Document Type
Paper
Keywords
Optical Profilometry, Impact Coverage, Surface Roughness
DOI
10.5703/1288284317945
Location
STEW 202
Start Date
25-9-2025 11:45 AM
Abstract
A critical consideration in peening process design is achieving sufficient impact coverage. Conventional methods for assessing coverage rely on manual inspection, which is time-consuming and poorly suited for automated control. In this work, we investigate the use of frequency-domain analysis to quantify surface modification in peened samples using optical profilometry (OP) data. Three-dimensional surface maps of Almen strips were acquired using a high-resolution OP system and analyzed via fast Fourier transform (FFT) to compute spatial power spectral densities (PSDs). PSD maps and radially averaged profiles reveal consistent amplification of harmonic components similar to the nominal particle size, with increasing intensity and frequency shift as a function of impact velocity and coverage. A normalized PSD metric was introduced to highlight frequency bands most affected by peening, and the peak amplification was shown to correlate with process parameters. These results suggest that spectral decomposition of OP measurements offers a rapid, interpretable, and scalable method for characterizing peened surfaces and could support future closed-loop process control in manufacturing environments.
Included in
Harmonic Analysis and Representation Commons, Manufacturing Commons, Metallurgy Commons, Tribology Commons
Fourier Analyses Of Optical Profilometry As An Inferential Measurement For Impact Coverage.
STEW 202
A critical consideration in peening process design is achieving sufficient impact coverage. Conventional methods for assessing coverage rely on manual inspection, which is time-consuming and poorly suited for automated control. In this work, we investigate the use of frequency-domain analysis to quantify surface modification in peened samples using optical profilometry (OP) data. Three-dimensional surface maps of Almen strips were acquired using a high-resolution OP system and analyzed via fast Fourier transform (FFT) to compute spatial power spectral densities (PSDs). PSD maps and radially averaged profiles reveal consistent amplification of harmonic components similar to the nominal particle size, with increasing intensity and frequency shift as a function of impact velocity and coverage. A normalized PSD metric was introduced to highlight frequency bands most affected by peening, and the peak amplification was shown to correlate with process parameters. These results suggest that spectral decomposition of OP measurements offers a rapid, interpretable, and scalable method for characterizing peened surfaces and could support future closed-loop process control in manufacturing environments.