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Automated on‐line fault prognosis for wind turbine pitch systems using supervisory control and data acquisition

  • Published:2015-07 Issue:5 Volume:9 Page:503-513
  • ISSN:1752-1416
  • Container-title:IET Renewable Power Generation
  • language:en
  • Short-container-title:IET Renewable Power Generation

Author:

Chen Bindi1,Matthews Peter C.1,Tavner Peter J.1

Affiliation:

1. School of Engineering and Computing SciencesDurham UniversityDurhamDH1 3LEUK

Publisher

Institution of Engineering and Technology (IET)

Subject

Renewable Energy, Sustainability and the Environment

Cited by 61 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Condition-based maintenance of wind turbine structures: A state-of-the-art review;Renewable and Sustainable Energy Reviews;2024-10

2. Fault Diagnosis for Takagi-Sugeno Model Wind Turbine Pitch System;IEEE Access;2024

3. Neural Networks for Offshore Wind Turbine Converter Failure Prognosis;IFAC-PapersOnLine;2024

4. Automated Chemical Mixing Plant;2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE);2023-12-04

5. Condition Monitoring of Wind Turbine Pitch System Based on Informer;2023 Global Reliability and Prognostics and Health Management Conference (PHM-Hangzhou);2023-10-12
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