Condition based maintenance and operation of wind turbines
Lecture Notes in Mechanical Engineering, ISSN: 2195-4364, Vol: 19, Page: 1013-1025
2015
- 8Citations
- 29Usage
- 34Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations8
- Citation Indexes8
- CrossRef2
- Usage29
- Abstract Views29
- Captures34
- Readers34
- 34
Book Chapter Description
With application of advanced sensing technology, the condition based maintenance and operation has been made possible to many industrial systems. In a wind turbine, there are a few hundreds of sensing signals used to monitor the component performance and operational condition. The condition information is utilized in operational control of wind turbines and the wind farm in order to reduce the down time and Cost of Energy (CoE). In this chapter, a framework of condition based maintenance and operation of wind turbines is presented. This framework starts with data collection of sensing signals through SCADA and includes data processing and modeling, failure pattern recognition, remaining useful life/health condition prediction, load prediction (prediction of wind trend), integrated decision making for maintenance and operation of wind turbines and the wind farm, and maintenance planning. The research challenges involved in each step of the framework are discussed. The framework presented in this chapter serves as a guideline which is also useful to other systems.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84950997705&origin=inward; http://dx.doi.org/10.1007/978-3-319-09507-3_87; https://link.springer.com/10.1007/978-3-319-09507-3_87; https://ro.uow.edu.au/eispapers/6054; https://ro.uow.edu.au/cgi/viewcontent.cgi?article=7084&context=eispapers; https://dx.doi.org/10.1007/978-3-319-09507-3_87; https://link.springer.com/chapter/10.1007/978-3-319-09507-3_87
Springer Science and Business Media LLC
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