数据采集与处理2013，Vol.28Issue(1)：34-40,7.
多重分形的振动信号故障特征提取方法
Fault Feature Extraction Method of Vibration Signals Based on Multi-Fractal
摘要
Abstract
Considering fault feature extraction difficulty to the non-linear vibration signals, a feature extraction method is proposed based on the general dimension mean (MeanD,) and the parameters of singular spectrum (△α and △f). Firstly, characteristics of multi-fractal for the vibration signals are analyzed, then MeanDq, △α and △f are calculated, respectively. Subsequently, they are used as fault characteristic values. Finally, fault feature extraction method is applied to fault detection for rolling bearing. The result shows that the state of the vibration signals for rolling bearing can be effectively identified by MeanDq,△α and △f together. Besides, MeanDq, and △α have a stronger sensibility than △f. Apparently, the example proves that the integrated method is feasible.关键词
振动信号/广义维数均值/奇异谱/滚动轴承/故障特征提取/多重分形Key words
vibration signal/ general dimensionsion mean/ singular spectrum/ rolling bearing/ fault feature extraction/ multi-fractal分类
机械制造引用本文复制引用
李兆飞,柴毅,李华锋..多重分形的振动信号故障特征提取方法[J].数据采集与处理,2013,28(1):34-40,7.基金项目
国家自然科学基金(60974090)资助项目 （60974090）
教育部博士点基金(102063720090013)资助项目 （102063720090013）
中央高校基本科研业务费专项资金(CDJXS10172205)资助项目. （CDJXS10172205）
