Condition Monitoring and Diagnostic Engineering Management
eBook - PDF

Condition Monitoring and Diagnostic Engineering Management

  1. 1,020 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Condition Monitoring and Diagnostic Engineering Management

About this book

This Proceedings contains the papers presented at the 14th International Conference on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2001), held in Manchester, UK, on 4-6 September 2001. COMADEM 2001 builds on the excellent reputation of previous conferences in this series, and is essential for anyone working in the field of condition monitoring and maintenance management.The scope of the conference is truly interdisciplinary. The Proceedings contains papers from six continents, written by experts in industry and academia the world over, bringing together the latest thoughts on topics including: Condition-based maintenance Reliability centred maintenance Asset management Industrial case studies Fault detection and diagnosis Prognostics Non-destructive evaluation Integrated diagnostics Vibration Oil and debris analysis Tribology Thermal techniques Risk assessment Structural health monitoring Sensor technology Advanced signal processing Neural networks Multivariate statistics Data compression and fusion This Proceedings also contains a wealth of industrial case studies, and the latest developments in education, training and certification. For more information on COMADEM's aims and scope, please visit http://www.comadem.com

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Yes, you can access Condition Monitoring and Diagnostic Engineering Management by A. Starr,B.K.N. Rao in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Industrial Health & Safety. We have over one million books available in our catalogue for you to explore.

Table of contents

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