DESIGN OF AUTOMATED DEFECTOSCOPY SYSTEMS
[ 1 ] Wydział Techniczny, Akademia im. Jakuba z Paradyża | [ P ] pracownik
[2.3] Informatyka techniczna i telekomunikacja[2.9] Inżynieria mechaniczna
2025
artykuł naukowy
angielski
- HRRS
- defect detection
- detection attributes
- detection parameters
- comparative studies
PL Defects on highly reflective rotating surfaces can adversely affect the performance, service life, and safety of products, making surface defect detection a critical process in quality assurance. This study focuses on analysing the roughness and shape accuracy of precision surfaces, particularly for metal and ceramic components with rotational symmetry. Identifying surface defects, assessing deviations from ideal roundness and cylindricity, and quantifying these deviations are key objectives in ensuring manufacturing precision. Various techniques are employed in defect detection, including visual, optical, interferometric, polarization, reflexometric, holographic and other advanced methods. These approaches involve subjecting the rotating surface to illumination and analysing the reflected signals. The reflected signal is processed to generate a two-dimensional function based on the rotation angle and spatial coordinates, enabling precise evaluation of surface quality. Within this framework, statistical parameters are computed in a sliding analysis window to detect irregularities. For instance, sliding dispersion values are used to differentiate defect-free regions from defective ones, with lower dispersion indicating smooth, uniform surfaces and higher values pointing to potential defects. By comparing these values against a predefined threshold, defects are identified systematically. This approach provides a robust and efficient methodology for detecting and quantifying surface defects on rotationally symmetric components. It ensures improved precision in manufacturing processes and enhances the reliability and safety of the resulting products. The findings emphasize the importance of integrating advanced defect detection techniques in modern production lines to maintain high-quality standards.
2025
611 - 616
CC BY-NC-ND (uznanie autorstwa - użycie niekomercyjne - bez utworów zależnych)
otwarte czasopismo
ostateczna wersja opublikowana
12.2025
w momencie opublikowania
100