Characteristic quantitative evaluation and stochastic modeling of surface topography for zirconia alumina abrasive belt

Abstract

Study of abrasive belt topography is the basis to understand wear evolution during belt grinding. Considering its importance and research gap, this paper proposed a quantitative characteristic evaluation method for abrasive belt surface, in addition, also provided a stochastic simulation approach for zirconia alumina abrasive belt based on measured assessment results. In quantitative evaluation, power spectrum density analysis, and autocorrelation function analysis were operated to determine the macroscopic texture feature through frequency structure, cutoff frequency, autocorrelation length, and texture vertical ratio. Besides, a set of parameters was defined in character statistics analysis to describe abrasive belt surface more specifically, including area ratio, summit density, cutting edge protrusion height, interspacing of grains, tip radius, and cone angle. The measured results illustrate that zirconia alumina abrasive belt topography is kind of isotropy surface with nearly constant area ratio and is constituted by three parts of waviness with different wavelength. The mathematical probability distribution models of protrusion height, inter-grain spacing, and cone angle accord with Gaussian distribution, while tip radius obeys Gamma distribution. Based on above conclusions, a stochastic simulation using a novel shuttle-shaped grain model was developed. The simulation is based on random spatial movement of grains with certain distribution regularity. The similarity of characteristic parameters between the experimental and numerical results, including summit density, cutting edge protrusion height, and inter-grain spacing, has successfully validated the stochastic model. This quantitative description and topography modeling provide a valuable foundation for investigating abrasive belt wear mechanisms and its effect on workpiece surface roughness.