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Stator and Bearing Faults Diagnosis of Induction Motor

Om Prakash Yadav

$166.95   $133.74

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English
Eliva Press
05 December 2025
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:  
Imprint:   Eliva Press
Dimensions:   Height: 229mm,  Width: 152mm,  Spine: 11mm
Weight:   286g
ISBN:   9789999329750
ISBN 10:   9999329756
Pages:   210
Publication Date:  
Audience:   General/trade ,  ELT Advanced
Format:   Paperback
Publisher's Status:   Active

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