Multi Sensor based Bearing Fault Diagnosis of Switched Reluctance Motor for Electric Vehicle-Reference-Cited by-同舟云学术

Multi Sensor based Bearing Fault Diagnosis of Switched Reluctance Motor for Electric Vehicle

Published:2023-03-24 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2023 6th International Conference on Electronics, Communications and Control Engineering
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Author:

Choudhary Anurag¹^ORCID,Mian Tauheed²^ORCID,Fatima Shahab²^ORCID,Panigrahi Bijaya Ketan³^ORCID

Affiliation:

1. School of Interdisciplinary Research (SIRe), Indian Institute of Technology Delhi, India

2. Centre for Automotive Research and Tribology, Indian Institute of Technology Delhi, India

3. Department of Electrical Engineering, Indian Institute of Technology Delhi, India and Centre for Automotive Research and Tribology, Indian Institute of Technology Delhi, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3592307.3592348

Reference22 articles.

1. State of the Art Technologies in Fault Diagnosis of Electric Vehicles: A Component-Based Review

2. A. Sharma , P. Verma , A. Choudhary , L. Mathew and S. Chatterji , “ Application of Wavelet Analysis in Condition Monitoring of Induction Motors ” in Advances in Electromechanical Technologies , Singapore : Springer , pp. 795 - 807 . A. Sharma, P. Verma, A. Choudhary, L. Mathew and S. Chatterji, “Application of Wavelet Analysis in Condition Monitoring of Induction Motors” in Advances in Electromechanical Technologies, Singapore: Springer, pp. 795-807.

3. An intelligent self-adaptive bearing fault diagnosis approach based on improved local mean decomposition

4. Bearing Fault Diagnosis of Switched Reluctance Motor in Electric Vehicle Powertrain via Multisensor Data Fusion

5. Support vector machines based non-contact fault diagnosis system for bearings

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