Prof. Toliyat is currently a Raytheon Company endowed professor of electrical and computer engineering at Texas A&M University. He has received several awards, including the prestigious Cyrill Veinott Award in Electromechanical Energy Conversion from the IEEE Power Engineering Society (2004), the Patent and Innovation Award from Texas A&M University System Office of Technology Commercialization (2007), the TEES Faculty Fellow Award (2006), the Texas A&M Select Young Investigator Award (1999), and the Space Act Award from NASA (1999). He has also received four prize paper awards from the IEEE. Prof. Toliyat has published more than 370 technical papers (including more than 110 in IEEE Transactions) and has 12 issued and pending U.S. patents.

• Introduction. Faults in Induction and Synchronous Motors. Modeling of Electric Machines Using Winding and Modified Winding Function Approaches. Modeling of Electric Machines Using Magnetic Equivalent Circuit Method. Analysis of Faulty Induction Motors Using Finite Element Method. Fault Diagnosis of Electric Machines Using Techniques Based on Frequency Domain. Fault Diagnosis of Electric Machines Using Model-Based Techniques. Application of Pattern Recognition to Fault Diagnosis. Implementation of Motor Current Signature Analysis Fault Diagnosis Based on Digital Signal Processors. Implementation of Fault Diagnosis in Hybrid Vehicles Based on Reference Frame Theory. Robust Signal Processing Techniques for the Implementation of Motor Current Signature Analysis Diagnosis Based on Digital Signal Processors. Index.

Prof. Toliyat is currently a Raytheon Company endowed professor of electrical and computer engineering at Texas A&M University. He has received several awards, including the prestigious Cyrill Veinott Award in Electromechanical Energy Conversion from the IEEE Power Engineering Society (2004), the Patent and Innovation Award from Texas A&M University System Office of Technology Commercialization (2007), the TEES Faculty Fellow Award (2006), the Texas A&M Select Young Investigator Award (1999), and the Space Act Award from NASA (1999). He has also received four prize paper awards from the IEEE. Prof. Toliyat has published more than 370 technical papers (including more than 110 in IEEE Transactions) and has 12 issued and pending U.S. patents.

• Introduction. Faults in Induction and Synchronous Motors. Modeling of Electric Machines Using Winding and Modified Winding Function Approaches. Modeling of Electric Machines Using Magnetic Equivalent Circuit Method. Analysis of Faulty Induction Motors Using Finite Element Method. Fault Diagnosis of Electric Machines Using Techniques Based on Frequency Domain. Fault Diagnosis of Electric Machines Using Model-Based Techniques. Application of Pattern Recognition to Fault Diagnosis. Implementation of Motor Current Signature Analysis Fault Diagnosis Based on Digital Signal Processors. Implementation of Fault Diagnosis in Hybrid Vehicles Based on Reference Frame Theory. Robust Signal Processing Techniques for the Implementation of Motor Current Signature Analysis Diagnosis Based on Digital Signal Processors. Index.

Prof. Toliyat is currently a Raytheon Company endowed professor of electrical and computer engineering at Texas A&M University. He has received several awards, including the prestigious Cyrill Veinott Award in Electromechanical Energy Conversion from the IEEE Power Engineering Society (2004), the Patent and Innovation Award from Texas A&M University System Office of Technology Commercialization (2007), the TEES Faculty Fellow Award (2006), the Texas A&M Select Young Investigator Award (1999), and the Space Act Award from NASA (1999). He has also received four prize paper awards from the IEEE. Prof. Toliyat has published more than 370 technical papers (including more than 110 in IEEE Transactions) and has 12 issued and pending U.S. patents.

• Introduction. Faults in Induction and Synchronous Motors. Modeling of Electric Machines Using Winding and Modified Winding Function Approaches. Modeling of Electric Machines Using Magnetic Equivalent Circuit Method. Analysis of Faulty Induction Motors Using Finite Element Method. Fault Diagnosis of Electric Machines Using Techniques Based on Frequency Domain. Fault Diagnosis of Electric Machines Using Model-Based Techniques. Application of Pattern Recognition to Fault Diagnosis. Implementation of Motor Current Signature Analysis Fault Diagnosis Based on Digital Signal Processors. Implementation of Fault Diagnosis in Hybrid Vehicles Based on Reference Frame Theory. Robust Signal Processing Techniques for the Implementation of Motor Current Signature Analysis Diagnosis Based on Digital Signal Processors. Index.