Cable Life Prediction Based on BP Neural Network

Abstract

A power cable is a cable used to transmit and distribute high-power electrical energy in the backbone of the power system. Cross-linked polyethylene insulated cable has been widely used due to its various advantages, and its design life is generally 30 years, during which it will inevitably be affected by the internal or external environment of the cable, resulting in cable accidents. At present, most of the studies mainly focus on the local influencing factors of cables, which are broadly divided into three categories: mechanical properties, physicochemical properties, and electrical properties, and the results of the studies can only reflect the assessment of the influence factors on the degree of cable aging, and cannot specifically give the number of years the cable has been in operation. Therefore, this paper proposes an intelligent algorithm model based on BP neural network. The algorithm takes the measured operational data of the cable as input and then trains the network model to realize the calculation of the operational life of the cable. The simulation results show that the algorithm has the advantages of high accuracy and fast convergence.