A Convolutional Neural Network Model-Based Approach for Multi-Fault Diagnosis of Asynchronous Motors-Reference-Cited by-同舟云学术

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A Convolutional Neural Network Model-Based Approach for Multi-Fault Diagnosis of Asynchronous Motors

Published:2023-07-07 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)
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Author:

Shi Jun¹,Li Jiangnan¹,Wang Tao²

Affiliation:

1. Shenzhen Power Supply Bureau Co., Ltd,Shenzhen,China

2. Electric Power Research Institute,CSG,Guangzhou,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10294329/10294332/10294534.pdf?arnumber=10294534

Reference23 articles.

1. Diagnosis of Bearing Fault in Induction Motors Using Hilbert Demodulation Approach[J];SONG;Transactions of China Electrotechnical Society,2018

2. Diagnosis method of rolling bearing outer raceway fault in induction motors[J];XU;Electric Machines and Control.,2022

3. Broken Rotor Bar Fault Diagnosis Based on Random Forests in Induction Motors[J];SHI;Small & Special Electrical Machines,2017

4. A Review of Fault Diagnosis and Online Condition Monitoring of Stator Insulation in AC Electrical Machine[J];ZHENG,2019

Cited by 1 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. Fault Diagnosis Expert System for Medium Voltage Three-Phase Asynchronous Motors Based on Fuzzy Neural Nets;Lecture Notes in Electrical Engineering;2024

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