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Knowledge graph construction and fault identification for new energy power equipment

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  • Erhui Zhang

Abstract

To optimize the accuracy of fault identification and cross-domain adaptability for new energy power equipment, we proposed a fault recognition method based on knowledge graphs. First, a knowledge graph for power equipment is constructed, integrating multisource fault information. Then, a reasoning rule mining approach is introduced to enhance the model’s fault recognition precision. Additionally, an adaptive knowledge graph transfer method is implemented to improve the model’s performance in cross-domain applications. Experimental results demonstrate that, compared to similar approaches, the proposed method excels in both knowledge graph construction and fault recognition capabilities, thereby validating the reliability and effectiveness of the proposed approach.

Suggested Citation

  • Erhui Zhang, 2025. "Knowledge graph construction and fault identification for new energy power equipment," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 20, pages 2143-2156.
    • Handle: RePEc:oup:ijlctc:v:20:y:2025:i::p:2143-2156.
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    File URL: http://hdl.handle.net/10.1093/ijlct/ctaf143
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