Electrical Machines Diagnosis

Electrical Machines Diagnosis By Jean?Claude Trigeassou(auth.)
2011 | 344 Pages | ISBN: 1848212631 | PDF | 16 MB
Monitoring and diagnosis of electrical machine faults is a scientific and economic issue which is motivated by objectives for reliability and serviceability in electrical drives. This book provides a survey of the techniques used to detect the faults occurring in electrical drives: electrical, thermal and mechanical faults of the electrical machine, faults of the static converter and faults of the energy storage unit. Diagnosis of faults occurring in electrical drives is an essential part of a global monitoring system used to improve reliability and serviceability. This diagnosis is performed with a large variety of techniques: parameter estimation, state observation, Kalman filtering, spectral analysis, neural networks, fuzzy logic, artificial intelligence, etc. Particular emphasis in this book is put on the modeling of the electrical machine in faulty situations. Electrical Machines Diagnosis presents original results obtained mainly by French researchers in different domains. It will be useful as a guideline for the conception of more robust electrical machines and indeed for engineers who have to monitor and maintain electrical drives. As the monitoring and diagnosis of electrical machines is still an open domain, this book will also be very useful to researchers.Content: Chapter 1 Faults in Electrical Machines and their Diagnosis (pages 1-22): Chapter 2 Modeling Induction Machine Winding Faults for Diagnosis (pages 23-68): Chapter 3 Closed?Loop Diagnosis of the Induction Machine (page 0): Chapter 4 Induction Machine Diagnosis Using Observers (pages 93-129): Chapter 5 Thermal Monitoring of the Induction Machine (pages 131-166): Chapter 6 Diagnosis of the Internal Resistance of an Automotive Lead?acid Battery by the Implementation of a model Invalidation?based Approach (pages 167-192): Chapter 7 Electrical and Mechanical Faults Diagnosis of Induction Machines Using Signal Analysis (pages 193-225): Chapter 8 Fault Diagnosis of the Induction Machine by Neural Networks (pages 227-270): Chapter 9 Faults Detection and Diagnosis in a Static Converter (pages 271-319):