Cable is an important tool to transmit the electricity in power systems. However, the local defects caused by some negative factors can lead to great loss of the power systems. Time-frequency domain reflectometry (TFDR) is one method to accurately locate such defects, but traditional Wigner-Ville distribution (WVD) used in TFDR will bring about cross-terms interference problem. To solve the problem, Gaussian window pseudo Wigner-Ville distribution (PWVD) is proposed. PWVD is a kind of windowed Wigner-Ville distribution, which can greatly reduce the amplitudes of the cross-terms in traditional TFDR. Compared to Choi-Williams distribution and filtering methods, it does not increase the number of variables, so the amount of calculation can be smaller. Besides, due to the Gaussian envelope of the incident signal, the Gaussian window can automatically fit the signal period. And the cable defect localization ability of the method was verified by several cable breakage defect positioning experiments. The cable defect positioning method based on Gaussian window PWVD can accurately locate the defects of cables. And the method is expected to solve the cross-terms interference in TFDR and to be utilized as one of the main diagnostic methods in power system in the future.

Cable defect; positioning; Gaussian window; pseudo Wigner-Ville distribution; time-frequency domain reflectometry