Transformer Fire Identification Method Based on Multi-Neural Network and Evidence Theory

In order to solve the problems of transformer fire accidents such as the traditional fire control system has simple function, single fire characteristic parameters and is prone to false alarm, underreporting and so on, a synthetic diagnosis method using multi-neural network and evidence theory for transformer accidents is presented. The monitoring and early warning of transformer fire is realized by collecting temperature, video (flame and smoke), CO, combustion sound and other information in real time, and then combining with network technology. The results of example analysis show that the accuracy of this method for transformer fire identification is 73%.