Fault diagnosis of rolling element bearing based on morphological filter and grey incidence
Fault diagnosis of rolling element bearing based on morphological filter and grey incidence
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发表时间：
2009
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通讯作者：
Zhan Zhi-gang
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作者：
Zhan Zhi-gang
针对滚动轴承故障诊断中噪声背景强、样本量少的问题，提出了一种基于形态学滤波和灰色关联法的滚动轴承故障诊断方法。通过形态学差分滤波器可以不考虑振动信号频谱来提取故障特征。灰色关联法在小样本分类中具有良好的性能，可用于滚动轴承故障模式的识别。对故障信号进行形态学滤波器滤波，将提取的特征频率的酉幅值作为特征向量，利用灰度关联法对故障模式进行分类。未知模式与标准故障模式之间的灰色关联度。实验结果表明了该方法的有效性。
Considering the strong noise background and lack of sample in fault diagnosis of rolling element bearing,a rolling element bearing fault diagnosis method was proposed based on morphological filter and grey incidence.Fault characteristic can be extracted by morphological difference filter without considering frequency spectrum of vibration signal.The method of grey incidence has good performance in small-sample classification and can be used in recognition of rolling element bearing fault pattern.The fault signal was filtered by morphological filter,the unitary magnitude of characteristic frequency extracted was considered as characteristic vector and then the fault pattern was classified by use of grey incidence between unknown pattern and standard fault pattern.Experiment results show the effectiveness of the method.