摘要
提出了一种基于经验模态分解 (EMD) 和包络谱分析的轴承故障诊断的新方法.EMD 是把时间序列信号,分解成不同特征时间尺度的固有模态函数(IMF),具有自适应的分析能力,然后通过选取表征轴承故障的 IMF分量进行包络谱分析,就可提取轴承故障信号的特征.轴承故障实验信号的研究结果表明:该方法能有效地识别轴承故障.
A novel method tofault diagnosis of bearing based on EMD and envelope spectrum is presented. EMD method is self-adaptive to non-stationary andnon-linearsignal. The methodology developed in this paper decomposes the original times series data in intrinsic oscillation modes, using the empirical mode decomposition. Then the envelope spectrum is applied to the selected intrinsic mode function which stands for the bearing faults. The basic principle is introduced in de- tail. The EMD is applied in the research of the faults diagnosis of the bearing. The experimental results show that this method based on EMD and envelope spectrum can effectively diagnosis the faults of bearing.
出处
《河北工业大学学报》
CAS
2005年第1期11-15,共5页
Journal of Hebei University of Technology
基金
国家自然科学基金资助项目(50375157)
关键词
故障诊断
轴承
包络谱分析
经验模态分解
信号处理
faultsdiagnosis
bearing
envelope spectrum analysis
empirical mode decomposition
signalprocessing
