Presentation + Paper
10 October 2020 Fast 3D surface defect detection with fringe projection
Author Affiliations +
Abstract
Ensuring high quality standards at a competitive cost through rapid and accurate industrial inspection is a great challenge in the eld of intelligent manufacturing. Three-dimensional (3D) optical quality inspection technologies are gradually widely applied for surface defect detection of complex workpieces because of its non-contact, high- accuracy, digitization and automation. However, the contradiction between cost and eciency, dependence on additional position hardware, and compromised detection strategies remain the urgent obstacles to overcome. In this work, we propose a fast 3D surface defect inspection approach based on fringe projection pro-lometry (FPP) for complex objects without any auxiliary equipment for position and orientation control. Firstly, a multi- view 3D measurement based on geometric constraints is employed to acquire high-accuracy depth information from dierent perspectives. Then, a cycle-positioning-based registration scheme with the establishment of the pose-information-matched 3D standard digital model is proposed to realize rapid alignment of the measured point cloud and the standard model. Finally, a minimum 3D distance search method is driven by a dual-thread processing mechanism for simultaneous scanning and detection to quantify and locate 3D surface defects in real time. To validate the proposed inspection approach, a software that combines 3D imaging, point cloud registration, and surface defect calculation is developed to perform quality inspections on complicated objects. The experimental results show that our method can accurately detect the 3D surface defect of the workpiece through more economical hardware and more convenient means in real time, which is of great signicance to intelligent manufacturing.
Conference Presentation
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Jiaming Qian, Shijie Feng, Yixuan Li, Tianyang Tao, Qian Chen, and Chao Zuo "Fast 3D surface defect detection with fringe projection", Proc. SPIE 11552, Optical Metrology and Inspection for Industrial Applications VII, 1155208 (10 October 2020); https://doi.org/10.1117/12.2573374
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KEYWORDS
Defect detection

3D metrology

3D modeling

3D imaging standards

Clouds

Image registration

Inspection

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