基于EMD与功率谱分析的滚动轴承故障诊断方法研究

RESEARCH OF FAULT DIAGNOSIS OF ROLLING BEARINGS BASED ON EMD AND POWER SPECTRUM ANALYSIS METHOD

针对西部油田大型设备故障信号的非线性、非平稳特征,提出一种基于经验模态分解方法EMD(empiricalmode decomposition)和功率谱的分析方法。首先对滚动轴承振动信号进行经验模态分解,然后对分解后包含轴承故障特征信息的固有模态函数分量作功率谱分析,得到各分量的功率谱图,清晰直观显示出故障特征信号的功率谱,从混有背景信号和噪声的振动信号中提取轴承故障信息。由于EMD方法具有自适应特性,适宜于非线性、非平稳信号的分解,该方法应用于滚动轴承的故障振动信号分析中,结果表明,该方法能够突出滚动轴承振动信号的故障特征,从而提高滚动轴承故障诊断的准确性。

According to the non-stationary and non-linear characteristic of wiling bearing vibration signal, an analysis method based on empirical mode decomposition and power spectrum is put forward. Firstly, the original vibration signals are decomposed into a finite number of stationary intrinsic mode functions （IMFs） by EMD（empirical mode decomposition）. Then the IMFs relating to fault information are applied to power spectrum analysis. The result of the method is the power spectrum of relating IMFs, which can illustrate the characteristic of the signal clearly and extract the fault characteristic information easily. Since the EMD method is self-adaptive, it is applicable to non-linear and non-stationary signals. Applied example proves the effectiveness of the method.