摘要
在定义瞬时频率具有物理意义的内禀尺度分量(Intrinsic scale component,ISC)的基础上,提出了一种新的自适应时频分析方法——局部特征尺度分解(Local charac-teristic-scale decomposition,LCD),该方法可以自适应地将一个复杂信号分解为若干个ISC分量之和.分别采用LCD方法和经验模态分解(Empirical mode decomposition,EMD)方法对仿真信号进行了分析,分析结果表明:2种方法都可以有效地对信号进行分解,但LCD方法在计算效率和抑制端点效应等方面要优于EMD方法.此外,还将LCD方法应用于滚动轴承故障诊断,实验信号的分析结果进一步表明了该方法的有效性.
Based on the definition of intrinsic scale component （ISC）, a new self-adaptive time-frequency analysis method,i, e. , local characteristic-scale decomposition （LCD）, was proposed. By using LCD, a complicated signal can be decomposed into a number of ISC,whose instantaneous frequencies have physical meaning. The processed simulation signal was analyzed by LCD and empirical mode decomposition （EMD）. The analysis results have demonstrated the validity of the two decomposition methods. Moreover, LCD is superior to EMD in computational efficiency and restriction of end effects. In addition, LCD is also applied to fault diagnosis for roller bearing and the analysis results from the actual fault vibration signal have fur- ther proved the effectiveness of LCD.
出处
《湖南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2012年第6期35-39,共5页
Journal of Hunan University:Natural Sciences
基金
国家自然科学基金资助项目(51075131
51175158)
湖南省自然科学基金资助项目(11jj2026)
中央高校基本科研业务费专项基金资助项目
湖南大学汽车车身先进设计制造国家重点实验室自主课题资助项目(60870002)
关键词
故障诊断
局部特征尺度分解
内禀尺度分量
滚动轴承
fault diagnosis
local characteristic-scale decomposition
intrinsic scale component
roller bearings
