基于BP神经网络的电站锅炉污染诊断  

Diagnosis of Power Plant Boiler Contamination by BP Neuronal Network

作　　者：李树权[1] 史延馥[2] 王全胜[1] 

机构地区：[1]河北电力职工大学,河北保定071051 [2]东北电力学院,吉林吉林132012

出　　处：《河北电力技术》2002年第3期36-38,共3页Hebei Electric Power

摘　　要：文章基于神经网络理论 ,提出了可以对电站锅炉污染受热面诊断的方法。根据额定工况下不同受热面进出口烟温差 ,建立了基于BP网络的污染诊断模型。此模型可以有效地诊断无法由常规测量仪表监测的锅炉污染情况 。The paper proposes a diagnosis method of power plant boiler contamination surfaces by neuronal network theory.A contamination diagnosis model is built according to the difference of inlet and outlet gas temperatures of different surfaces in normal condition.It can effectively diagnosis the boiler contamination conditions which cannot done by normal measurement instruments.It can be the theoretical reliament of effective boiler ash removal scheme.

关 键 词：BP神经网络 电站 锅炉 污染诊断 

分 类 号：TM621.2[电气工程—电力系统及自动化] TP183[自动化与计算机技术—控制理论与控制工程]