Condition Monitoring of Wind Turbine Generator Based on Transfer Learning and One-Class Classifier-Reference-Cited by-同舟云学术

Condition Monitoring of Wind Turbine Generator Based on Transfer Learning and One-Class Classifier

Published:2022-12-15 Issue:24 Volume:22 Page:24130-24139
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Jin Xiaohang¹^ORCID,Pan Hengtuo²^ORCID,Ying Chengzuo²,Kong Ziqian³,Xu Zhengguo³^ORCID,Zhang Bin⁴^ORCID

Affiliation:

1. College of Mechanical Engineering and the Key Laboratory of Special Purpose Equipment and Advanced Manufacturing Technology, Ministry of Education and Zhejiang Province, Zhejiang University of Technology, Hangzhou, China

2. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou, China

3. College of Control Science and Engineering, Zhejiang University, Hangzhou, China

4. Department of Electrical Engineering, University of South Carolina, Columbia, SC, USA

Funder

National Key Research and Development Program of China

Ningbo Natural Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/9984967/09940166.pdf?arnumber=9940166

Reference25 articles.

1. Adversarially Learned One-Class Classifier for Novelty Detection

2. Wind Turbine Blade Breakage Monitoring With Deep Autoencoders

3. Detection and identification of windmill bearing faults using a one-class support vector machine (SVM)

4. A survey of transfer learning

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