โ Scribed by Gabriel Fricout; Dominique Jeulin; Pierre-Jean Krauth; Thierry Jacquot
No coin nor oath required. For personal study only.
The visual aspect of rough surfaces such as steel surfaces becomes of great importance for the quality of the final product they are dedicated to. In a previous work, we have solved the theoretically complex problem of automatically classifying surfaces according to the quality of their aspect. In this case, the measurements were based on topographical maps obtained through interferometric microscopy. The resulting data were analyzed by an algorithm based on morphological and statistical features extraction from surface topography, factorial analysis, bootstrap over-sampling and Bayesian classification. It was then important to apply this methodology as efficiently as possible to perform an automatic, on-line and continuous inspection of the product. In this paper, we focus on all steps leading to such an on-line application, among which choosing an optical sensor and the corresponding optical configuration adapted to an industrial environment and overcoming all difficulties to go from first laboratory tests to on-line measurements on fast moving product are particularly determining. Finally, results of on-line acquisitions are displayed, that are in good agreement with expected aspect characterization.
๐ SIMILAR VOLUMES
This paper presents a new approach for the sampling of sculptured surfaces using continuous scanning coordinate measuring machine probe heads. This approach is based on scanning isoparametric lines on the sculptured surface. This paper addresses the issue of isoparametric line sampling. The problem
The incompressible viscous flow over several non-smooth surfaces is simulated numerically by using the lattice Boltzmann method. A numerical strategy for dealing with a curved boundary with second-order accuracy for velocity field is presented. The drag evaluation is performed by the momentum-exchan