摘要
排列熵作为一种统计测度,是通过相空间重构来衡量时间序列复杂度的一个参数。为研究机械设备非平稳信号的非线性动力学特征,将排列熵引入机械设备故障诊断,研究了不同工作状态下滚动轴承振动信号的排列熵和嵌入维数与时间延迟对计算机械振动信号排列熵的影响,观察设备状态变化及振动冲击对排列熵的影响并对其进行了分析。结果表明:排列熵可以有效地检测出机械设备状态的变化,可以作为检测机械设备状态变化的一个参数。
To take into account non-linear behavior of non-stationary signals, which may characterize working status of machine systems, the utility of permutation entropy for machine condition monitoring and health diagnosis is investigated. As a statistical measure, the permutation entropy describes complexity of the time series through phase space reconstruction , thus can be serve as a parameter to detect change of machine condition. The effect of embedded dimension and time delay on permutation entropy is studied. Experimental results on bearing vibration analysis confirm that the permutation entropy provides an effective measure for monitoring the working status of machine systems.
出处
《振动与冲击》
EI
CSCD
北大核心
2007年第12期131-134,共4页
Journal of Vibration and Shock
基金
国家自然科学基金支持项目(50575216)
安徽省教育厅自然科学基金支持项目(2006KJ275B)
关键词
排列熵
非线性
检测
信号突变
故障诊断
permutation entropy
nonlinearity
detection
signal distortion
faults diagnosis
