Power spectral analysis of surface microtopography formed in CW Laser surface texturing

Abstract

Laser surface texturing (LST) has shown immense promise in modifying the physical as well as interactive properties of the surfaces. Understanding the surface microtopography generated during LST provides key knowledge on developing desirable surfaces for different technologies. The work focuses on determining the range of frequency components present in the microtopography when processed at different parameters, such as beam diameter (BD), scanning speed (SS), and beam overlap (BO). Power spectral density (PSD) is utilized to evaluate the intensity of each spatial frequency and fitting models are applied to quantify their contribution to the overall microtopography. The experiments were performed on titanium alloy Ti6Al4V using a continuous watt fiber laser at constant power. The surface microtopography differs when processed under different conditions. The microtopography contains low and high spatial frequency components distributed along both the scan and overlap direction. The PSD analysis reveals the increase in high spatial frequency features when BD and SS are increased. Conversely, the growth of spatial features is observed with an increase in BO reducing the dominance of high spatial frequencies. With the increase in BD, the energy density decreases which reduces the growth of spatial features inducing increased contribution of high spatial frequency content noticeable by upward curvature in the PSD. An increase in SS causes rapid laser motion to affect the microtopography along the scan direction. The increase in BO leads to the enhanced overlapping between successive passes causing remelting and growth of previously formed microtopography and increasing the contribution of low spatial frequency content in the microtopography. The fitting model parameters from ABC at low spatial frequency and Fractal at high frequency provide the quantitative reasoning for the observed trend. Power spectral analysis reveals significant information about the surface microtopography formed during LST and accurate quantification of the PSD may help numerical models to fine-tune the surface features according to the desired functionality.