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.
关键词
大滞后/串级控制/前馈控制/BP神经网络/遗传算法/大数据
Key words
large lag/cascade control/feed-forward control/BP neural network/genetic algorithm/big data
维普
万方数据