噪声与振动控制2016，Vol.36Issue(4)：169-173,197,6.DOI:10.3969/j.issn.1006-1335.2016.04.036
形态分量分析和谱峭度在轴承故障诊断中的应用
Applications of Morphological Component Analysis and Fast Spectral Kurtosis in Rolling Bearing Fault Diagnosis
摘要
Abstract
When a rolling bearing is faulted, its vibration signal is usually composed of many components generated by different vibration sources. These components are dominated by the harmonic components induced by the natural vibration of the bearing, the impulsive components resulted from fitting or crack faults and some other perturbation components. It is helpful to separate these components from the original vibration signals effectively for fault diagnosis of the rolling bearing. In this paper, a new fault diagnosis method is proposed based on morphological component analysis (MCA) and fast spectral kurtosis (FSK). Firstly, the impulsive components and harmonic components are separated from the vibration signals of the faulted rolling bearing by using MCA. Then, the harmonic components are analyzed by using FSK filtering analysis. Finally, the signals obtained from the previous steps are analyzed by using Hilbert envelope demodulation analysis. The fault diagnosis of a rolling bearing is carried out according to the envelope spectrum method. The feasibility and effectiveness of this method are verified by the experiments.关键词
振动与波/滚动轴承/故障诊断/形态分量分析/谱峭度Key words
vibration and wave/rolling bearing/fault diagnosis/morphological component analysis/fast spectral kurtosis分类
机械制造引用本文复制引用
马朝永,张学飞,胥永刚..形态分量分析和谱峭度在轴承故障诊断中的应用[J].噪声与振动控制,2016,36(4):169-173,197,6.基金项目
国家自然科学基金资助项目(51375020)；北京市教委科研计划资助项目 （51375020）
