Robust fault diagnosis of rolling bearings via entropy-weighted nuisance attribute projection and neural network under various operating conditions
Autor(en): |
Di Yang
(Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan, China)
Yong Lv (Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan, China) Rui Yuan (Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan, China) Hewenxuan Li (Department of Mechanical, Industrial and Systems Engineering, University of Rhode Island, Kingston, RI, USA) Weihang Zhu (Department of Engineering Technology, University of Houston, Houston, TX, USA) |
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Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Structural Health Monitoring, März 2022, n. 6, v. 21 |
Seite(n): | 147592172210774 |
DOI: | 10.1177/14759217221077414 |
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Datenseite - Reference-ID
10665317 - Veröffentlicht am:
09.05.2022 - Geändert am:
10.12.2022