Research On Temperature Predictive Control In Biological Oxidation Pretreatment

Bio-oxidative gold extraction pretreatment uses bacteria to oxidize the difficult-to-treat gold ore encapsulating the target element,thereby exposing the target mineral.It can be seen that effective control of the internal temperature of the oxidation tank is a prerequisite to ensure its high oxidation rate,especially in cold or high altitude places,where the air pressure is low,the air density is small,and the temperature difference between day and night is large.As a result,the overall heat loss of the oxidation tank is heavy,and the oxidation reaction process in the tank is slowed down,which seriously affects the production efficiency and resource utilization rate of the biological oxidation pretreatment process.Therefore,in the cold and high altitude areas,the temperature in the oxidation tank changes drastically resulting in the low oxidation rate of the biological oxidation pretreatment,and the heat transfer in the oxidation tank,the temperature change and the mechanism of the effect of the temperature on the biological oxidation pretreatment process are in-depth Analyzed,further research on the temperature control method in the oxidation tank is of great significance to the pretreatment process of bio-oxidation gold extraction in cold and high altitude areas.First,a brief introduction is made to the entire process flow of the biological oxidation pretreatment process,and in view of the serious heat loss caused by external environmental factors,through the comprehensive application of knowledge of heat transfer and fluid dynamics,the oxidation tank The heat transfer in the air and its reasons have been analyzed in detail to lay the foundation for the later work.Secondly,in order to reduce the prediction error caused by data abnormality,extract the historical data of oxidation tank operation and process the missing and abnormal values in the data,and to eliminate the dimensional difference,the data sample needs to be normalized,that is,the sample data Map to between.Finally,in order to solve the temperature control problem in the oxidation tank and increase the oxidation rate,this article first introduces the rise and principle of the generalized regression neural network and the fruit fly optimization algorithm in detail,and selects the generalized regression neural network to construct the prediction model and choose to improve The Drosophila optimization algorithm optimizes the parameter smoothing factor of the generalized regression neural network to improve the accuracy of the prediction model and ensure the accuracy of the prediction effect.And the accuracy of the constructed prediction model is verified by experimental simulation.Finally,the proposed algorithm will construct a predictive model for the temperature of the oxidation tank,and an improved artificial bee colony algorithm will be used to optimize the target performance function.The predictive control method is used to predict and control the oxidation tank to achieve real-time control of the temperature in the oxidation tank.The simulation results show that the predictive control method proposed in this paper has a better control effect on the temperature in the oxidation tank.