| The curing machine is an important part of the dyeing machine,the fabric is pre-cured and then enters the curing machine,in which at a high temperature for 60 to 80 seconds,so that some chemicals can fix on the surface or inside of the fabric fiber.In order to meet the technical requirements of the dyed fabric,the temperature of circulating air in the curing chamber must be set in a reasonable range and the temperature difference of the entire curing chamber should be as small as possible.The paper takes the curing machine as the object of research,for the reason of the phenomenon that the difference of the air temp erature is large and the air temperature is nonuniform in the curing chamber,we research it from two aspects which is the air temperature control system and the air flue entrance speed control system.Firstly,in terms of the air temperature control system,analyze the heated air temperature,determine the air temperature control system is a complex control system with nonlinearity,great inertia,large time lags and the strong interference characteristics,the paper have an experimental determination of the step response curve of the system,and stimulate the mathematical model of the system.The article presents a method that use the fuzzy neural network PID that combine with fuzzy controller,neural network controller and PID controller to control the temperature of the curing machine,and established the network model of the fuzzy neural network PID controller.The article used MATLAB for simulation analysis,and compared the fuzzy neural network PID with the traditional PID and the fuzzy PID in two sets of simulation results,we can see that the method satisfies the requirements of various technical indexes of the temperature control system of curing machine,and the overshoot is close to zero,the vibration disappeared in system,the accommodation time is reduced to 500s,and the temperature is affected by external disturbances rarely,it has good disturbance compensation and the ability of anti-interference,the robustness of the system has improved greatly,and it can meet the purpose of controlling the hot air temperature of the curing machine well.Secondly,in terms of the air flue entrance speed control system,introduced the basic structure and effect of the air flue and the nozzle of the curing machine.Numerical simulation analysis on the flow field in the air flue by Fluent found that because of the unreasonable structure of air flue,the speed of hot air from the air flue into the curing chamber is nonuniform extremely,and causing the temperature of the hot air in the curing chamber is nonuniform.Reconstructed the structure of the air flue and analyzed and optimized the velocity field in the air flue fiom three aspects,we can see that the outlet average speed of the optimized air is reasonable,the range of the speed fluctuation is small,and the speed difference between the slit-nozzle meets the requirements.Use the optimized air flue to control the inlet air speed,so that the speed and temperature in the curing chamber is more evenly,and the control system can improve efficiency and reduce energy loss.Through the simulation verification,the use of the air flue for phased speed control is effective.Finally,researched on the hardware and software of the curing machine temperature control system.Designed the structure of the hardware and selected the model number of the hardware,and designed the software of the upper computer and the lower computer.Since the Kingview and MATLAB can interact through OPC,the module of fuzzy neural network PID control with complex algorithm is implemented in MATLAB.Completed control of the entire system with the Kingview and PLC.Finally,tested the air temperature control system found that the control effect was good. |
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