摘要
针对静电除尘器的粉尘排放浓度和电能消耗等问题,以及最佳工作电压会随着工况的变化而变化,进而提出了一种提高和改善电除尘器性能的整体优化控制方法。用全监督RBF神经网络建立电除尘器出口浓度-供电电压模型,最小二乘法辨识电功率模型,采用遗传算法GA寻找最佳工作2次电压的设定值。结果证明,该优化控制方法,在保证除尘效率的同时又兼顾了节能问题。
Aiming at the dust emission concentrations of the electric factory electrostatic precipitator and electricity consumption etc,and the best working voltage will changes with working condition,the overall optimization control method was forward which can improve and change the electrostatic precipitator performance. Using RBF neural network, precipitator export degrees-power supply voltage model, least-square identification electric power model were built, a genetic algorithm was adopted to obtain optimal working voltage. Results show that the proposed optimization control method, ensure the efficiency of dust,and both energy saving problems.
出处
《电气传动》
北大核心
2012年第2期65-68,共4页
Electric Drive
关键词
静电除尘器
供电电压
优化控制
遗传算法
神经网络
electrostatic precipitator
the power supply voltage
optimized control
genetic algorithm
neural network
