Diagnosis Scheme of Cable Insulation defects based on big data Technology

Abstract:
The aging of cable insulation is the main cause of cable failure. At present, the transportation inspection department lacks a fast and effective method for cable live detection. The current harmonic method is decomposed according to the defect characteristics, which can effectively analyze the cable insulation defects, but because there are many possible relationships between the defect features and defects, it is difficult to get accurate diagnosis results simply by using the functional relationship. In order to solve this problem, this paper uses the theory of power cable defect harmonic generation, establishes the cable defect harmonic feature database, and puts forward a cable insulation defect diagnosis scheme based on big data technology. It provides big data support for live detection of power cable, and realizes intelligent evaluation and life prediction of cable.