Temperature Coordinated Control Of Intensive Multistage Oxidation Tank In Alpine Region

In high and cold regions,gale and snow are easy to occur.In the process of bio-oxidation metallurgy,temperature is an important condition for the survival of bacteria in oxidation tank.The microorganisms in the oxidation tank grow logarithmically in a suitable temperature range,and have high reproductive rate and high activity.If the temperature is not in this range,the growth curve of microorganisms is nonlinear,even lose activity and stop growing.So it is very important to ensure that bacteria grow in suitable temperature range.Oxidation tank is the key part of microbial growth,but the temperature control in the oxidation tank is more intricate,particularly the accurate command of temperature is more difficult.Therefore,in order to solve the problem that the temperature regulation of the multi-stage oxidation tank of biological oxidation pretreatment is quite different in alpine region,the research contents of this paper are as follows:In this paper,combined with the on-site technology,taking the dense multi-stage oxidation tank in alpine region as the research object,the temperature synergistic control of the dense multi-stage oxidation tank is studied.Firstly,the PSO-optimized PID neural network control method is used to ensure the accuracy of temperature control in the oxidation tank for the electric control valve of the single oxidation tank heat exchanger tube.On this basis,the speed dynamic compensation cooperative control method based on maximum error is adopted for the dense multi-stage oxidation tank system,and the speed dynamic compensation cooperative control model is established.The simulation results show that the method can accurately control the temperature of the multi-stage oxidation tank and meet the technological requirements of the special weather conditions in the alpine region.In order to further verify the feasibility and accuracy of the method proposed in this paper,the existing equipment of Siemens Laboratory is used to build a multi-stage oxidation tank temperature coordination control system data monitoring platform.Through the construction of the upper monitoring interface,the test data can be obtained and recorded.In the SMPT-1000 simulation experiment equipment of Siemens Laboratory,the PID neural network control and the PSO optimized PID neural network control are used respectively for the heat exchanger tube control valve.The feasibility and superiority of the method adopted in this paper are verified.The research results provide new ideas and methods for precise control of bioleaching process in alpine region.