Evaluation And Optimization Of Strip Steel Quality Based On Rolling Process Parameters

Hot strip rolling is an important production process in the metallurgical industry.As the main product,hot strip rolling occupies an important position in various industries of national production,and the process of hot strip rolling mainly includes heating,roughing,finishing,laminar cooling and coiling,which has the characteristics of long process,many parameters and complex process,and is a typical complex industrial production process.At present,with the continuous development of society,the demand of users for strip steel products is not only increasing,but also the requirements for quality are getting higher and higher.Therefore,further improving the quality of strip steel products and realizing the operation optimization of the production process have become the focus of the development of steel enterprises.The quality of strip steel products directly affects the economic efficiency of enterprises,and the operation optimization of the production process is one of the necessary means to improve product quality.A scientific,objective and reasonable evaluation method can provide strong support for the improvement of product quality,and is also an important prerequisite for operation optimization.At present,only the traditional methods and strategies of quality evaluation and operation optimization can no longer meet the requirements of high-quality development of strip steel products.This thesis takes the 2250 mm hot strip mill production line of steel mill B as the research object,and addresses the problem that the production line mainly relies on manual evaluation of product quality and optimization of production process set values based on experience,and proposes a comprehensive evaluation model that can reflect the comprehensive quality of strip steel products and a master element model that can optimize the set values using industrial data,expert knowledge combined with control methods and strategies.The main research works are as follows:(1)By reading the relevant literature and learning the theoretical knowledge,we understand the development status of the hot strip rolling production process,describe the process flow and production characteristics of hot strip rolling in detail,understand the process characteristics and control system of 2250 mm hot strip rolling line in steel mill B by studying the relevant technical manuals,find the limitations in the current production of this line,and propose an optimal control scheme with synergy of quality evaluation and set value optimization for the problems of the line.(2)Collect and process the production data,combine the actual situation of production and expert experience,select suitable data,analyze the process parameters and quality data,remove the abnormal values in the data,fill in the missing values,and analyze the data statistically,and finally standardize the data to provide a better data set for the establishment of the model.(3)Taking surface quality,mechanical properties and dimensional accuracy as indicators,a fuzzy comprehensive evaluation model for strip steel products is established,and the rationality of the evaluation results of the model is improved by combining the entropy power method and hierarchical analysis method of assigning weights on the basis of considering user requirements and expert knowledge,and the scoring results are finally obtained by fuzzy synthesis of affiliation degrees.(4)Using the process parameters affecting product quality and the quality deviation obtained from the evaluation model as input,a principal element model is established to realize the optimization of the set values.Firstly,the process parameters are dimensionalized and a regression model of the quality deviation and the principal components of the process parameters is established,which is then mapped to the parameter adjustment space to guide the size and direction for the adjustment of the process parameters,so that the operator can have a basis to correct the corresponding set values and realize the optimal control of the production process.