Bearing Fault Detection in ASD-Powered Induction Machine Using MODWT and Image Edge Detection
Author:
Affiliation:
1. Digital Systems Group, Electronics Department, Instituto Nacional de Astrofísica Óptica y Electrónica, Puebla, Mexico
2. Computer Department, Instituto Nacional de Astrofísica Óptica y Electrónica, Puebla, Mexico
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09721248.pdf?arnumber=9721248
Reference44 articles.
1. Bearing Fault Diagnosis Based on Subband Time-Frequency Texture Tensor
2. A Novel Fault Diagnosis Method Based on Integrating Empirical Wavelet Transform and Fuzzy Entropy for Motor Bearing
3. MODWT and VMD based intelligent gearbox early stage fault detection approach;saini;J Failure Anal Prevention,2021
4. Novel predictive features using a wrapper model for rolling bearing fault diagnosis based on vibration signal analysis
5. Rolling element bearing fault diagnosis for rotating machinery using vibration spectrum imaging and convolutional neural networks
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3. Bearing fault detection in induction motors using the ROCOF and k-nearest neighbors algorithm;2023 IEEE 14th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED);2023-08-28
4. Instantaneous Square Current Signal Analysis for Motors Using Vision Transformer for the Fault Diagnosis of Rolling Bearings;Applied Sciences;2023-08-17
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