Research On Safe Control In The Process Of Hydrometallurgy Thickening Based On Knowledge And Data

How to detect the failure before it occurs and make adjustments in time to achieve safe and stable operation of the equipment is process safety control.Hydrometallurgy is a metallurgical method for treating complex ore and low grade ore.Thickening process is an indispensable process in hydrometallurgical process.It can separate solid and liquid efficiently by thickening machine.In the actual production process,the operating environment of bushy machine is bad and there are many influencing factors,which can easily cause the failure of "pressure rake"and "running muddy".Once the fault occurs,the light production stops,the waste of raw materials,and the heavy will cause serious production accidents,threatening the safety of staff.Therefore,it is of great significance to study the safety control of thickening process.Firstly,the key variables in the process of thickening are extracted from the working principle of the thickener,and the coupling relationship between the variables is sorted out.Based on the typical fault state of the thickener,the relationship between the abnormal state and each monitoring variable is analyzed,and the key point of safety control is pointed out,which lays a foundation for establishing reasonable abnormal condition recognition and safety control model.Secondly,it summarizes the historical experience and knowledge of abnormal detection in the thick washing process,and at the same time,it uses the decision tree algorithm to mine effective abnormal detection rules from the historical abnormal data,so as to build the rule base of abnormal condition detection in the thickening process.The method of rule verification based on accuracy and coverage is proposed to screen the rule according to the characteristics of abnormal condition data.Simulation analysis proves the validity and comprehensiveness of the extracted anomaly detection rules.Finally,a self-healing controller for thickening process based on case-based reasoning is designed.In view of the characteristics of this problem and the defects of the traditional case reuse methods,the optimized recombination reuse strategy is proposed for the situation that only the bottom flow concentration anomaly occurs or only the overflow turbidity anomaly occurs,and the multi-case fusion reuse strategy is proposed for the situation that both anomalies occur simultaneously.The simulation results show that the self-healing controller based on case-based reasoning can control various abnormal conditions and achieve good safety control effect.