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.