Modeling And Adaptive Real-Time Optimization Of Hydrometallurgy Cyanidation Leaching Process

Resources are not only the basis of development of the economic,but also the main factor to restrict economic and social developing.With the rapid development of our economy,the consumption of mineral resources is also increasing which make for rapid reduction of high-grade ore.While there are a large number of low-grade non-ferrous mineral resources in our country,how to use these resources effectively is of great significance to the sustainable development strategy of our country.As one of the two extractive metallurgy technologies,Hydrometallurgy has obvious advantages compared with pyrometallurgy.Hydrometallurgy has 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.Leaching process is one of the central unit operations in the hydrometallurgical processes.It directly determines the purity of metal extraction.Although leaching technology in hydrometallurgy of our country meets advanced world standards,the control of leaching production process still remains low level of automation,remains manual control and off-line assays,which lead to low efficiency,high recourses and energy consumptions and unstable product quality.Therefore,it has seriously restricted the development of hydrometallurgical industry in our country.This thesis aims at hydrometallurgy leaching process of a gold refinery.Based on deeply analyzing the characteristics of leaching production process,we establish the mechanistic model for forecasting of leaching rate,Then discuss the amount of cyanide added optimal setting for the purpose of lowest cost.The main researches are summarized as follows:1.Taking the basic principle of leaching process as the entry point,the mechanism model of the process is established based on the relationship between material and energy balance.We determine the main parameters of the model from industrial data,documents and other methods,and the most important parameters which need identification later are empirical value and greatly influenced by the technology.By model simulation,the process characteristics of the leach process were revealed,and the influence on the leaching rate of the factors are analyzed.2.Aim at the leaching process parameters which to be identified,proposed a method of identification of the leaching process mechanistic model parameters based on the genetic algorithm,and the leaching rate of the prediction model is established.At last the accuracy of the model is validated by simulation experiment.3.According to the research and analysis on the leaching process,the thesis establishes the optimization model for operation variables of leaching process with the aim of minimum material loss.And then it vises modifier adaptation real-time optimization method to optimize the process instead of the optimization method based on the model,which makes the optimization result more close to the actual optimal control trajectory.Finally the validity of the method is verified by simulation.4.Taking the whole process of hydrometallurgical refinery integrated control system project in Shandong province as background,the leaching section plant as a research object,a prediction and optimization operating platform 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 can provide the optimal operating guide for this process.