Development Of Coal Washing Ash Reducer And Optimization Analysis Of Mixing Parameters

Coal sample cleaning is to remove the chloride ion introduced in the flotation process,which is an indispensable step in the study of accurate measurement of chlorine content in coal sample and reducing the harm of coal combustion.A large number of chlorine-containing substances discharged from coal combustion will cause serious corrosion to the pipeline,furnace body and other equipment,and pose a great threat to people’s life and health.At present,the coal sample cleaning is still in the manual stage,with high labor intensity and strong repeatability,and the manual cleaning relies on experience to judge the chloride ion removal effect,which can not form an effective evaluation standard,strong randomness and low efficiency.With the development of industrial technology,automation technology is gradually applied to all walks of life.If the automation of coal sample cleaning process can be realized,it will have a significant impact on work efficiency and industry development.Therefore,in view of the above problems,the following research has been carried out.(1)The main structure of coal sample cleaning equipment is determined by the selection of mixing mode and blade;The inner layer is the filter screen wall and the double-layer stirring tank structure is adopted to speed up the drainage speed and improve the cleaning efficiency;By analyzing the cleaning process,determining the relevant hardware model,using PLC to control the components,the automation of coal sample cleaning equipment is realized.(2)Aiming at the problem of coal sample cleaning efficiency not reaching the standard,this paper analyzes from the perspective of improving mixing efficiency:suspension uniformity and mixing time are the main factors affecting mixing efficiency,and takes them as optimization objectives.Through analyzing the parameters affecting suspension uniformity and mixing time,three main parameters are determined to optimize the objectives,including speed,blade diameter and blade height from the bottom.64 groups of experiments were designed by setting the appropriate interval of each parameter,and the solid-liquid suspension process of stirred tank was simulated by numerical simulation.On the basis of the simulation data,the influence of single parameter was analyzed,and the control group was set up to explore the influence of speed,blade diameter and height from the bottom on the suspension uniformity and mixing time respectively.The results show that the influence trends of the three parameters on the suspension uniformity and mixing time are different.When one of the three parameters is changed,the suspension uniformity and mixing time will change obviously.Only through a single variable analysis can only get the trend,can not be combined with each other to get the position of the optimal value,but also need to analyze three variables at the same time.(3)The model between variable and target is established by using support vector machine regression algorithm,and compared with BP neural network,the superiority of support vector machine in small sample modeling is verified;On the basis of ensuring the high correlation of support vector machine prediction model,data generalization is carried out to ensure the accuracy and reliability of data fitting of explicit equation;NSGA-II algorithm is used to solve the optimization problem of the explicit equation of the prediction model.The results show that the mixing effect is the best when the speed is 261.49 rpm,the blade diameter is 200 mm,and the blade height from the bottom is75.03 mm.Finally,the efficiency of the solution is verified by simulation and experiment,and the parameter optimization of coal sample cleaning equipment is realized.