This research presents an intelligent and automated diagnostic framework for early detection of stator and bearing faults in three-phase induction motors (IMs), which are vital components in industrial, commercial, and residential systems. Combining experimental data with advanced AI techniques like fuzzy logic, neural networks, and support vector machines, the study develops high-accuracy models for stator fault classification. For bearing fault diagnosis, a multi-stage methodology is introduced using statistical time-domain features, KPCA-SVM classifiers, and a novel Adaptive Modified Morlet Wavelet (AMMW) transform. The proposed techniques demonstrate excellent performance even in noisy conditions, offering a highly reliable solution for real-time IM fault monitoring and predictive maintenance.
By:
Om Prakash Yadav Imprint: Eliva Press Dimensions:
Height: 229mm,
Width: 152mm,
Spine: 11mm
Weight: 286g ISBN:9789999329750 ISBN 10: 9999329756 Pages: 210 Publication Date:05 December 2025 Audience:
General/trade
,
ELT Advanced
Format:Paperback Publisher's Status: Active