An Efficient Cross-Terms Suppression Method in Time–Frequency Domain Reflectometry for Cable Defect Localization

Abstract

Time–frequency domain reflectometry (TFDR) is a highly sensitive method to locate the defects of cables. However, there are cross terms when a multicomponent signal is converted to the time–frequency domain by the conventional Wigner–Ville distribution (WVD), which will greatly interfere with the localization results. To solve this problem, pseudo Wigner–Ville distribution (PWVD) with Gaussian-rectangular window is proposed in this article, which can significantly reduce the amplitude of the cross terms without changing the energy distribution in the time–frequency domain. The simulation results show that the normalized amplitude of the cross term has been greatly reduced with the method proposed in this article. Due to the large number of independent variables in this algorithm and large storage requirements for calculation, a simplification method based on dimensionality reduction is proposed to improve the computational efficiency. Experiments were also carried out to verify the effectiveness of this algorithm. The amplitudes of the localization curve at the defects based on PWVD are much larger than the results via conventional WVD. Besides, the numerator of the cross correlation function between the incident signal and the reflected signal is found to be related to the degree of the defect. The method is expected to significantly improve diagnosis accuracy in cable defect localization and assessment in the future.