Modeling And Intelligent Control Of Temperature In Transition Ladle In The Production Of Ultra-thin Amorphous Alloy

Ultra-thin amorphous alloy has the characteristics of low loss,high magnetic permeability and miniaturization,and are widely used in power electronic equipment manufacturing.In actual production,the thickness of the ultra-thin amorphous alloy are affected by many factors.The temperature in the transition ladle is one of the main influencing factors.The temperature in the transition ladle is too high,The viscosity of the melt will be reduced,resulting in the reduction of the friction between the laminar flows of the melt,the amount of the melt sprayed from the nozzle of the transition ladle during the belt making process,and the thickness of the ultra-thin amorphous alloy will also be reduced;if the temperature in the transition ladle is too low,it is easy to cause the melt to solidify in advance and block the nozzle.Accurate temperature control in the transition ladle is one of the keys to the stable production of ultrathin amorphous alloy.In this thesis,the temperature in transition ladle in ultra-thin amorphous alloy production is taken as the research object,the prediction model of temperature in transition ladle is established,and the control strategy of temperature in transition ladle based on fuzzy PID in prediction variable theory domain is proposed to realize the intelligent control of temperature in transition ladle and reduce the temperature fluctuation in transition ladle.The main contents of this paper are as follows:(1)The production process of ultra-thin amorphous alloy is studied,the composition of ultra-thin amorphous alloy production system is analyzed,and the working principle,mechanical structure and electrical connection of alloy smelting equipment,belt-making equipment,coiling equipment and thickness measuring equipment are summarized.The subsequent research on temperature control of the transition ladle lays the foundation.(2)Aiming at the problem of delay and strong coupling in the temperature control system of the transition ladle.Based on the guided mutation GA-BP neural network,the temperature prediction model of the transition ladle is established to predict the temperature trend in the transition ladle in the future,which provides a reference for the parameter adjustment of the temperature controller in the transition ladle.Firstly,the absolute median method is used to preprocess the ultra-thin amorphous alloy production site data,eliminate and interpolate the abnormal data.The field data of ultra-thin amorphous alloy production are classified and stored according to the thickness specification;Then,the factors that affect the temperature in the transition ladle are selected as the input variables of the prediction model,and the prediction model of the temperature in the transition ladle based on BP neural network is established.The weight and threshold of BP neural network are optimized by genetic algorithm,and the guided mutation factor is added on the basis of traditional genetic algorithm to speed up the optimization speed and improve the accuracy of the prediction model of the temperature in the transition ladle;Finally,the simulation experiment based on the actual production data of ultrathin amorphous alloy verifies the accuracy and effectiveness of the temperature prediction model in the transition ladle.(3)Aiming at the problem that the temperature in the transition ladle fluctuates greatly and it is difficult to control accurately.in the production site.The predictive variable universe fuzzy PID control strategy is proposed.Firstly,the fuzzy universe expansion factor is combined with the temperature prediction model in the transition ladle,and the predictive universe regulator based on rule reasoning is designed to realize the advance correction of the fuzzy universe according to the temperature change trend;then the fuzzy controller takes the temperature deviation and deviation change rate in the transition ladle as the input,and dynamically modifies the PID controller parameters through fuzzy reasoning to realize the intelligent control of the temperature in the transition ladle;Finally,the temperature control model in the transition ladle is established based on the production field data of a steel plant in Shanxi,and a large number of simulation experiments are carried out.The results show that the temperature control method of the transition ladle proposed in this paper has faster response speed,higher control accuracy and stronger anti-interference performance.(4)Based on Win CC software design and development,the monitoring host computer interface for the production process of ultra-thin amorphous alloy is developed,and the data communication between Win CC and Matlab is established by using OPC technology,which realizes the real-time display,data storage and analysis,and alarm and record prompts of important parameters in the temperature control process of the transition ladle,temperature prediction model algorithm parameter setting in transition ladle,temperature intelligent control algorithm parameter setting and other functions.