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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.
Aiming at the problem of composite fault diagnosis of unbalanced rotor faults and weak damage of rolling bearings, a fault diagnosis method based on empirical mode decomposition is proposed to separate the coupling characteristics of composite fault and the characteristic of bearing damage fault signal. Firstly, The decomposition of the composite signal into several intrinsic mode functions (IMFs) through empirical mode decomposition. Then, by calculating the correlation coefficients between each IMF and the original composite signal, the main components containing the fault characteristic information are removed to remove the false components. Finally, The main components of the low-frequency components of the spectrum analysis proposed rotor fault characteristics, the main components of the high-frequency components of the Hilbert envelope demodulation to extract the modulation fault characteristics, namely bearing damage fault characteristics. Simulation and experimental results show that the effectiveness of the method And practicality.