Fault Diagnosing Of An Induction Motor Based On Signal Fusion Using One-Dimensional Convolutional Neural Network
Author:
Affiliation:
1. Tarbiat Modares University,Control Engineering, M.Sc. Electrical Department,Tehran,Iran
2. Tarbiat Modares University,Assistance Electrical Department,Tehran,Iran
3. IUST,Control Engineering, M.Sc. Electrical Department,Tehran,Iran
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9729328/9729329/09729338.pdf?arnumber=9729338
Reference10 articles.
1. Design and implementation of an automatic condition‐monitoring expert system for ball‐bearing fault detection
2. Bearing Fault Detection and Diagnosis Using Case Western Reserve University Dataset With Deep Learning Approaches: A Review
3. Fault diagnosis of an induction motor using data fusion based on neural networks
4. Bearing fault diagnosis based on vibro-acoustic data fusion and 1D-CNN network
5. Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Phase Selection and Location Method of Generator Stator Winding Ground Fault Based on BP Neural Network;Energies;2023-02-03
2. An Intelligent System for Bearing Fault Diagnosis of Induction Motor using Wavelet Transform Based Deep Learning Framework;2022 IEEE 6th International Conference on Condition Assessment Techniques in Electrical Systems (CATCON);2022-12-17
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