Electrical Machines Diagnosis

344 Pages·2011·15.976 MB·English

by  Jean?Claude Trigeassou(auth.)

Electrical Machines Diagnosis
Electrical Machines
Diagnosis

Edited by
Jean-Claude Trigeassou
First published 2011 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.
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____________________________________________________________________________________
Library of Congress Cataloging-in-Publication Data

Electrical machines diagnosis / edited by Jean-Claude Trigeassou.
p. cm.
Includes bibliographical references and index.
ISBN 978-1-84821-263-3
1. Electric apparatus and appliances--Maintenance and repair. 2. Electric machinery--Maintenance and
repair. 3. Electric fault location. I. Trigeassou, Jean-Claude.
TK452.E4155 2011
621.31'0420288--dc23
2011022945

British Library Cataloguing-in-Publication Data
A CIP record for this book is available from the British Library
ISBN 978-1-84821-263-3

Printed and bound in Great Britain by CPI Antony Rowe, Chippenham and Eastbourne.
Table of Contents
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
Chapter 1. Faults in Electrical Machines and their Diagnosis. . . . . . . . . 1
Sadok BAZINE and Jean-Claude TRIGEASSOU
1.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2. Composition of induction machines . . . . . . . . . . . . . . . . . . . . . 3
1.2.1. The stator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2.2. The rotor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2.3. Bearings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.3. Failures in induction machines . . . . . . . . . . . . . . . . . . . . . . . . 5
1.3.1. Mechanical failures . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.3.2. Electrical failures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.4. Overview of methods for diagnosing induction machines . . . . . . . . 10
1.4.1. Diagnosis methods using an analytical model . . . . . . . . . . . . . 12
1.4.2. Diagnostic methods with no analytical model . . . . . . . . . . . . . 16
1.5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
1.6. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Chapter 2. Modeling Induction Machine Winding
Faults for Diagnosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Emmanuel SCHAEFFER and Smail BACHIR
2.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.1.1. Simulation model versus diagnosis model . . . . . . . . . . . . . . . 23
2.1.2. Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.1.3. Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.1.4. Chapter structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.2. Study framework and general methodology . . . . . . . . . . . . . . . . 26
2.2.1. Working hypotheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
vi Electrical Machines Diagnosis
2.2.2. Equivalence between winding systems . . . . . . . . . . . . . . . . . 27
2.2.3. Equivalent two-phase machine with no fault . . . . . . . . . . . . . 34
2.2.4. Consideration of a stator winding fault . . . . . . . . . . . . . . . . . 37
2.3. Model of the machine with a stator insulation fault . . . . . . . . . . . . 40
2.3.1. Electrical equations of the machine with
a stator short-circuit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
2.3.2. State model in any reference frame . . . . . . . . . . . . . . . . . . . 43
2.3.3. Extension of the three-phase stator model . . . . . . . . . . . . . . . 47
2.3.4. Model validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
2.4. Generalization of the approach to the coupled modeling
of stator and rotor faults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
2.4.1. Electrical equations in the presence of rotor imbalance . . . . . . . 53
2.4.2. Generalized model of the machine with stator
and rotor faults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
2.5. Methodology for monitoring the induction machine . . . . . . . . . . . 57
2.5.1. Parameter estimation for induction machine diagnosis . . . . . . . 58
2.5.2. Experimental validation of the monitoring strategy . . . . . . . . . 61
2.6. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
2.7. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
Chapter 3. Closed-Loop Diagnosis of the Induction Machine . . . . . . . . 69
Imène BEN AMEUR BAZINE, Jean-Claude TRIGEASSOU,
Khaled JELASSI and Thierry POINOT
3.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
3.2. Closed-loop identification . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
3.2.1. Problems in closed-loop identification . . . . . . . . . . . . . . . . . 71
