粗糙集属性约简算法研究

Attribute Reduction Algorithm Rough Set

由于列车滚动轴承的振动信号一般表现为非平稳性,传统的故障诊断方法效果不佳,基于粗糙集的故障诊断是近年来故障诊断的研究方向之一。属性约简是粗糙集的重点研究方向之一,文章通过对各种属性约简算法的比较得到合适约简算法并将其应用到故障诊断中。

bThe traditional fault diagnosis method is not effective because of the vibration signal of the rolling bearing of the train is stable. Fault diagnosis based on rough set is one of the research directions in recent years. Attribute reduction is one of the key points in the research of rough set. In this paper, a suitable reduction algorithm is obtained by comparing several attribute reduction algorithms, and then applied it to fault diagnosis.