Combining SCADA and vibration data into a single anomaly detection model to predict wind turbine component failure-Reference-Cited by-同舟云学术

Combining SCADA and vibration data into a single anomaly detection model to predict wind turbine component failure

Published:2020-10-04 Issue:3 Volume:24 Page:197-211
ISSN:1095-4244
Container-title:Wind Energy
language:en
Short-container-title:Wind Energy

Author:

Turnbull Alan¹^ORCID,Carroll James¹^ORCID,McDonald Alasdair¹

Affiliation:

1. Electronic and Electrical Engineering University of Strathclyde Glasgow UK

Funder

Engineering and Physical Sciences Research Council

Publisher

Wiley

Subject

Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/we.2567

Reference29 articles.

1. Wind energy: UK experiences and offshore operational challenges

2. ValpyB EnglishP.Future renewable energy costs: offshore wind how technology innovation is anticipated to reduce the cost of energy from european offshore wind farms;2014.

3. Reliability Comparison of Wind Turbines With DFIG and PMG Drive Trains

4. Reliability of wind turbines—experiences of 15 years with 1,500 wts;Hahn B;Wind Energy,2007

Cited by 28 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. Artificial intelligence based abnormal detection system and method for wind power equipment;International Journal of Thermofluids;2024-02

2. A novel hybrid physical AI-based strategy for fault severity estimation in spur gears with zero-shot learning;Mechanical Systems and Signal Processing;2023-12

3. Two-Stage Cascaded High-Precision Early Warning of Wind Turbine Faults Based on Machine Learning and Data Graphization;Journal of Electrical Engineering & Technology;2023-10-20

4. Vibration prediction of offshore wind turbines based on long short-term memory network;Ships and Offshore Structures;2023-09-26

5. A Self-Powered Sensing System with Embedded TinyML for Anomaly Detection;2023 IEEE 3rd International Conference on Industrial Electronics for Sustainable Energy Systems (IESES);2023-07-26