轴承退化状态的LCD-Hilbert相对谱熵识别

BEARING DEGRADATION STATE IDENTIFICATION OF LCD-HILBERT RELATIVE SPECTRUM ENTROPY

为有效地对轴承退化状态进行识别,结合LCD分解和Hilbert变换定义了LCD-Hilbert时频谱,同时利用相对熵可以较好表征振动信号概率分布差异的特性,提出基于LCD-Hilbert相对谱熵的轴承退化特征提取方法。通过仿真信号对定义的LCD-Hilbert相对频率能谱熵、相对瞬时能谱熵和相对奇异谱熵的合理性和有效性进行了验证。将这3个特征指标组成退化特征,对实测轴承内圈和外圈故障模式下的不同程度故障振动信号进行了进一步分析,并通过支持向量机对轴承退化状态进行了识别,结果验证了所提方法的有效性。

In order to better identification the degradation state of bearing,a degradation state feature extraction method for bearing named LCD-Hilbert relative spectrum entropy is proposed based on relative entropy for characterizing the probability distribution difference among different signals.The analysis results of simulation signal demonstrate the availability and relationality of the proposed LCD-Hilbert relative frequency energy spectrum entropy(LHFE),relative instantaneous energy spectrum entropy(LHIE) and relative singular spectrum entropy(LHSE) used as degradation feature.The degradation feature vector is composed of the three features.The practical vibration of bearing with inner race fault and outer race fault which in different degradation state are analyzed,and the support vector machine is further used to identification degradation state and the results demonstrate the ability of the proposed method.