3.2.2. Identification problems for diagnosing electrical machines . . . . . 73
3.3. General methodology of closed-loop identification
of induction machine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
3.3.1. Taking control into account . . . . . . . . . . . . . . . . . . . . . . . 74
3.3.2. Machine identification by closed-loop decomposition . . . . . . . . 76
3.3.3. Identification results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
3.4. Closed-loop diagnosis of simultaneous stator/rotor faults . . . . . . . . 82
3.4.1. General model of induction machine faults . . . . . . . . . . . . . . 82
3.4.2. Parameter estimation with a priori information . . . . . . . . . . . . 83
3.4.3. Detection and localization. . . . . . . . . . . . . . . . . . . . . . . . . 84
3.4.4. Comparison of identification results through direct
and indirect approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
3.5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
3.6. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
Table of Contents vii
Chapter 4. Induction Machine Diagnosis Using Observers . . . . . . . . . . 93
Guy CLERC and Jean-Claude MARQUES
4.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
4.2. Model presentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
4.2.1. Three-phase model of induction machine without fault . . . . . . . 96
4.2.2. Park’s model of an induction machine without fault . . . . . . . . . 100
4.2.3. Induction machine models with fault . . . . . . . . . . . . . . . . . . 104
4.3. Observers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
4.3.1. Principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
4.3.2. Different kinds of observers. . . . . . . . . . . . . . . . . . . . . . . . 108
4.3.3. Extended observer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
4.4. Applying observers to diagnostics . . . . . . . . . . . . . . . . . . . . . . 119
4.4.1. Using Park’s model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
4.4.2. Use of the three-phase model. . . . . . . . . . . . . . . . . . . . . . . 124
4.4.3. Spectral analysis of the torque reconstructed
by the observer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
4.5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
4.6. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
Chapter 5. Thermal Monitoring of the Induction Machine . . . . . . . . . 131
Luc LORON and Emmanuel FOULON
5.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
5.1.1. Aims of the thermal monitoring on induction machines . . . . . . . 131
5.1.2. Main methods of thermal monitoring
of the induction machines . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
5.2. Real-time parametric estimation by Kalman filter. . . . . . . . . . . . . 137
5.2.1. Interest and specificities of the Kalman filter . . . . . . . . . . . . . 137
5.2.2. Implementation of an extended Kalman filter . . . . . . . . . . . . . 138
5.3. Electrical models for the thermal monitoring. . . . . . . . . . . . . . . . 142
5.3.1. Continuous time models . . . . . . . . . . . . . . . . . . . . . . . . . 143
5.3.2. Full-order model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
5.3.3. Discretized and extended model . . . . . . . . . . . . . . . . . . . . . 147
5.4. Experimental system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
5.4.1. General presentation of the test bench. . . . . . . . . . . . . . . . . . 149
5.4.2. Thermal instrumentation. . . . . . . . . . . . . . . . . . . . . . . . . . 151
5.4.3. Electrical instrumentation . . . . . . . . . . . . . . . . . . . . . . . . 153
5.5. Experimental results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
5.5.1. Tuning of the Kalman filter . . . . . . . . . . . . . . . . . . . . . . . 157
5.5.2. Influence of the magnetic saturation . . . . . . . . . . . . . . . . . . 160
5.6. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
5.7. Appendix: induction machine characteristics. . . . . . . . . . . . . . . . 163
5.8. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
viii Electrical Machines Diagnosis
Chapter 6. Diagnosis of the Internal Resistance of an Automotive
Lead-acid Battery by the Implementation of a Model
Invalidation-based Approach: Application to Crankability
Estimation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
Jocelyn SABATIER, Mikaël CUGNET, Stéphane LARUELLE,
Sylvie GRUGEON, Isabelle CHANTEUR, Bernard SAHUT,
Alain OUSTALOUP and Jean-Marie TARASCON
6.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
