Prediction of Insulation Deterioration Degree of Cable Joints Based on Temperature and Operation Data

• Published in: Ji suan ji ke xue Vol. 49; no. 10; pp. 132 - 137
• Main Author: XU Si-qin, HUANG Xiang-qian, YANG Kun, ZHANG Zhan-long, GAN Peng-fei
• Format: Journal Article
• Language: Chinese
• Published: Editorial office of Computer Science 01.10.2022
• Subjects: cable joints|insulation deterioration|sparrow search algorithm|kernel extreme learning machine
• ISSN: 1002-137X
• DOI: 10.11896/jsjkx.210900139

The deterioration of cable joints will lead to the increase of heat loss,and then lead to the rise of surface temperature of the joints.At the same time,the surface temperature is affected by many factors such as operating load,environmental temperature.In general,the relationship between deterioration degree and temperature data shows a non-linear distribution.For this reason,a prediction method based on improved sparrow search algorithm(ISSA) optimization for kernel extreme learning machine(KELM) is proposed to predict the insulation deterioration degree of cable joints.Firstly,based on the experimental validation of the multi-physical coupling model of cable joints,the surface temperature distribution data of cable joints at different deterioration levels,loads and ambient temperatures are obtained for building the training set,validation set and test set.Secondly,the sparrow search algorithm is optimized based on the idea of flight behavior in the bird swarm algorithm(BSA),which ensures global convergence