Vision‐based fatigue crack automatic perception and geometric updating of finite element model for welded joint in steel structures

Digital twin requires establishing a self‐updated model to simulate the structural damage perceived onsite. Despite the great success in damage identification and quantification, the difficulty in registration still limits the efficiency of model updating. This study presented a framework that enabl...

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Bibliographic Details
Published in:Computer-aided civil and infrastructure engineering 2024-06, Vol.39 (11), p.1659-1675
Main Authors: Gao, Tian, Yuanzhou, Zhiyuan, Ji, Bohai, Xie, Zaipeng
Format: Article
Language:English
Subjects:
Algorithms
Cameras
Coordinate transformations
Damage detection
Digital twins
Fatigue cracks
Fatigue failure
Finite element method
Hough transformation
Image reconstruction
Mathematical morphology
Model updating
Perception
Perceptions
Steel structures
Stiffness matrix
Structural damage
Welded joints
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Summary:Digital twin requires establishing a self‐updated model to simulate the structural damage perceived onsite. Despite the great success in damage identification and quantification, the difficulty in registration still limits the efficiency of model updating. This study presented a framework that enables a finite element (FE) model of welded joints to remesh itself for updating the geometric changes caused by the fatigue crack. Leveraging the linear geometry of the weld, a crack registration algorithm was proposed for the automation of crack perception. First, a dual‐task network was established to identify the crack and weld on the 2D image, where the deep Hough transform was introduced to detect the positioning weld among the irregular structural geometry. With the time‐of‐flight technique, the crack was then reconstructed and quantified in the 3D camera coordinate system. Meanwhile, the 3D structure coordinate system was established from positioning welds. Through simple coordinate transformation, the fatigue crack was automatically registered to the welded joint. Finally, the perception algorithms were integrated with the FE model, taking about 1 min to map the crack into the model. Under laboratory tests, the perception performance was not sensitive to the camera pose. The perceived errors were mainly reflected in the crack local morphology, not leading to improper reconstruction of the structural stiffness matrix.
ISSN:1093-9687
1467-8667
DOI:10.1111/mice.13166