Modeling And Optimization Of Hydrometallurgy Leaching Process

There are lots of non-ferrous metal resources in our country. With the rapid growth of the national economy and steady progress of industrialization, it is very important to use such resources effectively and economically for sustainable development strategy 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 metal resources. Leaching process is one of the central unit operations in the hydrometallurgical processes.This thesis aims at hydrometallurgy leaching process. Based on deeply analyzing the characteristics of leaching production process, researches on prediction methods for leaching rate in hydrometallurgy leaching process and its applications are carried out comprehensively and systematically by using hybrid modeling method, which is composed of mechanism and data modeling methods. According to optimized objectives of leaching process, an optimization model is proposed based on the hybrid model. And an improved optimization algorithm is developed. The main researches are summarized as follows:1. Through analyzing the basic principle of leaching process, the leaching of gold ore which takes cyanide as the leaching agent is studied. A mechanism model for leaching process is proposed by analyzing the relationship of material balance and energy balance. The main parameters of model are verified using experimental analysis and identification. The validity and generalization of the model are proved through experiments which are tested by practical data. Meanwhile, the effect for leaching rate of leading factors is analyzed by simulation experiment. The basis of hybrid model and process optimization is established by the mechanism model.2. Due to the complexity of the leaching process, the mechanism model is based on several assumptions and simplifications. Therefore, its prediction accuracy is low. According to the mechanism model, this thesis builds the hybrid model of leaching process by the hybrid modeling theory. It consists of two parts:the mechanism model and data-driven model. The mechanism model describes the basic characteristics of the leaching process. The data-driven model compensates the model error by a kernel partial least squares (KPLS) method. By simulation experiment, the efficiency of the hybrid modeling methods has been verified.3. According to the research on the leaching process, the thesis establishes the optimization model for operation variables of leaching process with the aim of economic benefits. And then it uses the propagation of particle swarm optimization method to optimize the process. The validity of the method is shown by the comparison of the optimization results with the production records.4. Taking a leaching section in a gold hydrometallurgy plant as a research example, prediction and optimization operating system software of leaching section has been designed and developed based on the above theory studies. Prediction for leaching rate of leaching process has been achieved. And the optimal operating guide for this process has been provided.