Fire Early Warning System of Substation AC power supply Based on BP Neural Network Model

Abstract:
In order to effectively identify the unsafe factors of substation AC power supply and give effective early warning of fire accidents, in this paper we analyze the change mechanism of various sensing data in the process of substation AC power supply fire. Then, based on multi information fusion method, BP neural network algorithm is used to analyze and monitor the risk factors of fire in station AC power supply, and a fire early warning algorithm based on BP neural network is proposed. Based on this algorithm, a station AC power fire early warning system is proposed. The test shows that the system can quickly identify the factors that may cause fire accidents in the station AC power supply and give early warning in advance, which provides a valuable reference for the application of station AC power supply fire early warning engineering.