摘要
该文介绍了自组织特征映射人工神经网络模型在电厂系统故障诊断中的应用。通过与常规的ＢＰ网络用于汽轮机故障诊断中的应用的比较，得出：自组织模型具有自学习功能，运算速度快，类型识别能力强的优点，应用前景广阔。
The paper describes the application of artificial nervous network models with self organizing characteristic reflection in fault diagnosis of power plant systems. By comparison with conventional BP networks used for fault diagnosis of steam turbines, the following conclusion is drawn: self organizing models possess self studying capability, are quick in performing calculations and are strong in type discrimination. They have prospects of general application.
出处
《动力工程》
CSCD
1997年第2期7-11,共5页
Power Engineering
基金
国家攀登B计划资助项目
