Composite fault diagnosis method based on empirical mode decomposition
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摘要: 针对转子不平衡故障和滚动轴承微弱损伤性故障的复合故障诊断问题,提出了一种基于经验模式分解的故障诊断方法,进行复合故障的耦合特征分离和轴承损伤性故障信号特征提取研究.该方法首先通过经验模式分解将复合信号分解为若干个本征模函数(intrinsic mode function,IMF);然后通过计算各IMF与原始复合信号的相关系数确定包含故障特征信息的主要成分,除去虚假分量;最后针对主要成分中的低频成分进行频谱分析提出转子故障特征,针对主要成分中的高频成分进行Hilbert包络解调提取调制故障特征,即轴承损伤性故障特征.仿真及实验结果表明该方法的有效性和实用性.Abstract: Aimed at a composite fault of rotor failure and weak roller bearing fault, a fault diagnosis method based on empirical mode decomposition (EMD) was proposed to separate the coupling features of the composite fault and to extract the fault feature of the roller bearing. Signals were decomposed to obtain several intrinsic mode functions (IMF) by EMD. Main components are confirmed by calculating the correlation coefficient of every IMF and original composite signal, and false components were removed at the same time. Finally low-frequency rotor fault feature was extracted by FFT from the low-frequency component of main components, and high-frequency modulate feature of the roller bearing was extracted by Hilbert envelope demodulation from the high-frequency component of main components. Simulation and experiment analysis results indicate the validity and the practicability of the method proposed.
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