6.2. Fractional model of a lead-acid battery for the start-up phase . . . . . . 169
6.3. Identification of the fractional model. . . . . . . . . . . . . . . . . . . . . 171
6.3.1. Output error identification algorithm . . . . . . . . . . . . . . . . . . 171
6.3.2. Calculation of the output sensitivities. . . . . . . . . . . . . . . . . . 173
6.3.3. Validation of the estimated parameters . . . . . . . . . . . . . . . . . 174
6.3.4. Application to start-up signals . . . . . . . . . . . . . . . . . . . . . . 174
6.4. Battery resistance as crankability estimator. . . . . . . . . . . . . . . . . 175
6.5. Model validation and estimation of the battery resistance . . . . . . . . 178
6.5.1. Frequency approach of the model validation . . . . . . . . . . . . . 178
6.5.2. Application to the estimation of the battery resistance. . . . . . . . 181
6.5.3. Simplified resistance estimator. . . . . . . . . . . . . . . . . . . . . . 184
6.6. Toward a battery state estimator . . . . . . . . . . . . . . . . . . . . . . . 188
6.7. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
6.8. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190
Chapter 7. Electrical and Mechanical Faults Diagnosis
of Induction Machines using Signal Analysis . . . . . . . . . . . . . . . . . . . 193
Hubert RAZIK and Mohamed EL KAMEL OUMAAMAR
7.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193
7.2. The spectrum of the current line . . . . . . . . . . . . . . . . . . . . . . . 194
7.3. Signal processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196
7.3.1. Fourier’s transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196
7.3.2. Periodogram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
7.4. Signal analysis from experiment campaigns . . . . . . . . . . . . . . . . 199
7.4.1. Disturbances induced by a broken bar . . . . . . . . . . . . . . . . . 199
7.4.2. Bearing faults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
7.4.3. Static eccentricity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211
7.4.4. Inter turn short circuits . . . . . . . . . . . . . . . . . . . . . . . . . . 220
7.5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222
7.6. Appendices. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223
7.6.1. Appendix A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223
7.6.2. Appendix B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223
7.7. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224
Table of Contents ix
Chapter 8. Fault Diagnosis of the Induction
Machine by Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
Monia Ben Khader BOUZID, Najiba MRABET BELLAAJ,
Khaled JELASSI, Gérard CHAMPENOIS and Sandrine MOREAU
8.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
8.2. Methodology of the use of the ANN
in the diagnostic domain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228
8.2.1. Choice of the fault indicators . . . . . . . . . . . . . . . . . . . . . . 229
8.2.2. Choice of the structure of the network . . . . . . . . . . . . . . . . . 230
8.2.3. Construction of the learning and test base . . . . . . . . . . . . . . . 231
8.2.4. Learning and test of the network. . . . . . . . . . . . . . . . . . . . . 232
8.3. Description of the monitoring system . . . . . . . . . . . . . . . . . . . . 232
8.4. The detection problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233
8.5. The proposed method for the robust detection . . . . . . . . . . . . . . . 235
8.5.1. Generation of the estimated residues . . . . . . . . . . . . . . . . . . 236
8.6. Signature of the stator and rotor faults. . . . . . . . . . . . . . . . . . . . 237
8.6.1. Analysis of the residue in healthy regime. . . . . . . . . . . . . . . . 237
8.6.2. Analysis of the residue in presence of the stator fault . . . . . . . . 237
8.6.3. Analysis of the residue in presence of the rotor fault . . . . . . . . . 241
8.6.4. Analysis of the residue in presence of simultaneous
stator/rotor fault . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244
8.7. Detection of the faults by the RN neural network . . . . . . . . . . . . 244
d
8.7.1. Extraction of the fault indicators . . . . . . . . . . . . . . . . . . . . 244
8.7.2. Learning sequence of the RN network. . . . . . . . . . . . . . . . . 245
d
8.7.3. Structure of the RN network . . . . . . . . . . . . . . . . . . . . . . 246
d
8.7.4. Results of the learning of the RN network . . . . . . . . . . . . . . 247
d
8.7.5. Test results of the RN network . . . . . . . . . . . . . . . . . . . . . 248
d
8.8. Diagnosis of the stator fault . . . . . . . . . . . . . . . . . . . . . . . . . . 251
