INTELLIGENT FAULT DIAGNOSIS
AND PROGNOSIS FOR
ENGINEERING SYSTEMS
Intelligent Fault Diagnosis and Prognosis for Engineering Systems. G. Vachtsevanos, F. Lewis, M. Roemer
A. Hess and B. Wu © 2006 John Wiley & Sons, Inc. ISBN: 978-0-471-72999-0
INTELLIGENT FAULT
DIAGNOSIS AND
PROGNOSIS FOR
ENGINEERING SYSTEMS
GEORGE VACHTSEVANOS
FRANK LEWIS
MICHAEL ROEMER
ANDREW HESS
BIQING WU
JOHN WILEY & SONS, INC.
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Library of Congress Cataloging-in-Publication Data:
Intelligent fault diagnosis and prognosis for engineering systems / George
Vachtsevanos . . . [et al.].
p. cm.
Includes bibliographical references and index.
ISBN-13: 978-0-0471-72999-0 (cloth)
ISBN-10: 0-471-72999-X (cloth)
1. Fault location (Engineering)
2. System analysis.
fault diagnosis and prognosis for engineering systems.
George J.
I. Title: Intelligent
II. Vachtsevanos,
TA169.6.I68 2006
620⬘.0044—dc22
Printed in the United States of America
10 9 8 7 6 5 4 3 2 1
2006005574
To my wife Athena.
G.V.
To Roma, my son.
F.L.L.
To my wife Sharon, son Michael, and daughter Aubrey.
M.J.R.
To my parents, Yanying Chen and Qingliang Wu.
B.W.
CONTENTS
PREFACE
ACKNOWLEDGMENTS
PROLOGUE
1 INTRODUCTION
1.1
1.2
1.3
1.4
1.5
1.6
Historical Perspective / 1
Diagnostic and Prognostic System Requirements / 3
Designing in Fault Diagnostic and Prognostic Systems / 4
Diagnostic and Prognostic Functional Layers / 5
Preface to Book Chapters / 7
References / 12
2 SYSTEMS APPROACH TO CBM/PHM
2.1
2.2
2.3
2.4
2.5
2.6
2.7
2.8
Introduction / 13
Trade Studies / 16
Failure Modes and Effects Criticality Analysis (FMECA) / 18
System CBM Test-Plan Design / 26
Performance Assessment / 28
CBM/PHM Impact on Maintenance and Operations: Case
Studies / 37
CBM/PHM in Control and Contingency Management / 49
References / 54
xi
xiii
xv
1
13
vii
viii
CONTENTS
3 SENSORS AND SENSING STRATEGIES
Introduction / 56
Sensors / 57
Sensor Placement / 77
3.1
3.2
3.3
3.4 Wireless Sensor Networks / 80
3.5
3.6
Smart Sensors / 89
References / 91
4 SIGNAL PROCESSING AND DATABASE MANAGEMENT
SYSTEMS
56
95
4.1
4.2
4.3
4.4
4.5
4.6
Introduction / 95
Signal Processing in CBM/PHM / 96
Signal Preprocessing / 97
Signal Processing / 104
Vibration Monitoring and Data Analysis / 128
Real-Time Image Feature Extraction and Defect/Fault
Classification / 146
The Virtual Sensor / 150
Fusion or Integration Technologies / 152
Usage-Pattern Tracking / 162
4.7
4.8
4.9
4.10 Database Management Methods / 163
4.11 References / 165
5 FAULT DIAGNOSIS
172
Introduction / 172
The Diagnostic Framework / 175
Historical Data Diagnostic Methods / 181
Data-Driven Fault Classification and Decision Making / 191
Dynamic Systems Modeling / 211
Physical Model–Based Methods / 227
5.1
5.2
5.3
5.4
5.5
5.6
5.7 Model-Based Reasoning / 235
5.8
5.9
5.10 A Diagnostic Framework for Electrical/Electronic
Case-Based Reasoning (CBR) / 243
Other Methods for Fault Diagnosis / 258
Systems / 267
5.11 Case Study: Vibration-Based Fault Detection and Diagnosis
for Engine Bearings / 271
5.12 References / 279
6 FAULT PROGNOSIS
CONTENTS
ix
284
Introduction / 284
6.1
6.2 Model-Based Prognosis Techniques / 289
6.3
6.4
6.5
6.6
Probability-Based Prognosis Techniques / 301
Data-Driven Prediction Techniques / 312
Case Studies / 333
References / 351
7 FAULT DIAGNOSIS AND PROGNOSIS PERFORMANCE
METRICS
355
7.1
7.2
7.3
7.4
7.5
7.6
7.7
7.8
Introduction / 355
CBM/PHM Requirements Definition / 356
Feature-Evaluation Metrics / 358
Fault Diagnosis Performance Metrics / 362
Prognosis Performance Metrics / 385
Diagnosis and Prognosis Effectiveness Metrics / 395
Complexity/Cost-Benefit Analysis of CBM/PHM
Systems / 396
References / 398
8 LOGISTICS: SUPPORT OF THE SYSTEM IN OPERATION
400
8.1
8.2
Introduction / 400
Product-Support Architecture, Knowledge Base, and Methods
for CBM / 401
Product Support without CBM / 404
Product Support with CBM / 405
8.3
8.4
8.5 Maintenance Scheduling Strategies / 409
8.6
8.7
A Simple Example / 410
References / 416
APPENDIX
INDEX
417
424