SVM FAULT DIAGNOSIS OF WIND TURBINE'S GEARBOX BASED ON OPTIMAL FEATURE EXTRACTION ALGORITHM OF VIBRATION SIGNAL

Li Junyi; Yao Yuan; Liu Minghao

doi:10.19912/j.0254-0096.tynxb.2023-0484

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Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (7) : 626-633. DOI: 10.19912/j.0254-0096.tynxb.2023-0484

SVM FAULT DIAGNOSIS OF WIND TURBINE'S GEARBOX BASED ON OPTIMAL FEATURE EXTRACTION ALGORITHM OF VIBRATION SIGNAL

Li Junyi^1,2, Yao Yuan^1,2, Liu Minghao^1,2

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Abstract

Aiming at the feature extraction process of wind turbine's gear box fault diagnosis, a SVM fault diagnosis method based on the optimal feature extraction algorithm of vibration signal is proposed. Firstly, the signal types with high adaptability of the three main feature extraction algorithms are analyzed. Then, according to the signal characteristics of different types of signals, the characteristics of incoming vibration signals are extracted and classified by signal analysis, and the different types of signals are matched with the feature extraction algorithm with high adaptability to achieve the optimal feature extraction of vibration signals. Finally, the matching algorithm and support vector machines model are combined to realize fault diagnosis. Three kinds of gear fault signals collected in practice are tested and verified. The results show that this method can effectively extract the optimal features and match the algorithm, and has a higher fault diagnosis accuracy than the unmatched algorithm.

Key words

wind turbines / gearbox / fault diagnosis / feature extraction / signal classification / algorithm matching / support vector machines

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Li Junyi, Yao Yuan, Liu Minghao. SVM FAULT DIAGNOSIS OF WIND TURBINE'S GEARBOX BASED ON OPTIMAL FEATURE EXTRACTION ALGORITHM OF VIBRATION SIGNAL[J]. Acta Energiae Solaris Sinica. 2024, 45(7): 626-633 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0484

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