摘要
该文利用神经网络聚类学习方法对机械故障的故障模式进行识别分类，通过实验研究，证明该方法作为一种新的自适应模式识别技术，比传统的聚类方法和基于ＢＰ神经网络故障模式识别方法具有较高的模式分类能力。
Abstract The type grouping nerval network learning method is used to discriminate and classify different modes of machinery faults.Experimental studies show that this method used as a self adapting mode of discriminating technique has a better mode classification capability as compared to conventional type groping methods or fault mode discriminating methods based on BP nerval networks.Fig 1,tables 6 and refs 9
出处
《发电设备》
1999年第2期27-30,39,共5页
Power Equipment
