Mr. Yabin Zhang Profile

Yabin Zhang

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Proceedings Article | 25 April 2023 Paper

Fault diagnosis method of substation equipment based on BP neural network

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

Proceedings Volume 12598, 125982Y (2023) https://doi.org/10.1117/12.2673078

KEYWORDS: Neural networks, Sensors, Signal processing, Signal detection, Neurons, Diagnostics, Sampling rates, Design and modelling, Transformers, Power supplies

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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.

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