摘要
对高阶统计量用于机械故障特征提取进行了研究.首先利用Hilbert变换构造原始信号的解析信号,求取信号的包络,然后计算包络信号的高阶统计量.研究表明,用高阶统计量提取信号特征,可以容易地将正常齿轮信号和齿轮裂纹、断齿的信号分离.
The application of higher order statistics extracting of
mechanical falut features is studied. The analytical signals are acquired by means of Hilbert
transformation of the original singals. The enveloped signals are calculated from the analytical
signals. The higher order cumulants and moments of the enveloped signals are estimated. The
results of the research show that normal gear signals, cracked gear signals and broken gear
signals can be easily separated by using higher order statistics as the signal features.
出处
《华中理工大学学报》
CSCD
北大核心
1999年第3期6-8,共3页
Journal of Huazhong University of Science and Technology
基金
国家"九.五"攀登计划预选资助