Application of BP Neural Network in Acid Gas Emission Control of Waste Incineration Power Plant
For most waste incineration power plants that use semi dry methods,the main means of controlling the concentration of acidic gas emissions is to regulate the lime slurry flow rate at the inlet of the deacidification tower.Traditional PID control uses measured data from CEMS as feedback signal to regulate the lime slurry flow,but the distance from the inlet of the deacidification tower to the sampling point of the chimney flue gas is far,the reaction time is long,and the control effect is poor.To this end,the BP artificial neural network genetic algorithm is introduced to train the artificial neural network using a large amount of process data accumulated under manual control mode,in order to replace manual control.
large lagcascade controlfeed-forward controlBP neural networkgenetic algorithmbig data
万方数据
维普
