Fault diagnosis method of substation equipment based on BP neural network

Guangrui Shan; Yujin Zhang; Yabin Zhang; Ning Wu; Ting Xu

doi:10.1117/12.2673078

25 April 2023 Fault diagnosis method of substation equipment based on BP neural network

Guangrui Shan, Yujin Zhang, Yabin Zhang, Ning Wu, Ting Xu

Proceedings Volume 12598, Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022); 125982Y (2023) https://doi.org/10.1117/12.2673078
Event: Eighth International Conference on Energy Materials and Electrical Engineering (ICMEE 2022), 2022, Guangzhou, China

Abstract

Power transformer undertakes the important tasks of voltage transformation, power distribution, and power transfer in the power system, so the normal operation of the transformer is an important guarantee for the safe operation of the power system. The substation is one of the most important equipment in the distribution station and the national power system, so it is necessary to diagnose and analyze its operation status and fault maintenance. In recent years, substation equipment faults have occurred frequently, which has become the main problem to be solved in the current power industry. The existing methods have a high misdiagnosis rate in the application of substation equipment fault diagnosis, so this paper proposes research on substation equipment fault diagnosis method based on BP neural network. In this paper, the current sensor and temperature sensor are used to obtain the current signal and temperature signal of the substation equipment, and the obtained signals are processed by redundancy removal. The BP neural network is used to extract and analyze the fault characteristics of the equipment, diagnose the operation state of the equipment, and realize the fault diagnosis of the substation equipment. Proved by experiments, the misdiagnosis rate of the method designed in this paper is lower than that of the traditional method, and it has a good application prospect in the substation equipment fault diagnosis and provides theoretical support for the stable operation of substation.

Citation Download Citation

Guangrui Shan, Yujin Zhang, Yabin Zhang, Ning Wu, and Ting Xu "Fault diagnosis method of substation equipment based on BP neural network", Proc. SPIE 12598, Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022), 125982Y (25 April 2023); https://doi.org/10.1117/12.2673078

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KEYWORDS

Neural networks

Sensors

Diagnostics

Neurons

Signal detection

Signal processing

Design and modelling

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