Study On Thickness Control Of Hot Dip Galvanizing Zinc Based On BP Neural Network Model

With the increasing development of science and technology and industry level,the development of hot dip galvanized steel sheet by leaps and bounds.Galvanized steel has good corrosion resistance and physical properties,depending on the thickness of the coating,the home appliances,construction,automotive and other industries have been widely used and concerned.Galvanized zinc layer thickness is an extremely the important performance index to measure the quality of the hot galvanized steel plate,wherein the control accuracy of air knife equipment directly determine the quality and properties of galvanized steel strip.The galvanized layer is too thick,will cause the waste of raw materials,improve the production cost of products at the same time,adhesion and impact resistance of the galvanized zinc negative impact;layer is too thin or uneven.It will also affect the corrosion resistance of the hot-dip galvanized steel strip,and also can not meet the needs of the customer.Hot galvanizing production is a continuous process,the strip running through the zinc pot filled with liquid zinc,there will be a large number of liquid zinc attached on the surface of steel,high speed flow of liquid zinc excess will be ejected by the air knife blow back to the zinc pot,air knife device and the baffle and strip their specifications and speed up an important role for uniformity and control the thickness of zinc zinc layer.Thus,hot galvanized plate and strip quality and the production cost of galvanized steel surface layer thickness and uniformity are closely related.Air knife device is the key equipment to control the coating thickness,in order to make the zinc thickness control precision can meet the demands of production that must be of zinc layer thickness control The structure and principle of the execution unit of air knife research and analysis,control the thickness of zinc precision directly affects the galvanized product quality,production efficiency and performance index which influence the galvanizing line.At present,air knife control technology has been developing rapidly over the past,technology and structure have great to improve,but there are few domestic structure and control of technical experts and scholars on the air knife equipment are analyzed and discussed,which leads to some extent hindered the optimization and innovation of it.The automatic control system of galvanized layer thickness is perplexing,through the establishment of mathematical model in the actual production process and get the output function of zinc layer thickness,many manufacturers for high knife cutter spacing and other related variables and parameters mostly adopts manual adjustment way,past experience of operators often rely on this process,this kind of regulation is not the optimal regulation,the deviation of the thickness of zinc can not be timely and accurate adjustment,if things go on like this will lead to zinc layer thickness deviation,finally affects the production efficiency,but also can not completely form automatic control.Because the zinc layer thickness control process The influence factors are numerous,and these factors influence each other,mutual restraint,it is worth noting that effects of air knife equipment adjustment mechanism of zinc layer thickness is nonlinear,so if the conventional PID control theory is used to control the thickness of zinc is difficult to control the effect of the.BP neural network algorithm satisfying the the network structure formed a mapping from input to output,its powerful function,wide application range,proved that it can achieve any complex nonlinear mapping function.Therefore,to adjust the solar term knife pressure by BP neural network algorithm,and the parameters such as knife cutter spacing can be achieved since the thickness of zinc Dynamic control systemThe BP neural network to establish the double closed loop control system using the zinc layer,the hardware configuration and communication settings,making system structure improvement scheme principle diagram,determine the BP neural network model of zinc layer thickness,calculation and analysis of the learning process of zinc layer thickness of BP neural network model,the zinc layer thickness precision control within the scope of the error.The main circuit of the zinc layer thickness control system for zinc thickness closed-loop control loop,by using the BP neural network control algorithm,solving multi variable,nonlinear and difficult to establish the mathematical model of the problem;and vice loop pressure closed-loop control loop jet air knife,usually take The conventional PID algorithm is used to control the injection pressure of the air knife rapidlyThus,the rapid development of computer technology constantly updated and modern control theory,has laid a good foundation for the control of the thickness of zinc.In view of the shortcomings of manual control and many of the characteristics of zinc layer control,this paper will use the BP neural network algorithm for the related study and research,to solve the zinc thickness control related by setting up a reasonable mathematical model.