Modeling And Optimization Control Of Hydrometallurgy Cementation Process

In recent years, as the rapid development of metallurgical industry, it is very important to use such 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 rates of valuable metals in raw materials, benefit for environmental protection, and easy fulfillment 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 remains 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 modeling, data modeling and optimization in a batch. The main researches are summarized as follows:1. Based on deeply analyzing cementation process of hydrometallurgy, the dynamic mechanism model of cementation process is established according to the material balance of zinc and gold cyanide ions in reaction process, kinetics principle of chemical reaction, and the characteristics of plate and frame filter press in the cementation process;2. To aim at the difficulty of applying the dynamic first principle model to the industrial field directly, the data modeling method is put forward to solve prediction problem of the gold cementation rate on line. First, unfold the process variables in the batch process from a three-dimensional matrix to a two-dimensional matrix according to batches, and then process data. Data model of the cementation process is established using the KPLS algorithm, and the validity of the model is verified through a series of simulation experiments; 3. Due to the disturbance in batch of cementation process, the end of the product quality may deviate from the expected quality which leads to high production cost. To solve this problem, based on the data model, particle swarm optimization method is used for the optimization of the addition amount of zinc powder in batch in order to reduce the cost of zinc powder. Numerical simulations show that, this method can solve the addition amount of zinc powder of the follow-up periods online, which provide guidance for production operations in batch for field workers.