基于IMF投影图像分析的滚动轴承故障诊断方法研究

Research of Fault Diagnosis Method of Rolling Bearing based on Projection Image Analysis of Intrinsic Mode Function

提出了一种基于本征模式分量投影图像分析的滚动轴承故障诊断方法,实现了滚动轴承故障的状态识别与程度识别,首先,依托经验模式分解方法(Empirical Mode Decomposition,EMD)对轴承故障信号进行分析,获取故障本征模式分量(Intrinsic Mode Function,IMF);其次,构建各个本征模式分量的时频三维灰度投影图像,引入基于灰度共生矩阵(Gray Level Co-occurrence Matrix,GLCM)的纹理特征对三维投影图像进行分析;最后,通过主成分分析进一步压缩特征维度,并结合支持向量机(Support Vector Machine,SVM)实现了滚动轴承的故障诊断。研究从图像特征角度实现故障诊断,丰富了现有振动信号故障特征获取方法,实现了滚动轴承故障的状态识别与程度识别。

A projection image analysis method for the fault diagnosis of rolling bearing based on Intrinsic Mode Function （IMF） is proposed, the status recognition and the degree of recognition of the roiling bearing fault is realized. The main contents are as follow. Firstly, the Empirical Mode Decomposition method （EMD） is used to obtain IMF. Secondly, the time - frequency three - dimensional gray - scale projection image of each IMF is established. The texture feature of Gray Level Co - occurrence Matrix （GLCM） is also introduced to analyze the three - dimensional projection image. Finally, the feature dimension is compressed and combined based on the principal component analysis. The Support Vector Machine （SVM） is used to realize the fault diagnosis of rolling bearing. Both fault diagnosis and degree identification of rolling bearing is realized through a perspective of image characteristics. A new method based on projection image of characteristics calculation in vibration signal is given in this study.