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Publications
Li, H., Ding, Y. and Guedes Soares, C. (2024), An Intelligent Failure Data Analysis Framework for Failure Data Management of Wind Turbines, 43rd International Conference on Ocean, Offshore and Arctic Engineering (OMAE2024), 9-14 June, Singapore, Singapore, Paper No: OMAE2024- 125288, V007T09A028.
This paper proposes an intelligent failure data analysis framework to identify failure features of wind turbines intelligently and automatically, which requires fewer interactions of analysts. Initially, two operation and maintenance datasets in terms of failure and maintenance of onshore (LGS-Onshore) and offshore (LGS-Offshore) wind turbines are introduced. Subsequently, an intelligent failure data analysis model is developed based on Bidirectional Encoder Representations from Transformers and the Conditional Random Field model with the assistance of the proposed adaptive resampling mechanism. The advantage of the proposed framework is validated by the better performance in extracting failure features of wind turbines according to LGS-Onshore and LGS-Offshore datasets. Overall, this paper proposes a new concept of failure data analysis and contributes to the operation and maintenance of onshore and offshore wind turbines.
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