State degradation evaluation and early fault identification of wind turbine bearings-Reference-Cited by-同舟云学术

State degradation evaluation and early fault identification of wind turbine bearings

Published:2022-03 Issue: Volume:311 Page:122348
ISSN:0016-2361
Container-title:Fuel
language:en
Short-container-title:Fuel

Author:

Wan Xiaojing,Sun Wenlei,Chen Kun,Zhang Xiaodong

Publisher

Elsevier BV

Subject

Organic Chemistry,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering

Reference23 articles.

1. Opportunities and challenges of machinery intelligent fault diagnosis in big data era;Yaguo;J Mech Eng,2018

2. Chen Xuefeng, Guo Yanjie, Xu Caibin, et al Review of Fault Diagnosis and Health Monitoring for Wind Power Equipment China Mechanical Engineering. http://kns.cnki.net/kcms/detail/42.1294.TH.20200122.1124.010.html.

3. Basic research on machinery fault diagnostics: past, present, and future trends;Chen;Front Mech Eng,2018

4. Rolling elements bearings degradation indicator based on continuous hidden markov model;Zhang;J Fail Anal Prev,2015

5. A deep feature optimization fusion method for extracting bearing degradation features;Zhao;IEEE Access,2018

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