Fault Identification and Localization for Cables Based on Time-Frequency Domain Reflection

• Published in: 2023 IEEE International Conference on Control, Electronics and Computer Technology (ICCECT) pp. 896 - 900
• Main Authors: Ju, Dengfeng, Chu, Guangbin, Liang, Yun, Huang, Jie, Bai, Wei
• Format: Conference Proceeding
• Language: English
• Published: IEEE 28.04.2023
• Subjects: cable; fault location; High-voltage techniques; Location awareness; Power cable insulation; Power cables; Reflection; TFDR; Time-frequency analysis; Transmission line measurements; type identification
• DOI: 10.1109/ICCECT57938.2023.10140642

The insulation strength of cable is related with the security operation of power transmission and distribution system. Insulation diagnosis and fault localization for high voltage cables has great significance for urban power g rid security. This paper presented a novel method based on the time-frequency domain reflection method (TFDR) that can restrain the noise interference in the measurement of impedance spectroscopy of cables to precisely identify and locate defects in high voltage cable. In the paper, the cable transmission line model under normal operation and different fault types was analyzed according to the principle of TFDR cable fault location and the distribution parameter model of power cables. The cable sample that contains thermal aging defects is manufactured. The cable defect state features are extracted automatically based on the signal inject method and coupling devices from the original input samples, and the fault type recognition and location are realized with the time-frequency analysis algorithm. Based on the developed cable samples and detection devices, the proposed method is validated. The experimental results show that the method can effectively identify and locate the aging segments and concentration defects in cables. The TFDR method can serve as a sensitive fault diagnosis tool suitable for high-voltage cable networks under various conditions.