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静电除尘高压电源的优化控制系统
引用本文:李志军,甄美娜.静电除尘高压电源的优化控制系统[J].电气传动,2012,42(2):65-68.
作者姓名:李志军  甄美娜
作者单位:河北工业大学控制科学与工程学院,天津,300130
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。

关 键 词:静电除尘器  供电电压  优化控制  遗传算法  神经网络

Optimization Control System of Electrostatic Precipitation High-voltage Power Supplies
LI Zhi-jun , ZHEN Mei-na.Optimization Control System of Electrostatic Precipitation High-voltage Power Supplies[J].Electric Drive,2012,42(2):65-68.
Authors:LI Zhi-jun  ZHEN Mei-na
Affiliation:(School of Control Science and Engineering,Hebei University of Technology,Tianjin 300130,China)
Abstract: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.
Keywords:electrostatic precipitator  the power supply voltage  optimized control  genetic algorithm  neural network
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