FAULT DIAGNOSIS METHOD FOR WIND POWER TRANSMISSION SYSTEM BASED ON PENETRABLE VISIBILITY GRAPH AND GRAPH ISOMORPHISM NETWORKS

Zhou Zhongzhi; Deng Aidong; Liu Dongying; Liu Yang; Hu Qinyi; Rao Lang

doi:10.19912/j.0254-0096.tynxb.2023-1670

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (2) : 591-599. DOI: 10.19912/j.0254-0096.tynxb.2023-1670

FAULT DIAGNOSIS METHOD FOR WIND POWER TRANSMISSION SYSTEM BASED ON PENETRABLE VISIBILITY GRAPH AND GRAPH ISOMORPHISM NETWORKS

Zhou Zhongzhi^1,2, Deng Aidong^1,2, Liu Dongying³, Liu Yang^1,2, Hu Qinyi^1,2, Rao Lang^1,2

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Abstract

To address the difficulty in fault diagnosis of wind turbine transmission systems with limited samples, a novel fault diagnosis approach for rotating machinery is proposed, which leverages the Penetrable Visibility Graph and Graph Isomorphism Network. Initially, the time series signal data is transformed into graph-structured data using the penetrable visibility graph algorithm with limited depth, and the resulting connecting edges are then weighted. Subsequently, the weighted graph data is fed into a network model for training. Specifically, the model integrates a self-attention mechanism to enable adaptive modeling, thereby improving its generalization ability. Finally, a Softmax classifier is employed for fault pattern recognition. Experimental results demonstrate the effectiveness of the proposed method in achieving robust fault diagnosis performance, especially in scenarios with an extremely limited number of samples.

Key words

wind turbines / fault diagnosis / small sample / graph isomorphism network / penetrable visibility graph

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Zhou Zhongzhi, Deng Aidong, Liu Dongying, Liu Yang, Hu Qinyi, Rao Lang. FAULT DIAGNOSIS METHOD FOR WIND POWER TRANSMISSION SYSTEM BASED ON PENETRABLE VISIBILITY GRAPH AND GRAPH ISOMORPHISM NETWORKS[J]. Acta Energiae Solaris Sinica. 2025, 46(2): 591-599 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1670

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