Multi-Sensor Data Fusion for Bearing Fault Diagnosis Using Symmetrized Dot Pattern-Reference-Cited by-同舟云学术

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Multi-Sensor Data Fusion for Bearing Fault Diagnosis Using Symmetrized Dot Pattern

Published:2023-11-05 Issue: Volume: Page:
ISSN:
Container-title:2023 26th International Conference on Electrical Machines and Systems (ICEMS)
language:
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Author:

Zhang Wei¹,Xu Qiwei¹,Hu Yaowen²,Xu Chunlei³,Luo Lingyan¹

Affiliation:

1. Chongqing University,School of Electrical Engineering,Chongqing,China

2. School of General Education Chongqing City Management College,Chongqing,China

3. School of Big Data and information Industry Chongqing City Management College,Chongqing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10343527/10343421/10345155.pdf?arnumber=10345155

Reference14 articles.

1. Vibration–based Condition Monitoring

2. Review of condition monitoring of rotating electrical machines

3. A Motor Current Signal-Based Bearing Fault Diagnosis Using Deep Learning and Information Fusion

4. Bearing Fault Diagnosis of Induction Motors Using a Genetic Algorithm and Machine Learning Classifiers

5. A statistical feature investigation of the spalling propagation assessment for a ball bearing

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