摘要
在深入研究ＡＰＴ─２神经网络结构的基础上，提出了一种基于神经网络的自适应故障模式分类方法，并应用在轴承故障诊断中，结果表明：该方法对轴承故障模式具有自学习、快速稳定的识别能力。
The adaptive failure pattern classificationmethod based on neural network is presented through the study of ART-2 neural networks and it is put into application on bearing diagnosis. The results indicate that this method has recognizing abilities of fast, stable and self-adaptive response for bearing fault pattern.
出处
《北京科技大学学报》
EI
CAS
CSCD
北大核心
1995年第3期264-269,共6页
Journal of University of Science and Technology Beijing
基金
国家教育博士基金
关键词
故障诊断
神经网络
轴承
模式识别
failure diagnosis, neural networks, bearing, pattern recognition, ART-2 networks
