Automatic visual inspection of the surface appearance defects of bearing roller

An analysis is made of bearing surface appearance defect inspection. The intrinsic handicap of the most widely used analog thresholding technique for improving inspection reliability is demonstrated, and a test machine vision inspection system is proposed. The system utilizes a self-scanning photodiode array as the light sensor, a special mechanism for unrolling the roller surfaces, and a PC/AT for image processing. The performance of the system is controlled by a UC-Z80 single-board computer. For image processing, three novel methods were used: (1) average-based shading correction, (2) background model for pollution erasing, and (3) a local iterative operator for defect and background clustering. These algorithms make the defect segmentation very reliable, even in the presence of oil pollution. For different precision rollers, the system can easily be adapted by altering the input parameters. Test results show that the system is capable of inspecting most surface defects such as cracks, pits, rust, or scratches with high reliability. The minimum crack width which can presently be detected is 25 μm