Preliminary experimental analysis of the surface topography formation during laser polishing H13 tooling steel using statistical characteristics of the surface amplitude distribution

摘要

Surface finish is one of the most important quality characteristics of fabricated components. To complement that, laser polishing (LP) is one of the advanced manufacturing surface finishing techniques that has been recently developed and successfully employed for improving surface quality without deteriorating the overall structural form through surface smoothing by melting and redistributing a thin layer of molten material. This paper proposes a statistical digital twin of the LP process and demonstrates the applicability of amplitude distribution statistical characteristics in the experimental analysis of surface topography formation during LP process. Initially, the thermodynamic transformation of the initial surface topography is considered by means of technical cybernetics and machine learning approaches to describe two of the most critical LP process components, namely: thermodynamic melting and solidification of both solid material and surface topography. To exemplify the effective application of statistical amplitude distribution characteristics, LP experiments were conducted with two different laser powers (25 W and 100 W) on flat and ground initial surfaces and resulting surface topographies were measured. Several amplitude distribution characteristics, such as roughness average value, averaged transverse profile as a W-shape, averaged transverse roughness profile, and probability distribution function were calculated. After that, actual molten material area, volume redistribution and final surface quality were comparatively analyzed. It was shown that the proportion between two components of the LP thermodynamic transformation and surface topography is critically dependent on laser power. As such, during low-power conditions (< 25 W), surface quality is predominantly determined by the thermodynamic transformation of initial surface topography and therefore only this component can be used for statistically reliable LP process modelling and digital identification. In summary, amplitude distribution characteristics have several advantages in building a comprehensive understanding of the molten material redistributing along and across LP line.