Dynamic grinding wheel envelope measurement method based on sub-pixel micro shift fusion algorithm

Abstract Direct on-machine detection of the grinding wheel profile during the grinding process is critical for enhancing both the precision and efficiency of grinding operations. Nevertheless, the harsh conditions during the grinding process pose significant challenges to implementing such detection. To address this issue, this study proposes an online dynamic grinding wheel envelope measurement method based on nanocomposite motion. Specifically, the rotating grinding wheel is first subjected to micro-displacements within a 3 × 3 right neighborhood, with each displacement step set to 1/3 of a pixel; subsequently, dynamic wheel envelope images are acquired individually for each displacement state. These multiple images are then fused in the grayscale domain according to their respective displacement directions, yielding a sub-pixel high-precision fused image with a spatial resolution equivalent to 9 times that of the original pixel size. Next, an improved omnidirectional gradient sub-pixel detection algorithm is employed to extract the edge information of the grinding wheel profile. Following this, the Hough transform is applied to preliminarily extract the arc profile information of the grinding wheel, serving as a rough profile acquisition step. Finally, an iterative weighting process is performed on the collected rough grinding wheel profile to eliminate edge outliers, thereby minimizing interference with the subsequent profile fitting. Experimental results demonstrate that the proposed improved envelope measurement method can effectively reduce profile errors, achieving a measurement accuracy of ±0.18 μm; simultaneously, the online detection capability of the method contributes to a notable improvement in measurement efficiency.