Research On Optimization And Control Compensation Methods For Hydrometallurgy Overall Process Based On Data

Hydrometallurgy is the efficient process of dealing with low-grade mineral. There is close relationship between the integrated production indices and metallurgy enterprises economic benefit. The technical indices of hydrometallurgy are the belts between the integrated production indices and the production control, and they also have direct effects on the yield and other integrated production indices. And technical indices are realized through operation variables. Thus, researching on optimization and control for hydrometallurgy overall process based on data has important theoretical and practical significance.As a very complicated production process, hydrometallurgy process is influenced by various factors, and the relation of these factors is variable, strong coupling, non-linear; Especially, considering with the problem of optimization and control from the viewpoint of overall process, model error of process is inevitable, which leads to the difficulty of reaching method optimization and control of based on mechanism model. Therefore, how to compensate the optimization control results, which realized based on the mechanism model, through the data mining method and finally realize the optimal control is very crucial. The thesis, above all, specifically introduces flow of the hydrometallurgy process and process analysis, then analyzes and describes the processes. Regarding to the complexity and special characteristics of the whole process, realizing the optimization control of a single processes doesn’t mean that solve the hydrometallurgy overall process optimization control problem. Considering hierarchic optimization control strategy and complexity of whole production process, it puts forward a kind of hierarchic optimization control compensatory method. The first layer is the overall process-level optimization control, which takes the process indices as the goal to compensate,; The second layer takes the process indices determined in the first layer as the desired goals, and compemsate operation variables. According to whether there is the data for the production process, two different strategies are proposed in this paper to solve the problem of optimization and control copensation for hydrometallurgy overall process. When the enough field data is available, a data mining method based on rough set is used to extract the compensation empirical rule between each process indices and operation variables of this process from a large number of accumulated optimal data for the whole process. If the actual production conditions change, the empirical rule is adopted to optimize and compensate the production process. When there is not or lake of field data, it analyzes correlation degree of process indices and operation variables through mechanism model.Then, according to the size of the correlation degree, combined with process analysis, it can get the copensation scheme. With the production process progressing, lots of optimization data has been accumulated. While the data is enough, it can use data mining method based on rough set to optimize and control the overall process. Finally, the proposed methods in the thesis are proved to be effective and feasible for hydrometallurgy overall process through simulation.