Reprint
Early Detection of Faults in Induction Motors
Edited by
November 2023
200 pages
- ISBN978-3-0365-9335-7 (Hardback)
- ISBN978-3-0365-9334-0 (PDF)
This book is a reprint of the Special Issue Early Detection of Faults in Induction Motors that was published in
Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary
In modern industries, induction motors are the backbone of numerous applications, powering everything from manufacturing facilities to transportation systems. While they are known for their reliability, unexpected failures can still occur, leading to increased operational costs, facility damage, or service interruptions. "Early Detection and Fault Diagnosis of Induction Motors" is a comprehensive volume that compiles ten innovative journal articles focused on maintaining these machines. The papers explore a variety of techniques that introduce new ideas to the field.
Format
- Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
fault detection; fault diagnosis; frequency analysis; induction motors; rotating machines; signal processing; spectral analysis; time-frequency decompositions; bearing diagnosis; early damage detection; unlabeled learning; deep learning; dynamic information fusion; fault diagnosis; fault detection; induction motor; electric machine; machine learning; supervised learning; data-driven; power connection failures; condition monitoring; induction machines; negative sequence currents; shorted turn faults; phasor compensation; Prony method; broken rotor bar; fast Fourier transform; current signal analysis; artificial intelligence; condition monitoring; early detection; fault diagnosis; fault severity; frequency analysis; incipient fault; induction motor; machine learning; signal processing; induction motors; fault-tolerant control; AC machines; back EMF; feedforward compensation; induction motors; fault detection; machine learning; supervised learning; multiple coupled circuit model; parameter identification; fault detection; fault classification; induction motors; measurement techniques; physical variables; signal analysis; ITSC fault; traction motor; fault diagnosis; apFFT; SVM