Design Of Automatic Control System For Blast Furnace Coal Injection And Research On Key Control Algorithms

With the continuous penetration of automatic control technology into various fields of social production,in order to reduce production costs,Chinese iron and steel enterprises have proposed an automatic control technology for blast furnace coal injection that uses pulverized coal instead of coke.How to achieve stable,continuous and safe pulverized coal injection has always been a major research problem for researchers.This paper takes the automatic coal injection control system of the No.3blast furnace of a steel plant in Shandong as the research object,designs the software and hardware of the control system,and studies the key control algorithms to realize the stable and continuous injection of pulverized coal.The main research contents of this paper are as follows:(1)In-depth study of the process and characteristics of the blast furnace,combined with the control system design requirements and technical indicators,analyzes the problems and control difficulties in the control system,and gives the overall design plan of the control system.(2)A detailed analysis of the key problems existing in the blast furnace coal injection control system of the steel plant,and the design of a blast furnace coal injection automatic control system with Siemens S7-300 as the control core and a system structure combining industrial Ethernet and Profibus.The detailed software and hardware design,hardware selection,electrical schematic design,system configuration,control program design and man-machine interface configuration design of the control system are given.The system can realize the functions of pulverized coal preparation,pulverized coal injection,data recording,fault alarm,remote debugging and monitoring.Aiming at the problems of inaccurate calculation of coal injection quantity and unstable control,an input-processing-output(IPO)model and a multiple linear regression coal injection quantity measurement model are proposed.The model analyzes the main factors affecting the amount of coal injection in the system,uses real-time update variables to iterate the parameters of the regression equation,updates the measurement value of the coal injection volume in real time,and realizes the accurate measurement of the coal injection volume.So as to ensure the stable control of the amount of coal injection,and realize the precise injection of pulverized coal.(3)Aiming at the problem of ambiguity and blindness in the manual setting of coal injection rate in automatic control system,a coal injection rate prediction model based on improved particle swarm optimization(IPSO)optimized extreme learning machine(ELM)is proposed.Improve the convergence of the particle swarm optimization(PSO)by using chaotic inertia weights and adaptive learning factors,introduce cross-mutation operations of genetic algorithms to improve the global optimality of the particle swarm optimization,and then use the improved particle swarm optimization to establish the IPSO-ELM coal injection volume Forecast model.The simulation results show that the prediction model has higher accuracy than the ELM coal injection volume prediction model and the PSO-ELM coal injection volume prediction model.It also has higher prediction accuracy when the furnace condition fluctuates greatly,and has higher industrial application value.