基于神经网络算法的工业炉炉温控制系统研究  

Research on Industrial Furnace Temperature Control System Based on Neural Network Algorithm

作　　者：高海英[1] GAO Haiying(Xi'an Aeronautical Polytechnic Institute,Xi'an 710089,China)

机构地区：[1]西安航空职业技术学院,陕西西安710089

出　　处：《工业加热》2025年第1期24-26,35,共4页Industrial Heating

基　　金：陕西省“十四五”教育科学规划2022年度课题(SGH22Y1638,SGH22Y1633)。

摘　　要：准确控制对于确保产品质量、提高生产效率以及节约能源具有重要意义。随着科技的不断发展,神经网络算法作为一种强大的计算工具,在工业炉炉温控制系统中得到了广泛应用。神经网络算法以其模拟人脑神经元网络的方式进行计算,能够处理非线性、复杂的系统,具有强大的逼近能力和学习能力。在工业炉炉温控制领域,传统控制方法存在难以克服的挑战。因此,引入神经网络算法作为炉温控制系统的智能化手段,成为提高控制性能和适应性的有效途径。以步进式加热炉作为研究对象,讨论其构造及炉温控制难点,介绍神经网络模型及多步预测控制原理及方法,并对步进式加热炉神经网络炉温预测及控制界面设计做出具体介绍,希望能够为工业炉炉温控制系统的智能化提供新的思路和方法。Accurate control is important to ensure product quality,improve production efficiency and save energy.With the continuous devel-opment of science and technology,neural network algorithm,as a powerful computational tool,has been widely used in industrial furnace tem-perature control system.Neural network algorithms simulate the neuron network of the human brain to carry out calculations,and can deal with nonlinear and complex systems,with strong approximation ability and learning ability.In the field of furnace temperature control for industrial furnaces,there are insurmountable challenges in traditional control methods.Therefore,the introduction of neural network algorithm as an in-telligent means of furnace temperature control system becomes an effective way to improve the control performance and adaptability.The step-per-type heating furnace is taken as a research exclusive,discuss its structure and furnace temperature control difficulties,introduce the neural network model and multi-step predictive control principles and methods,and make a specific introduction to the stepper-type heating furnace neural network furnace temperature prediction and control interface design,hope to be able to provide new ideas and methods for the intelli-gence of industrial furnace furnace temperature control system.

关 键 词：神经网络算法 工业炉 炉温控制 

分 类 号：TG155.1.2[金属学及工艺—热处理]