摘要
提出了一种采用小波变换进行特征提取、支持向量机进行模式分类的多传感器信息融合诊断方法。该方法首先对多传感器的信息进行加权初级融合,接着利用小波变换的时频局部特性和多尺度、多分辨特性对传感器测量信号进行特征提取,最后利用支持向量机进行分类实现信息的特征级融合和分类。将其应用于某转子实验台的故障诊断中,取得了令人满意的结果。
A novel fault diagnosis method based on multi-sensor irfformation fusion is presented. First,sensors' information is averagely fused before feature extraction. Then, signals' characteristic features are extracted by means of wavelet transform. Finally, supprt vector machines are adopted to realize character - level fusion and patter recognition. Samples of some kind of rotor platform's fault diagnosis are tested,the test results prove this method is effective and commendable.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2005年第9期1665-1668,共4页
Systems Engineering and Electronics
关键词
支持向量机
小波变换
信息融合
特征提取
故障诊断
support vector machines
wavelet transform
information fusion
feature extraction
fault diagnosis