Abstract
•Fast Fourier transform (FFT) analysis enables rapid surface quality inspection.•The second harmonic of the FFT response is proportional to diffraction intensity.•The positional accuracy of theoretical diffraction spots exceeds 90 %.•Surface roughness data facilitate rapid diffraction fringe detection.•The proposed method reduces inspection time by 65 % (vs. a traditional method).
High-end optical molds are essential for mass-producing precision optical components used in biomedical, defense, and automotive manufacturing applications. These components are often produced through single-point diamond turning (SPDT), and their optical performance depends on their surface quality and shape accuracy. On mirror-grade surfaces, periodic microstructures caused by feed rate variations and tool wear can induce diffraction, leading to visible rainbow diffraction fringes that degrade optical performance. In traditional surface metrology, inspections of diffraction fringes require visual or laser-based methods, which are labor-intensive, time-consuming, and heavily reliant on human judgment and experience. To improve the efficiency of quality inspection, this study developed a fast Fourier transform (FFT)-based method to assess diffraction intensity. A full-factorial experiment was performed to analyze the effects of feed rate and tool wear on diffraction intensity, with the FFT employed to extract surface periodic features. The experimental results indicated that greater tool wear led to higher diffraction intensity, with the second harmonic of the FFT response being strongly correlated with diffraction intensity (K > 0.89) under 650-nm laser illumination. Analysis of the theoretical diffraction angle confirmed that the second harmonic was the main cause of diffraction, with the positional accuracy of theoretical diffraction spots exceeding 90 %. When the second harmonic response exceeded the surface roughness threshold, imaging quality was negatively affected. The proposed innovative FFT-based approach enabled rapid diffraction assessment, assists in tool wear monitoring and reducing quality inspection time by 65 % compared with traditional laser-based inspection methods. Thus, this method has high potential for application in quality inspections in SPDT.