摘要
提出了一种基于小波神经网络的快速、有效的电站锅炉受热面污染部位诊断的方法.采用额定工况下不同受热面出口烟温为特征参数,建立了小波神经网络污染部位诊断模型.测试结果表明,此模型可以快速、有效地诊断锅炉受热面的污染情况.
The paper proposes a new method of utility boiler location diagnosis on the basis of wavelet neural networks,which sets up a wavelet neural networks based diagnosis model for pollution location,using the gas temperature of different heating surfaces exits as feature parameter.It is indicated that this model can effectively diagnose the pollution location of heating surfaces of utility boilers by result of simulating test.
出处
《东北师大学报（自然科学版）》
CAS
CSCD
北大核心
2005年第1期28-31,共4页
Journal of Northeast Normal University(Natural Science Edition)
基金
教育部重点项目(02090)
关键词
小波
神经网络
锅炉
wavelet
neural network
boiler
