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Annular Region Statistical Feature-based Recognition of Bearing Rings under Non-exact Positioning

Bo Jin, Lijun Zhao, Shiqiang Zhu

Abstract


A monocular vision-based approach is proposed for inspecting the excircle filleting status of fixed-size bearing rings under non-exact positioning. Through cropping, grey-scaling, binary segmentation of the images grabbed from the top and bottom sides of bearing rings and extracting the black points sum in a specified annular region, the rings were classified as filleted or not based on the pre-established criterion. The methods of determining the critical parameters for binary segmentation as well as subsequent classification were discussed in details. Experimental results have showed that all the inspected bearing rings were recognized and classified correctly.

Keywords


bearing ring, filleting status, monocular vision, non-exact positioning.

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