| Rare earth is an important strategic material in my country and is widely used in traditional industries such as agriculture,metallurgy,petrochemical industry,glass,ceramics,etc.,as well as high-tech industries such as new energy vehicles and aerospace.However,domestic rare earth enterprises still stay on manual adjustment and experience control when separating and purifying rare earth,and cannot realize real-time adjustment when the working conditions change.Therefore,it is necessary to simulate and optimize the rare earth extraction process.The solvent extraction method based on the "cascade extraction theory" is often used in factories to calculate the number of stages required for the production of the extraction process when developing new processes.The problem that the material and liquid cannot be completely separated according to the separation coefficient due to physical reasons such as the stirring efficiency of the motor is not considered.The design is more ideal and cannot guide actual production.This paper takes into account that the rare earth extraction process based on the mechanism model does not consider the energy efficiency of the mixer in the extraction tank,which leads to the problem of large errors between the content of each component and the actual industrial production data.In this paper,the concept of energy efficiency separation coefficient is introduced to establish a model of rare earth element content in each extraction tank that is in line with the actual extraction industry.It is applied to the optimization process to obtain the stages of the extraction section and washing section that are in line with the actual situation.function solution.Aiming at the multi-peak and multi-variable characteristics of the optimized objective function,an improved chaotic double mutation adaptive differential evolution algorithm LCTADE(Linear-Chaos and Two Mutation Strategies of Adaptive Differential Evolution)with linear population reduction is proposed.To enhance the accuracy of LCTADE and the ability to face premature convergence,a covariance matrix and a Cauchy perturbation framework are added.Finally,the superiority of the proposed improved algorithms LCTADE and CC-LCTADE compared with other improved DE algorithms and the optimization model for calculating the content of each component at all levels based on the energy efficiency separation coefficient are verified by simulation.The specific research content is as follows:1.Use the optimized process to design the parameters of the rare earth enterprise construction or reorganization of the rare earth extraction process.It is necessary to calculate the content of each level of the rare earth element to determine the stages of the extraction section and the washing section.After analyzing the traditional calculation model of the relative separation coefficient based on the mechanism model,considering the efficiency of the extraction tank and introducing the energy efficiency separation coefficient,an optimization calculation model for the content of each component at each level based on the energy efficiency separation coefficient is proposed,and the energy efficiency separation coefficient is established.Solved optimization objective function;2.Considering the characteristics of the established objective function,the differential evolution algorithm is improved: firstly,the chaotic sequence is embedded in the improved algorithm to generate the initial population and enhance the population diversity;secondly,according to the different performance requirements of the mutation strategy at different stages of evolution,it is proposed Based on the double mutation strategy method of DE/current-to-pbest/1 and DE/rand/1;finally,use different parameter adaptive methods to set the F,CR and NP values,and finally,the complexity of the proposed LCTADE algorithm is analyzed and compared with other algorithms on CEC2017,and the LCTADE algorithm is used to simulate and verify the optimization calculation model of the content of each component at all levels based on the energy efficiency separation coefficient;3.The proposed improved algorithm LCTADE is further improved,and the covariance matrix and the Cauchy perturbation framework are added,and the obtained CC-LCTADE and the optimization model of the calculation of the content of each component at all levels based on the energy efficiency separation coefficient are simulated and verified.The function test of the CC-LCTADE method proposed in this paper for CEC2017 is compared with the algorithms before the framework is not added,which shows the feasibility of the proposed simple framework;The results of the optimization models for the calculation of the content of each component at all levels are compared and verified,which shows the effectiveness of the CC framework method proposed in this paper. |
