Majid Hussain1,2,*, Tayab Din Memon3,4, Imtiaz Hussain5, Zubair Ahmed Memon3, Dileep Kumar2
CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 435-470, 2022, DOI:10.32604/cmes.2022.020583
Abstract Owing to the 4.0 industrial revolution condition monitoring maintenance is widely accepted as a useful approach to
avoiding plant disturbances and shutdown. Recently, Motor Current Signature Analysis (MCSA) is widely reported
as a condition monitoring technique in the detection and identification of individual and multiple Induction Motor
(IM) faults. However, checking the fault detection and classification with deep learning models and its comparison
among themselves or conventional approaches is rarely reported in the literature. Therefore, in this work, we present
the detection and identification of induction motor faults with MCSA and three Deep Learning (DL) models namely
MLP, LSTM, and… More >
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