Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives
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Product details
- ISBN 9781119722755
- Weight: 454g
- Dimensions: 10 x 10mm
- Publication Date: 29 Oct 2021
- Publisher: John Wiley & Sons Inc
- Publication City/Country: US
- Product Form: Hardback
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An insightful treatment of present and emerging technologies in fault diagnosis and failure prognosis
In Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives, a team of distinguished researchers delivers a comprehensive exploration of current and emerging approaches to fault diagnosis and failure prognosis of electrical machines and drives. The authors begin with foundational background, describing the physics of failure, the motor and drive designs and components that affect failure and signals, signal processing, and analysis.
The book then moves on to describe the features of these signals and the methods commonly used to extract these features to diagnose the health of a motor or drive, as well as the methods used to identify the state of health and differentiate between possible faults or their severity.
Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives discusses the tools used to recognize trends towards failure and the estimation of remaining useful life. It addresses the relationships between fault diagnosis, failure prognosis, and fault mitigation.
The book also provides:
- A thorough introduction to the modes of failure, how early failure precursors manifest themselves in signals, and how features extracted from these signals are processed
- A comprehensive exploration of the fault diagnosis, the results of characterization, and how they used to predict the time of failure and the confidence interval associated with it
- A focus on medium-sized drives, including induction, permanent magnet AC, reluctance, and new machine and drive types
Perfect for researchers and students who wish to study or practice in the rea of electrical machines and drives, Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives is also an indispensable resource for researchers with a background in signal processing or statistics.
Elias G. Strangas, PhD, is a Professor at Michigan State University, where he heads the Electrical Machines and Drives Laboratory.
Guy Clerc is a Professor at the Université de Lyon, Ampère, in Villeurbanne, France.
Hubert Razik is a Professor at the Université de Lyon, Ampère, in Villeurbanne, France.
Abdenour Soualhi is an Assistant Professor at the LASPI Laboratory in Jean Monnet University Roanne.
