Experts has a new look! Let us know what you think of the updates.

Provide feedback
Home
Scholarly Works
Fault Diagnosis of Electric Motors by a...
Journal article

Fault Diagnosis of Electric Motors by a Channel-Wise Regulated CNN and Differential of STFT

Abstract

In various applications, the reliable and efficient detection of faults in electric machines is crucial, particularly in environments with high noise levels. To this end, the current study introduces an effective fault detection model utilizing the differential of Short-Time Fourier Transform (STFT) and a channel-wise regulated Convolutional Neural Network (CNN). The novel use of the differential of STFT is presented to enhance the diagnostic …

Authors

Mohammad-Alikhani A; Jamshidpour E; Dhale S; Akrami M; Pardhan S; Nahid-Mobarakeh B

Journal

IEEE Transactions on Industry Applications, Vol. 61, No. 2, pp. 3066–3077

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

DOI

10.1109/tia.2025.3532556

ISSN

0093-9994

Labels

Sustainable Development Goals (SDG)