Elucidating diamond grinding wheel surface characteristics through integrated optical microscopic reconstruction system

The topographical characteristics of diamond grinding wheels are critical to their performance, yet their quantification presents significant metrological challenges. Focus Variation (FV) microscopy is a promising technique for this purpose, but standard focus evaluation algorithms often fail when encountering the optically complex surfaces of grinding wheels, which feature specular reflections from abrasive grains and low-contrast textures from bonding materials. This leads to inaccurate 3D reconstructions and unreliable parameter extraction. To address this limitation, this paper proposes an enhanced FV methodology centered on a novel Multi-Gradient Adaptive Focus Evaluator (MGAF). The MGAF is specifically designed to improve the robustness and accuracy of focal plane detection on such challenging surfaces. Furthermore, a post-processing pipeline integrating a Multi-Scale Clustered Profiling technique based on Dual-Tree Complex Wavelet Transform is employed for the precise quantification of surface roughness and abrasive grain distribution. Comprehensive validation was performed against commercial system. The results demonstrate excellent agreement, with Sa discrepancies below 10% and a relative error in abrasive grain density quantification of less than 5%. This work validates the proposed methodology as a robust and accurate tool for the in-depth characterization of diamond grinding wheels, paving the way for improved quality control and process optimization.