In order to effectively suppress the white noise existing in the measured partial discharge signal of port high-voltage switchgear,an adaptive threshold denoising algorithm based on wavelet is proposed.Firstly,the threshold selection and threshold function in the wavelet threshold denoising algorithm were optimized,and the applicability and flexibility of the algorithm were improved by adding variables.The improved particle swarm optimization(SPSO)was applied to solve the optimal value of the added variables,so as to realize the adaptive selection of wavelet decomposition levels,wavelet threshold and threshold function.Secondly,the simulated signal and the measured signal were denoised.The results show that compared with the traditional denoising with soft and hard threshold functions,the signal-to-noise ratio of the proposed algorithm is improved by 5.31 dB and 2.38 dB respectively.From the time domain diagram of the denoised signal,it can be seen that compared with other algorithms,the proposed algorithm not only can bring good denoising results,but also can greatly retain effective components in signals.
关键词
高压开关柜/白噪声/局部放电/小波/自适应阈值/粒子群算法
Key words
high voltage switchgear/white noise/partial discharge/wavelet/adaptive threshold/particle swarm optimization algorithm
维普
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