Design of Comprehensive Evaluation System for Cable Joint Quality Based on Multi-Dimensional Detection Technology

In urban power grids, the reliability of cable joints is crucial to the stability of the entire power supply system. In view of the common fault problems of cable joints, this study aims to develop a cable joint quality evaluation system based on intelligent algorithms. The system integrates a variety of detection technologies, such as X-ray detection, high-frequency current detection, etc., uses the Analytical Hierarchy Process (AHP) to determine the weight of each detection data, and uses the random forest algorithm to perform comprehensive quality scoring and fault prediction. By introducing XGBoost and neural network algorithm (N-XGBoost), the system can learn historical detection data and continuously optimize the evaluation system. In practical applications, this evaluation system has been used in on-site inspections, and can effectively predict the smooth operating life of cable joints, and conduct on-site rectification of cable joints that do not meet standards. Through detailed case analysis, the effectiveness and practicality of the system are proved. Overall, this research provides an efficient and scientific evaluation method for the maintenance of cable joints, which significantly improves the operational safety and reliability of the power system.