Coke Production Process Quality Modeling And Its Optimization Control

The production process of coke is complicated large-scale system composed of multi-subsystem, which has the characteristic of severe non-linearity, uncertainty, time-varying, large-delay, strong coupling and multiple-parameter. its main product is coke. Coke is the main fuel and raw materials in the process of iron production in the blast furnace, plays an important role of a chemical reducing agent and permeable support in the skeleton. Coke is known as "the basic food of iron and steel enterprises" The quality of coke industry in each subsequent production stability has important significance. Therefore in order to ensure the realization of coke quality, coke production process optimization control, establishment of coke quality model is very meaningful. For coke production process, the product of many factors, because of its production process complex together with industrial noise pollution, the quality of modeling and optimization control have great difficulty.The paper is based on the production process and mechanism analysis of coke product, analyses and discusses the indicators of coke quality and the factors that affect the coke quality deeply, and propose the question of the production quality modeling and quality optimization of the coke production process.Then the paper gives BP neural network modeling approach of the coke quality which is based on based on GA optimization. Then simulates and analyses the model through the actual production data, the results show that the model has high prediction accuracy and good predict effectes, and the predicted hit rate can reach the actual requirements of the coking plant.The problem of quality optimization for the production process of coke are discussed deeply. Based on the improved particle swarm algorithm and its optimization analysis, this paper proposes the optimization method, which is based on Improved Particle Swarm Optimization Algorithm, for the coke production process product quality. The simulation results show that the proposed method is an effective and reliable solution to this optimization problem. It is effective theoretical basis to the coke industry optimization control provides an effective theoretical basis...