Application of image stitching in rail abrasion 3D online detection

Jinlong Lee; Xiaorong Gao; Zeyong Wang; Quanke Zhao; Lin Luo

doi:10.1117/12.2245679

27 September 2016 Application of image stitching in rail abrasion 3D online detection

Jinlong Lee, Xiaorong Gao, Zeyong Wang, Quanke Zhao, Lin Luo

Proceedings Volume 9684, 8th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test, Measurement Technology, and Equipment; 96841Z (2016) https://doi.org/10.1117/12.2245679
Event: Eighth International Symposium on Advanced Optical Manufacturing and Testing Technology (AOMATT2016), 2016, Suzhou, China

Abstract

PMP (Phase measuring Profilometry) is an excellent 3D online measurement method for its high precision. However, the measuring range is limited. While the rail is so long that far exceeds the measuring limit, the image stitching should be used to extent it. In this paper, based on the improved Stoilov algorithm, the rail shape is three-dimensionally reconstructed and the abrasion is detected combines image stitching. Two types of schemes are researched: (1)image stitching is firstly used on the deformed fringe patterns and then a larger range rail is constructed with Stoilov algorithm; (2)the three-dimensional construction of two fringe pattern is firstly performed, and then the constructed images are stitched into longer rail. In this paper, the improved Stoilov algorithm based on statistical approach and stitching algorithm are analyzed. 3D Peaks function is simulated to verify the two methods, and then three-dimensional rail shape is recovered based on these two methods and the rail abrasion is measured with the relative precision of higher than 0.1%, which is much higher than traditional methods, such as linear laser scanning.

Citation Download Citation

Jinlong Lee, Xiaorong Gao, Zeyong Wang, Quanke Zhao, and Lin Luo "Application of image stitching in rail abrasion 3D online detection", Proc. SPIE 9684, 8th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test, Measurement Technology, and Equipment, 96841Z (27 September 2016); https://doi.org/10.1117/12.2245679

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