基于BP神经网络电除尘效率模型研究  

Research of the Electrostatic Precipitator Efficiency Model Based on BP Neural Network Algorithm

作　　者：杜之正 

机构地区：[1]大唐临清热电有限公司,山东临清252600

出　　处：《东北电力技术》2014年第9期8-10,13,共4页Northeast Electric Power Technology

摘　　要：电除尘法已成为电厂烟气除尘的主要方法,但目前很难实现对电除尘效率的精确测量,综合分析影响电除尘效率的主要因素,并以BP神经网络结构为基础,建立除尘效率的BP神经网络模型。引进学习样本对此模型进行了仿真分析,通过比较实际系统和模型除尘效率曲线以及对模型误差的计算,验证了此模型的可行性。Electric dust removal method has become the main method of power plant flue gas dust removal. However, it is difficuh to aehiewve accurate measurement of the efficiency of electrostatic precipitator, a comprehensive analysis of the main factors affecting the efficiency of electrostatic preeipitalor is made. The electric dust removal efficiency model based on BP neural network algorithm is set up, intrndueing of learuing samples to earry out simulation analysis, By emnparing the actual system and dust collection efficiency curve model and calculation of the model error, feasibility of this mode is thus verufied.

关 键 词：电除尘 神经网络 模型 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]