984
Chapter 115. Study on the movement regulation of grinding media of vibration mill by noise testing 994
Chapter 116. Gas turbine blade and disk crack detection using tosional vibration monitoring: a feasibility study 1002
Chapter 117. The flow-induced vibration of cylinders in heat exchanger 1010
Author Index 17
COMADEM 1020