Abstract:

The capacitive component leakage current (CCLC) commonly exists in power distribution systems.However,it significantly interferes the leakage current measurement and reduces the accuracy of electrical fire monitoring.The leakage current test platform is built to simulate the actual circuit condition,and a data acquisition system is designed to display and acquire the data of four voltage modes and four load modes under the resistive leakage and capacitive leakage conditions.A multilayer fully connected BP neural network is used to eliminate the CCLC by predicting the resistive component leakage current (RCLC).The test results show that the prediction error of the RCLC reaches only 1.08%,which can prove that the methd can effectively identify the RCLC and improve the accuracy of electrical fire alarming.

Key words: capacitive component leakage current (CCLC), electrical fire monitoring, multilayer fully connected neural network, capacitive component leakage current compensation