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The invention discloses a partial discharge signal de-noising method based on a wavelet and a high-order PDE, comprising the following steps: S1, inputting a collected partial discharge noise signal; S2, selecting an appropriate mother wavelet through a correlation coefficient method, selecting an appropriate decomposition layer number N, and performing wavelet transformation and decomposition on the collected noise signal; S3, performing high-order PDE processing on low-frequency sub-components in the Nth layer; S4, calculating the signal-to-noise ratio SNR of a de-noised signal, repeating S3 and S4, and stopping iteration until the SNR value output at any iteration is smaller than the SNR value output at the previous iteration; S5, performing threshold processing on high-frequency sub-components in the first to Nth layers; and S6, performing wavelet reconstruction on the processed low-frequency sub-components and high-frequency sub-components to get a de-noised partial discharge signal. The method is simple in calculation, runs fast, can better remove noise, achieves low distortion, and can retain the signal edge properly.

Partial Discharge Signal De-noising Method Based on EMD and High Order PDE