Research on fault detection of critical transmission lines based on multi-source data fusion algorithm

Abstract

Key transmission line fault detection methods have the problem of large detection errors, and design a key transmission line fault detection method based on multi-source data fusion algorithm. The component symmetry between the forward and inverse traveling waves is used to discriminate the traveling wave abnormal region, combine the time window, pinpoint the information of the time field to the daily shift data, construct a tripping warning model based on the multi-source data fusion algorithm, and optimize the critical transmission line fault detection mode. Experimental results:The mean error values of the key transmission line fault detection method in the paper, compared with three other key transmission line fault detection methods, are: 0.059, 0.113, 0.120 and 0.115 respectively, proving that the use of the fault detection method is improved when combined with the multi-source data fusion algorithm.