Three-dimensional reconstruction of wear particle surfaces using multi-focus image sequence

Abstract

Wear particles hold morphological traits that are linked to wear rate and mechanisms. Wear particle analysis is vital in the context of wear monitoring. Current methods can be used in three-dimensional (3D) reconstruction for particle type recognition and wear mechanism identification. A 3D reconstruction method based on microscopic focusing and image processing is here proposed. A fixed-focus quasi-planar strategy is built using the defocusing principle. The stationary wavelet transform is employed to assess the degree of focus for the purpose of depth mapping, facilitating the construction of 3D particle models. The model is then optimized for surface morphology to address noise and unevenness. The reconstruction results of the proposed approach were compared with that of laser scanning confocal microscope with average errors of arithmetic mean height (Sa), root-mean-square height (Sq), and kurtosis (Sku) at 2.81%, 2.96%, and 10.06%, respectively. The algorithm is non-contact and adaptable, offering value across various fields.