8.8.1. Choice of the fault indicators for the RN network . . . . . . . . . 251
cc
8.8.2. Learning sequence of the RN network . . . . . . . . . . . . . . . . 253
cc
8.8.3. Structure of the RN network . . . . . . . . . . . . . . . . . . . . . . 254
cc
8.8.4. Learning results of the RN network . . . . . . . . . . . . . . . . . . 255
cc
8.8.5. Results of the test of the RN network . . . . . . . . . . . . . . . . . 256
cc
8.8.6. Experimental validation of the RN network . . . . . . . . . . . . . 259
cc
8.9. Diagnosis of the rotor fault. . . . . . . . . . . . . . . . . . . . . . . . . . . 263
8.9.1. Choice of the fault indicators of the RN network . . . . . . . . . . 265
bc
8.9.2. Learning sequence of the RN network . . . . . . . . . . . . . . . . 265
bc
8.9.3. Learning, test and validation results . . . . . . . . . . . . . . . . . . 266
8.10. Complete monitoring system of the induction machine . . . . . . . . . 267
8.11. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268
8.12. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269
x Electrical Machines Diagnosis
Chapter 9. Faults Detection and Diagnosis
in a Static Converter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271
Mohamed BENBOUZID, Claude DELPHA,
Zoubir KHATIR, Stéphane LEFEBVRE and Demba DIALLO
9.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271
9.2. Detection and diagnosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273
9.2.1. Neural network approach . . . . . . . . . . . . . . . . . . . . . . . . . 273
9.2.2. A fuzzy logic approach . . . . . . . . . . . . . . . . . . . . . . . . . . 280
9.2.3. Multi-dimensional data analysis . . . . . . . . . . . . . . . . . . . . . 285
9.3. Thermal fatigue of power electronic moduli and failure modes . . . . . 294
9.3.1. Presentation of power electronic moduli in diagnosis . . . . . . . . 294
9.3.2. Causes and main types of degradation of power
electronics moduli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304
9.3.3. Interconnection degradation effects on electrical
characteristics and potential use for diagnosis. . . . . . . . . . . . . . . . . 310
9.3.4. Effects of interface degradation on thermal characteristics
and potential use for diagnosis . . . . . . . . . . . . . . . . . . . . . . . . . 313
9.4. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 316
9.5. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 316
List of Authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327
Preface
Monitoring and diagnosing faults in electrical machines is a scientific and
economic issue which is motivated by objectives for reliability and serviceability in
electrical drives. This concern for continuity of serviceability has been motivating
electrotechnical engineers since the first industrial applications of electrical
machines. To avoid failures, these engineers used experiment feedback to improve
machine construction and to make the said machines more robust. Moreover, they
gathered knowledge from the detected faults and developed techniques for “manual
diagnosis”, following examples seen in mechanics and, above all, car maintenance.
The generalization of power supplies through power electronics from the 1950s
to 1960s and onward, and the decisive contribution of microcomputers at the end of
the 1970s radically changed the approach to machine maintenance through the
introduction of “automated” diagnosis techniques. The development of digital
control and an increased power in computer systems have opened up a channel for
new techniques of automatic control, integrating new functionalities, such as real-
time identification and online adaptation of control algorithms. The supervision
function has become a natural and necessary addition to the management of
automated systems which are becoming increasingly more sophisticated and
complex. Furthermore, the concept of integrating automated fault detection and
diagnosis came about at the beginning of the 1980s, as a functionality of supervision
systems.
This revolution in machine control has also, unfortunately, resulted in new
causes for machine failures. Now, to the classic electrical, mechanical, and thermal
faults, we can add failures in power electronics and information systems, as well as
new faults caused by Pulse Width Modulation power supplies. Moreover, these
failures may have instant destructive consequences which justify early diagnosis,
whether this is followed by a somewhat instantaneous switch-off or reconfiguration
of the machine’s power supply.