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The structure of the distribution network is complex, and the high-frequency signal of the traveling wave is susceptible to interference during the transmission process, which will lead to the lack of transient information and affect the acquisition and identification of the traveling wave characteristic data. To solve the problem that the fault transient traveling wave signal of the existing distribution network is disturbed by noise and leads to inaccurate positioning, a fault traveling wave positioning method based on Variational empirical Mode Decomposition (VMD), Sample Entropy (SE), and TEO is proposed. The VMD algorithm is used to decompose the fault-traveling wave signal into the Intrinsic Mode Function (IMF) component, and the low-frequency component of the noise is filtered out. The sample entropy algorithm is used to determine the noisy IMF, and the improved threshold method is used for processing. It is reconstructed and the Teager energy two operators are used to achieve accurate calibration of the fault traveling wave head. The experimental results show that the method proposed in this paper can have good denoising ability and accurately identify the traveling wave head of noisy faults. Compared with the traditional method, the denoising effect is better and the positioning error is smaller, which effectively improves the accuracy of traveling wave positioning in the distribution network.
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