关键词: 支持向量数据描述；经验模式分解；单值分类；故障诊断

Abstract:

Aiming at the problem of multidimensional samples which classified by support vector data description(SVDD) might lead to unsatisfactory results,a novel method based on empirical mode decomposition and SVDD was proposed,and it was applied to fault diagnosis for rolling bearings.The results show that the presented method is efficient to extract the fault feature,reduce the dimension of the signals and improve the veracity of one-class classification in intelligent diagnosis significantly.

Key words: support vector data description;empirical mode decomposition(EMD);one-class classification;fault diagnosis