基于神经网络的电除尘器效率在线确定方法

影响电除尘器效率的因素很多，导致电除尘器的效率难以在线确定，基于该问题提出了一种用神经网络构建电除尘器效率模型的新方法．在此神经网络模型中只需要输入锅炉蒸发量、处理烟气量、灰分、粉尘粒径和粉尘比电阻等运行参数，即可实现电除尘器效率的在线测定。仿真表明，该神经网络模型具有良好的逼近实际系统的效果，为电除尘器系统的进一步建模和优化控制提供了参考。

A Method for the On-line Determination of the Efficiency of a Neural Network-based Electrostatic Precipitator

There exist numerous factors, which can affect the efficiency of an electrostatic precipitator. This also makes it difficult to conduct an on-line determination of the precipitator efficiency. In view of the above the authors have proposed a new method for setting up a model of electrostatic precipitator efficiency with the help of a neural network. In this kind of neural network model it is only necessary to input such operating parameters as boiler steam output, flue gas flow to be processed, ash, dust particle diameter and dust specific resistance, etc and one can readily realize the on-line determination of the electrostatic precipitator efficiency. The results of a simulation indicate that this neural network-based model has a fair effectiveness approximating to an actual system, thus providing a useful reference for the further modeling and optimized control of an electrostatic precipitator system.