Papers by Keyword: Speckle Patterns

Abstract: Digital image correlation (DIC) is an optical technique for full field deformation measurement. The spatial resolution and precision of the measurements are limited by the number of pixels within the image. The use of magnifying optics provides greater spatial resolution images, enabling smaller displacements to be observed with greater accuracy. Increasing the magnification of an image significantly changes the appearance of the non-periodic, stochastic speckle pattern which provides the grey scale contrast necessary for the image correlation method. In the paper a methodology is developed to evaluate the properties of different speckle pattern types under a range of resolutions up to 705 pixel / mm. Numerical deformation of the patterns is also undertaken to evaluate how the changes in the pattern properties affect the accuracy of the DIC measurements.

Abstract: An approach of damage detection based on ESPI and SVM is proposed. ESPI
(Electronic Speckle Pattern Interferometry) is a non-contacting measuring method, which can measure the small static and dynamitic surface deformations and reveal the flaws by looking for flaw-induced deformation anomalies. Support Vector Machine (SVM) is a machine learning algorithm based on statistical learning theory, and it has recently been established as a powerful tool for classification and regression problems. To develop the precision of processing the pattern fringe data, the SVM is introduced to process the patterns corrupted by the laser speckle effect. The SVM is trained with fringe patterns generated from a finite element model and a simple model of the laser speckle effect. The output pattern is obtained to flag whether the damage exists or not. The trained SVM is tested for robustness with model generated test patterns of a flat plate. The results show that this approach is a promising and effective for damage detection.