针对运行的变速箱轴承难以采集振动信号进行状态监测与故障诊断的缺点, 采用红外热图像对变速箱轴承进行状态监测与故障诊断。利用红外热像仪采集变速箱两端轴承的红外热图像, 然后通过二维经验模态分解方法将红外热图像分解成本征模式函数, 对其处理后与主成分分析法相结合进行图像融合, 得到对比度增强后的图像。最后对原图像与增强后的图像进行特征参数提取, 并利用聚类分析对轴承不同状态进行分离。证明了红外热图像可以准确地诊断出轴承故障。

Considering that it is difficult to collect vibration signal of the running gearbox bearings for condition monitoring and fault diagnosis,we used infrared thermal image to carry out the jobs.Firstly,infrared thermal images of the two end bearings of the gearbox were collected by infrared thermography,and the infrared thermal image was decomposed into intrinsic mode function through bi-dimensional empirical mode decomposition.Then,the image was processed for image fusion with the principal component analysis method,and the image with enhanced contrast was obtained.Finally,feature parameters of the original image and the enhanced image were extracted,and cluster analysis was used to isolate the bearings of different states.It is proved that the infrared thermal image can accurately diagnose the faults of bearings.