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.
Description
Contents
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.
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