摘要
锅炉系统具有众多输入输出参数,各参数之间相互影响、紧密关联,锅炉还有惯性大、延迟大、非线性等特点,使得建立精确的数学模型来控制锅炉运行变得异常困难。以工业燃气锅炉为研究对象,基于燃烧系统和蒸汽过热系统进行建模,分析燃气锅炉的运行过程。优选合适的输入、输出参数,建立BP神经网络模型,进行仿真实验并对仿真结果进行分析,仿真结果表明BP神经网络模型误差在合理范围内,有较高的精度和泛化能力,能较好的预测锅炉运行结果,实现对工业燃气锅炉的智能调控。
The boiler system has many input and output parameters that interact and are closely related.The boiler also has characteristics such as large inertia,large delay,and nonlinearity,making it extremely difficult to establish accurate mathematical models to control the operation of the boiler.Taking industrial gas fired boilers as the research object,modeling based on combustion system and steam superheat system is conducted to analyze the operation process of gas fired boilers.Select appropriate input and output parameters,establish a BP neural network model,conduct simulation experiments,and analyze the simulation results.The simulation results show that the error of the BP neural network model is within a reasonable range,has high accuracy and generalization ability,can better predict the operating results of the boiler,and achieve intelligent control of industrial gas fired boilers.
关键词
燃气锅炉
神经网络
智能化控制
gas fired boiler
neural network
intelligent control
