Investigation of rolling bearing fault diagnosis based on scale-based concurrent matrix

Based on the fact that rolling bearing vibration signal's three-dimensional(3-D) graphics and two-dimensional(2-D) graphics contain different fault information,the texture feature vectors were extracted from different scale-based concurrent matrixes which were received from 2-D wavelet translation.The gray degree association was employed to express these texture feature space geometry similarity.The method was used to analyze different bearing defects' real test vibration data.The result shows that this means can get high pattern classification accuracy,but it will decrease with growing malfunction size because of influences of rolling bearing elements.It's also found that the normalization of texture feature vector is not reasonable to some diagnosis ways.