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Issue title: Some highlights on fuzzy systems and data mining
Guest editors: Shilei Sun, Silviu Ionita, Eva Volná, Andrey Gavrilov and Feng Liu
Article type: Research Article
Authors: Fang, Ruiming* | Wu, Mingling | Jiang, Shunhui
Affiliations: Department of Electrical Engineering, Huaqiao University, Xiamen, Fujian, China
Correspondence: [*] Corresponding author. Ruiming Fang, Department of Electrical Engineering, Huaqiao University, Xiamen, Fujian, China. Tel.: +86 5926162374; E-mail: [email protected].
Abstract: To satisfy the requirements of on-line status assessment of wind turbines, a fuzzy comprehensive evaluation method combined with normal cloud model based on SCADA data was proposed. Firstly, a concept was introduced, The Dynamic Inferior, which can take both the variation of assessment indices into the calculation process of inferior degree and the changing of the wind turbine operating condition into consideration. A Markov chain model was adapted to predict the variation of assessment indices. Then, a normal cloud model with the dynamic inferior degree as inputs was adopted to calculate the membership degree of different assessment indices to overcome the subjectivity of normal membership functions. Furthermore, a fuzzy comprehensive assessment method was developed to assess the status of wind turbines online. Finally, the method was tested on the historical SCADA data of wind turbines. The results showed that this method was capable of not only accurately assessing the status of wind turbines online, but could also warn of problems early, which can prevent the occurrence of serious complications.
Keywords: On-line status assessment, wind turbine, normal cloud model, dynamic inferior degree, fuzzy comprehensive evaluation method
DOI: 10.3233/JIFS-169163
Journal: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 6, pp. 2813-2819, 2016
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