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Electric Machines Modeling, Condition Monitoring and Fault Diagnosis by Hamid A. Toliyat | PDF Free Download.
The development of the electric motor is one of the greatest achievements of the modern energy conversion industry.
Countless electric motors are being used in our daily lives for critical service applications such as transportation, medical treatment, military operation, and communication.
However, due to the fundamental limitations of material lifetime, deterioration, contamination, manufacturing defects, or damages in operations, an electrical motor will eventually go into failure mode.
An unexpected failure might lead to the loss of valuable human life or a costly standstill in industry, which needs to be prevented by precisely detecting or continuously monitoring the working condition of a motor.
This book was written to provide a full review of diagnosis technologies and as an application guide for graduate and senior undergraduate students in the power electronics discipline who want to research, develop, and implement a fault diagnosis and condition monitoring scheme for better safety and improved reliability in electric motor operation.
Furthermore, electrical and mechanical engineers in the industry are also encouraged to use portions of this book as a reference to understand the fundamentals of fault cause and effect and to fulfill successful implementation.
This book approaches the fault diagnosis of electrical motors through the process of theoretical analysis and then practical application.
First, the analysis of the fundamentals of machine failure is presented through the winding functions method, the magnetic equivalent circuit method, and finite element analysis.
Second, the implementation of fault diagnosis is reviewed with techniques such as the motor current signature analysis (MCSA) method, frequency domain method, model-based techniques, and pattern recognition scheme.
In particular, the MCSA implementation method is presented in detail in the last chapters of the book, which discuss robust signal processing techniques and reference-frame-theory-based fault diagnosis implementation for hybrid vehicles as an example.
These theoretical analysis and practical implementation strategies are based on many years of research and development at the Electrical Machines & Power Electronics (EMPE) Laboratory at Texas A&M University.
The population of electric motors has greatly increased in recent years, not only in the United States but also in the world market as shown in Table 1.1 and Table 1.2. The world market is expected to be around $16.1 billion in 2011, which is assumed more than 50% growth just within 5 years .
Electric motors have been applied to almost every place in our daily life, such as manufacturing systems, air transportations, ground transportations, building air-conditioner systems, home energy conversion systems, various cooling systems in electrical devices, and even cell phone vibration systems.
It is also a well-known fact that the electric motors consume more than 50% of whole electrical energy demand in the United States.
The annual electrical energy demand in the United States was 3,873 billion kilowatt-hours in 2008, which is expected to be further increased in every year depending on population and economic growth .
This data indicates that more than 1,900 billion kilowatt-hours is consumed by electric motors annually in the United States, which is the biggest energy consumption by any single electric device in modern society.
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