Iterative Optimization Based On Data Model Of Hydrometallurgy Cementation Process

As the rapid development of metallurgical industry, it is very important to use resources effectively and economically for sustainable development of our country. As one of the two extractive metallurgy technologies, the remarkable advantages of hydrometallurgy are high comprehensive recovery rate of valuable metal in raw materials, benefit of environmental protection and easy fulfilment of continuous and automated production processes. Therefore hydrometallurgy is more suitable for recovering low-grade metal resources. The hydrometallurgical cementation process is one of important processes in hydrometallurgy. The control of cementation production process still stays on off-line analysis, experience adjustments and manual control, which lead to low efficiency, high resources consumption and unstable product quality. And it becomes a bottleneck for hydrometallurgy industrial development in our country.This thesis aims at the control of the quality of products in cementation process of hydrometallurgy. Based on deeply analyzing the characteristics of cementation production process, it is researched comprehensively and systematically on mechanism analysis, data model and optimization of batch to batch. The main researches are summarized as follows:(1) Based on analyzing cementation process of hydrometallurgy deeply and characteristics of plate and frame filter press, the dynamic reaction model of cementation process is established and a qualitative analysis is carried out. To aim at the difficulty of applying the dynamic first principle model to the industrial field directly, the data model of the process is established using the Kernel Partial Least Square algorithm, and the validity of the model is verified through a series of simulation experiments.(2) In order to maximize gold grade and minimize the consumption of zinc powder, the iterative optimization method is used to optimize and control cementation process based on KPLS model.(3) Due to the uncertain factors in batches of cementation process, the model and plant mismatch and the optimal control trajectory based on the model may deviates from the one which is based on the plant using iterative optimization method without considering uncertainty. To solve this problem, modifier adaptation method is used for real-time adjustment of optimization objectives and constraint conditions to keep Karush-Kuhn-Tucker using the information of previous batch processes as well as the measurement information in the present, and the actual optimal control trajectory of cementation process is achieved. Taking gold grade as optimization goal and taking zinc powder as decision variables, simulation experiments are carried out.(4) Finally, the prediction and optimization simulation platform for the hydrometallurgical cementation process is designed and built in this paper. And every part structure and function of the simulation platform is also introduced.