Design and Development of Ice Monitoring and Early Warning System for Distribution Power Lines

In recent years, frequent occurrences of low-temperature rain, snow, and freezing weather have increased the risks of power distribution line pole overturning and line interruptions. This paper designs and develops a distribution line icing warning system based on BP neural networks. Firstly, a front-end and back-end separation architecture is adopted to design and develop the system. The front-end is realized using technologies such as VUE3.2, ElementPlus, axios, Amap, and HeFeng weather API. The back-end is developed using the SpringBoot and Mybatis-Plus frameworks, along with the MySQL database. Then, by using a combination of JAVA and MATLAB programming techniques, the system implements the daily prediction of icing thickness for distribution lines based on BP neural networks. Taking a typical icing-prone region as an example, the accuracy of the icing thickness prediction is verified, and the monitoring and warning of distribution line icing are achieved.