A Boiler Heating Surface Overtemperature Warning Method Based on Multi source Data Fusion and Neural Network Model

In order to accurately monitor the overheating of boiler heating surfaces and ensure the safety of boiler use, this paper proposes a boiler heating surface overheating warning method based on multi-source data fusion and neural network model. By integrating data from multiple sources such as temperature sensors and pressure sensors, real-time monitoring of the temperature status of the boiler heating surface is achieved. At the same time, a neural network model is used to learn the warning threshold, thereby achieving accurate warning of overheating of the boiler heating surface. The experimental results show that this method can effectively improve the accuracy and timeliness of boiler heating surface overtemperature warning.