Electric Machines : Modeling, Condition Monitoring, and Fault Diagnosis

Title: Electric Machines : Modeling, Condition Monitoring, and Fault Diagnosis
Author: Hamid A. Toliyat, Homayoun Meshgin-Kelk, Seungdeog Choi, Subhasis Nandi
ISBN: 0849370272 / 9780849370274
Format: Hard Cover
Pages: 272
Publisher: CRC Press
Year: 2013
Availability: Out of Stock
Special Indian Edition.

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In the recent past, digital signal processing techniques, artificial neural networks (ANN), and fuzzy or neuro-fuzzy systems have been used extensively for speed, torque estimation, and solid state drive control of DC and AC machines. Thus the field of fault diagnosis and condition monitoring has become multidisciplinary. This text describes different types of faults in electronic machines, as well as the various techniques employed in their detection. It concentrates mainly on state-of-the-art non-invasive methods that can be utilized for running machines without interfering with or interrupting their processes. The authors also explain how the availability of cheap yet powerful processing powers using digital signal processors makes it possible to seamlessly integrate the task of condition monitoring and fault diagnosis with machine control algorithms.

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Preface

Chapter 1 : Introduction
Chapter 2 : Faults in DC, Induction, Synchronous, and Permanent Magnet Machines
Chapter 3 : Modeling of Electric Machines using Winding Functions Method
Chapter 4 : Modeling of Electric Machines using Magnetic Equivalent Circuit Method
Chapter 5 : Modeling of Electric Machines using Finite Element Method
Chapter 6 : Fault Diagnosis of Electric Machines using Frequency Domain Techniques
Chapter 7 : Fault Diagnosis of Electric Machines using Model-Based Techniques
Chapter 8 : Fault Diagnosis of Electric Machines using Other Techniques
Chapter 9 : Application of Neural Network to Fault Diagnosis
Chapter 10 : Application of Wavelet to Fault Diagnosis
Chapter 11 : Application of Pattern Recognition to Fault Diagnosis

Index