Your browser does not support JavaScript!

Signal Processing for Fault Detection and Diagnosis in Electric Machines and Systems

Buy e-book PDF
(plus tax if applicable)
Buy print edition
image of Signal Processing for Fault Detection and Diagnosis in Electric Machines and Systems
Editor: Mohamed Benbouzid 1
View affiliations
Publication Year: 2020

Over the last three decades, the search for competitiveness and growth gains has driven the evolution of machine maintenance policies, and the industry has moved from passive maintenance to active maintenance with the aim of improving productivity. Active maintenance requires continuous monitoring of industrial systems in order to increase reliability, availability rates and guarantee the safety of people and property. This book presents the main advanced signal processing techniques for fault detection and diagnosis in electromechanical systems. It focuses on presenting these advanced tools from time-frequency representation and time-scale analysis to demodulation techniques, including innovative and recently developed options. Each technique is evaluated and compared, and its advantages and drawbacks highlighted. Parametric spectral analysis, which aims to handle some of the main drawbacks of these approaches, is introduced as a potential solution. Signal Processing for Fault Detection and Diagnosis in Electric Machines and Systems offers thorough, analytical coverage of the following topics: parametric signal processing approach; the signal demodulation techniques; Kullback-Leibler divergence for incipient fault diagnosis; high-order spectra (HOS); and fault detection and diagnosis based on principal component analysis. Finally, a brief conclusion suggests some possibilities for the future direction of the field. The book is a useful resource for researchers and engineers whose work involves electrical machines or fault detection specifically, and also of value to postgraduate students with an interest in entering this field.

Inspec keywords: principal component analysis; electric machines; demodulation; fault diagnosis; signal processing

Other keywords: fault detection; higher-order spectra; Kullback-Leibler divergence; signal demodulation techniques; parametric signal processing approach; principal component analysis; electric machines; incipient fault diagnosis

Subjects: General and management topics; Other topics in statistics; General electrical engineering topics; a.c. machines; Signal processing and detection; Digital signal processing; d.c. machines; Other topics in statistics

Related content

This is a required field
Please enter a valid email address