Partial discharge detection method for power equipment based on UHF method

Shengchun Liu and Jie Zhang

International Journal of Energy Technology and Policy, 2024, vol. 19, issue 1/2, 120-134

Abstract: In order to avoid the impact of noise on the performance of partial discharge detection and improve the accuracy of detection results, a partial discharge detection method for power equipment based on ultra-high frequency method is proposed. Firstly, use a conical antenna sensor to collect ultra-high frequency signals during partial discharge of power equipment. Then, wavelet entropy is used to denoise the collected ultra-high frequency partial discharge signal, removing the noise components contained in the signal and retaining the effective information components of the signal. Extract features such as signal skewness, steepness, discharge level, phase, and cross correlation, and use chicken swarm algorithm to detect partial discharge of power equipment based on the extracted features. The experimental results show that the detection result of this method is the most accurate, and the number of false samples for partial discharge signal type is 0, indicating that its detection effect is good.

Keywords: UHF; power equipment; partial discharge; antenna sensor; wavelet entropy; feature extraction. (search for similar items in EconPapers)
Date: 2024
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