Abstract

Cables are mainly composed of wires and are used to transmit signals or electrical energy. It can be seen everywhere in real life. However, due to the changeable environment in which it is located, it often leads to the problem of insulation aging. Therefore, it is particularly important to study the law of cable insulation aging and to evaluate its life. Humpback whale hunting behavior is simulated by WOA, a swarming intelligence algorithm. It can intelligently identify the relationship between various data. SVR is a linear regression model with a special computational loss. The aim of this paper is to investigate a WOA-SVR model to evaluate the aging law and life of cable insulation. This paper analyzes a variety of detection models. Finally, the partial discharge detection model and the depolarization detection model are selected for comparative testing with the WOA-SVR model studied in this paper. The test method is to count the aging of cable insulation under different temperature, humidity, and electric field strength environments. The test results show that the evaluation accuracy of the WOA-SVR model in this paper is 92%, 97%, and 98%, respectively, under different temperatures, humidity, and electric field strengths. The average accuracy of its evaluation is higher than the other two models. Therefore, the WOA-SVR model is more accurate and reliable for the cable insulation aging law and life evaluation.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call