Research And Application Of Dynamic Optimization Algorithm In Production Process Of Cement Calcining System

Cement industry is the pillar industry of China’s national economic development.Cement firing system is one of the three major links of cement production.Optimization of the production process of cement firing system is of great significance to reduce the production process cost and improve the quality of cement products.At present,the optimization of the production process of the cement firing system mainly depends on the experience of the operator,which cannot guarantee the rationality of the optimized operation.At the same time,the unreasonable operation will cause a large amount of energy consumption in the production process.Combined with the optimization of the production process of the cement firing system,based on CNN cement clinker quality and calcining process energy consumption prediction model,on the basis of the prediction model is ADE algorithm is adopted to establish the cement firing system production process optimization model,which fall in the premise of guarantee the quality of cement clinker fever as the energy consumption of the system,finally,the cement firing system based on optimization model of production process optimization software design and implementation of software system,and in the cement enterprises the field application.Specific research contents are as follows:(1)The process flow of the cement calcining system was studied,the production index and influencing factors of the sintering system were analyzed,the key variables with strong correlation with the energy consumption and quality index of the cement calcining system were selected,and the dynamic optimization model was proposed according to the analysis results.Finally,the overall dynamic optimization scheme of the production index of the cement calcining system was introduced.(2)For cement production process of the nonlinear,strong coupling and time-varying delay problems,according to the selection of variables by using convolutional neural network to establish the quality of cement clinker can be applied to the actual working condition prediction model and calcining process energy consumption prediction model,and based on the established forecast model,the quality of cement clinker as energy consumption optimization constraints,to minimize energy consumption as a target,using the adaptive differential evolution algorithm design index of the cement calcining system production dynamic optimization algorithm model,implements the cement calcining system to minimize energy consumption optimization solution;(3)For cement production process quality and energy consumption index can not be real-time measurement problem,based on the above research content of the theory analysis and model,using C# programming language and SQL Server2014 database,designing and implementing the cement calcining system production process optimization software,after the laboratory simulation software is applied to the scene of the production system is optimized in the experiment,according to the analysis of experimental data to verify the effectiveness of the optimization algorithm.