Study on live detection and fault identification of insulation defects in distribution network cables based on harmonic characteristics

Due to the complex operating environment of distribution network cables and the stringent requirements for outage maintenance, there is an urgent need for accurate and effective new live detection technologies. This study focuses on the induced current in the metal shielding layer of a 10kV single-core cable. Through theoretical derivation and modeling simulation, the evolution patterns, inherent mechanisms, and influencing factors of harmonic distortion in the induced current were investigated. The simulation results indicate that magnetic field distortions at the insulation defect locations cause abnormal harmonic components, specifically the 3rd, 5th, and 7th harmonics, in the induced current within the metal shielding layer. Further real-world experiments show that the main components of these harmonics are closely related to factors such as load current, the type of insulation defect, and the through-flow aging time of the insulation material. Finally, by applying the K-means clustering analysis algorithm to the measured harmonic data, effective classification of insulation defects in distribution network cables was achieved. At a conductor current of 400A, the recognition rate for water droplet defects reached 84.5%, providing a theoretical basis for timely warning and live diagnosis of insulation defects.