RECOGNITION METHOD OF ROTOR IMBALANCE BASED ON CONVOLUTIONAL NEURAL NETWORK WITH TRAINING INTERFERENCE

Chen Mingyang; Xing Zuoxia; Guo Shanshan; Xu Jian; Liu Yang

doi:10.19912/j.0254-0096.tynxb.2024-0869

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (9) : 162-170. DOI: 10.19912/j.0254-0096.tynxb.2024-0869

RECOGNITION METHOD OF ROTOR IMBALANCE BASED ON CONVOLUTIONAL NEURAL NETWORK WITH TRAINING INTERFERENCE

Chen Mingyang, Xing Zuoxia, Guo Shanshan, Xu Jian, Liu Yang

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Abstract

For identificating rotor imbalance in wind turbine under varying wind directions, a method based on expert system and convolutional neural networks is proposed. Firstly, based on the response of rotor imbalances, an expert system for detection of rotor imbalance is proposed. It includes the identification, isolation and location of the rotor imbalance. Secondly, to address the impact of varying wind conditions on identification accuracy, a identification method based on convolutional neural network with training interference is proposed. The wind condition interference problem is reduced to a domain adaptive problem in the neural network for the identification of rotor imbalance. A variable probability Dropout method and a small Mini-batch are combined for training to simulate the uncertainty of wind. Finally, the cross-validation data set is established to verify and test the proposed method. The average accuracy is more than 98%, which proves the effectiveness of the proposed method.

Key words

wind turbines / convolutional neural networks / expert systems / fault diagnosis / rotor imbalance

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Chen Mingyang, Xing Zuoxia, Guo Shanshan, Xu Jian, Liu Yang. RECOGNITION METHOD OF ROTOR IMBALANCE BASED ON CONVOLUTIONAL NEURAL NETWORK WITH TRAINING INTERFERENCE[J]. Acta Energiae Solaris Sinica. 2025, 46(9): 162-170 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0869

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