Fault diagnosis and identification of capacitive voltage transformer based on optimized probabilistic neural network

Jianjun Zhang; Biyan Yan; Weidong Liu; Yijia Wu; Han Zhang; Lu Zhang; Tan Zhou; Yu Zeng; Bowei Wei

doi:10.1117/12.2645490

23 November 2022 Fault diagnosis and identification of capacitive voltage transformer based on optimized probabilistic neural network

Jianjun Zhang, Biyan Yan, Weidong Liu, Yijia Wu, Han Zhang, Lu Zhang, Tan Zhou, Yu Zeng, Bowei Wei

Author Affiliations +

Proceedings Volume 12302, Seventh International Conference on Electromechanical Control Technology and Transportation (ICECTT 2022); 123020Y (2022) https://doi.org/10.1117/12.2645490
Event: Seventh International Conference on Electromechanical Control Technology and Transportation (ICECTT 2022), 2022, Guangzhou, China

Abstract

In view of the frequent faults of capacitive voltage transformer in the process of putting into operation, an optimized probabilistic neural network method for fault diagnosis of capacitive voltage transformer is proposed in this paper. Based on the existing state data, the feature extraction parameters are modified to improve its classification accuracy, so as to realize the diagnosis and identification of common faults of capacitive voltage transformer. Compared with the traditional preventive experiment of power failure, it can find the potential equipment defects better. Finally, the simulation analysis shows that this method can be applied to the common fault diagnosis of capacitive voltage transformer.

Citation Download Citation

Jianjun Zhang, Biyan Yan, Weidong Liu, Yijia Wu, Han Zhang, Lu Zhang, Tan Zhou, Yu Zeng, and Bowei Wei "Fault diagnosis and identification of capacitive voltage transformer based on optimized probabilistic neural network", Proc. SPIE 12302, Seventh International Conference on Electromechanical Control Technology and Transportation (ICECTT 2022), 123020Y (23 November 2022); https://doi.org/10.1117/12.2645490

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