基于模糊神经网络的热风炉温度智能控制研究  

Research on Intelligent Control of Hot Air Furnace Temperature Based on Fuzzy Neural Network

作　　者：王珺[1] WANG Jun(Xi'an Aviation Vocational and Technical College,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》2023年第11期30-32,37,共4页Industrial Heating

基　　金：高职院校“双师型”教师教学能力发展研究(22XHJG30)。

摘　　要：钢铁工业始终是我国现代工业的支柱之一,在经济和社会方面都有着重要的影响,钢铁是现代工业发展的重要基础材料。随着我国工业化水平的不断提高,对钢铁的需求也在不断增加,因此钢铁的冶炼生产直接关系到我国的基础设施建设。热风炉属于热动力机械,是工业冶炼生产的的重要设备,其控制系统直接关系到高炉蓄热以及节能问题。本文在现有文献资料基础上综合分析了模糊神经网络控制系统、热风炉燃烧变化过程包括温度的变化以及智能燃烧控制策略,针对性提出了基于模糊神经网络的热风炉温度智能优化方式,最后对设计的模糊神经网络温度控制进行了系统仿真研究,发现应用模糊神经网络能够使得热风炉温度较快的到达稳态,从而提升了热风炉自动燃烧的控制效果。Iron and steel industry has always been one of the pillars of China's modern industry,in economic and social aspects have an important impact,iron and steel is an important basic material for the development of modern industry.With the continuous improvement of China's industrialization level,the demand for steel is also increasing,so the smelting production of steel is directly related to the construction of China's infrastructure.Hot blast furnace is an important equipment in industrial smelting,and its control system is directly related to heat storage and energy saving of blast furnace.Based on the existing literature,the fuzzy neural network control system,the combustion change process of hot blast stove,including the change of temperature,and the intelligent combustion control strategy are comprehensively analyzed,and specifically proposes the intelligent optimization method of hot blast stove temperature based on fuzzy neural network.Finally,the designed fuzzy neural network temperature control system is simulated.It is found that the application of fuzzy neural network can make the temperature of hot blast furnace reach the steady state quickly to improving the control effect of automatic combustion of hot blast furnace.

关 键 词：模糊神经网络 热风炉 温度智能控制 系统仿真 

分 类 号：TF325.4[冶金工程—冶金机械及自动化]