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Vision system concept design for 3-D imaging: System integration in NDT thermographic tool for crack detection in welded components
University West, Department of Engineering Science.
2023 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 HE creditsStudent thesis
Abstract [en]

Thermographic inspection has raised attention as a suitable Non Destructive Testing technique to detect cracks in welded components. In this work, complementary vision systems are designed to be implemented into an existing thermographic inspection tool, with the objective of improving the Probability Of Detection and general performance of the tool by detecting common welding features and defects. An analysis of the thermographic tool and a bibliographic review of contemporary 3-D vision systems deems the laser triangulation technique as the most suitable for the intended purpose. Thus, two drafts for incorporating laser triangulation systems in the thermographic tool are designed. In the first one, a laser line beam source is rotated to scan the surface, while in the second one the scanning is performed by a linearly displaced mirror with an static light source. Detailed schemes, design parameter equations and measurement triangulation equations are formulated for each method. With a justified selection of values for the design parameters, a theoretical achievable measurement accuracy of 12.5 µm and 0.14 mm can be obtained for the first and second designs, respectively. Considerations and possible real accuracies are indicated for each method. Finally, CAD models for each method are constructed following the design parameters and component dimensions. The models show that prototypes and real implementations of the designs are possible. As future work, prototypes and testing of the designs is suggested, to study the validity of the designs and implementation challenges. 

Place, publisher, year, edition, pages
2023. , p. 49
Keywords [en]
thermographic inspection, laser triangulation, crack detection, welded components
National Category
Robotics
Identifiers
URN: urn:nbn:se:hv:diva-20608Local ID: EXR600OAI: oai:DiVA.org:hv-20608DiVA, id: diva2:1788556
Subject / course
Robotics
Educational program
Master i robotik och automation
Supervisors
Examiners
Available from: 2023-08-21 Created: 2023-08-16 Last updated: 2023-08-21Bibliographically approved

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