Research On Predictive Control Of Dissolved Oxygen In The Pretreatment Process Of Biological Oxidation

The biological oxidation pretreatment process is one of the key processes of biological oxidation metallurgy,which is related to the final gold extraction rate.The amount of dissolved oxygen as a key factor affecting the oxidation rate in the biological oxidation pretreatment process directly affects the activity of bacteria and the oxidation rate of refractory ore metallurgy,which directly affects the final extraction rate of gold.Precise predictive control of the amount of dissolved oxygen in the oxidation pretreatment process can ensure the growth and basic metabolism of the bacteria,and can also maintain a high biological oxidation rate,thereby obtaining a high gold extraction rate.It plays an important role in the entire biological oxidation pretreatment process.In addition,due to the inability to accurately predict and control the amount of dissolved oxygen,most of the current process sites adopt the principle of "prefer more than less" for the oxygen charge of the oxidation tank,which brings about the problem of low oxygen utilization rate and serious waste of resources.Combined with the above problems,in order to ensure the growth and basic activity of bacteria and make the biological oxidation process normal,it is urgent to accurately predict and control the dissolved oxygen concentration in the process of ore biological oxidation,so as to achieve energy saving and consumption reduction while ensuring the oxidation efficiency.The main arrangement of this paper is as follows:Firstly,the theoretical basis for the later research is to understand the process of biological oxidation pretreatment,analyze the oxygen consumption mechanism in the process of biological oxidation pretreatment,and the influence of dissolved oxygen concentration on redox potential and biological oxidation rate in the biological oxidation process.Secondly,in order to improve the utilization rate of oxygen and achieve accurate prediction of dissolved oxygen,a prediction model of dissolved oxygen based on least squares support vector machine was established.The least squares support vector machine is selected as the prediction model,and the whale algorithm is used to optimize the kernel function width and penalty factor of the least squares support vector machine,and the single least squares support vector machine model is compared with the least squares support vector machine model of particle swarm optimization.The simulation results show that the method can achieve better control of dissolved oxygen.The accuracy of the prediction.It provides technical support for the control scheme of dissolved oxygen.Thirdly,on the basis of the above-mentioned predictive model,a model predictive control method is adopted to achieve precise control of the amount of dissolved oxygen.In this paper,the ant colony optimization algorithm is added to the rolling optimization part of the model predictive control to optimize the performance indicators of the objective function,and realize the precise control of the dissolved oxygen.The simulation experiment results show that this method can effectively realize the predictive control of the dissolved oxygen amount,so as to realize the oxygen supply on demand,and achieve the purpose of energy saving and consumption reduction.