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Publications
Guo, J.Y., Wang, Z.Y., Li, H. and Guedes Soares, C. (2024), A transformer-based fault detection framework for offshore wind turbines based on SCADA data, Advances in Maritime Technology and Engineering, Guedes Soares, C. & Santos T.A. (Eds.), Taylor and Francis, London, UK, pp. 547-553.
This paper presents a novel Transformer model for fault detection of offshore wind turbines based on Supervisory Control and Data Acquisition (SCADA) data. Fault detection contributes to safety and effectiveness of the energy production of offshore wind turbines. Initially, the preprocessing of SCADA data is carried out aiming at enhancing the quality and accessibility of data. Subsequently, the Pearson correlation analysis with the assistance of a Transformer model is complete to select pivotal input signals. SCADA data from multiple wind turbines recorded in the LGS-Offshore dataset validated the effectiveness and the superior performance of the proposed methodology. The outcomes of this paper contribute to failure prevention and the maintenance resource management of wind farms.
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