Machine Vision for As-Built Modeling of Complex Draped Composite Structures

Döbrich, Oliver; Anderegg, Ayoh; Gort, Nicolas; Brauner, Christian

doi:10.3390/ma14030682

Cited by 3 publications

(4 citation statements)

References 47 publications

(49 reference statements)

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“…Stationary cameras were used on these steady production processes where no geometrical information was required. The obtained values were used for quality assessment (Lian et al, 2000) and process control (Mersmann, 2011;Lekanidis and Vosniakos, 2020), simple damage detection (Wilhelmsen and Ostrom, 2016), and for importing material relevant input data (fiber orientation) into a virtual environment finite element analysis (FEA) models for further use in numerical simulation (Stender et al, 2019;Döbrich et al, 2021). Studies on using composite machine vision in material research to study the fatigue behavior of glass-fiber-reinforced composites are also found in the literature (Song et al, 2022).…”

Section: State Of the Artmentioning

confidence: 99%

“…The field of view for those applications is rather small and is limited to a specific section of composite parts or composite production processes. The digital image evaluation at the component level of composite structures is carried out by handguided or robot-guided camera systems (Kunze et al, 2020;Döbrich et al, 2021). Commercially available systems are provided by Hexagon (Sweden, formerly Apodius) [hand-guided inspection system (Stender et al, 2019;Antoniou et al, 2020;Döbrich et al, 2021)] or CIKONI (Germany) [robot-guided Hexagon system (Pasco et al, 2019)].…”

Section: State Of the Artmentioning

confidence: 99%

“…The digital image evaluation at the component level of composite structures is carried out by handguided or robot-guided camera systems (Kunze et al, 2020;Döbrich et al, 2021). Commercially available systems are provided by Hexagon (Sweden, formerly Apodius) [hand-guided inspection system (Stender et al, 2019;Antoniou et al, 2020;Döbrich et al, 2021)] or CIKONI (Germany) [robot-guided Hexagon system (Pasco et al, 2019)]. These systems can easily adapt to the shape of the structural part (Malhan et al, 2018).…”

Section: State Of the Artmentioning

confidence: 99%

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Machine vision system for digital twin modeling of composite structures

Döbrich

Brauner

2023

Front. Mater.

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Although the structural design of composite structures has already been carried out on a virtual level, composite mechanical properties remain sensitive to fiber orientation and therefore to the quality and reliability of the production process. Considering both manual single-unit manufacturing and advanced mass-unit fabrication, requirements on the production quality may differ, but certainty on the achieved result is crucial. A digital twin model, deterministically derived from produced parts, can be transferred into a virtual simulation environment to check for potential deviations of fiber alignment, resulting from variations in source material or composite production. Transferring that deterministic information into a virtual simulation environment allows for an estimation of the part’s structural potential despite any possible deviations by carrying out numerical simulation predictions on that model. This step of quality assessment can help reduce scrap parts by relying on simulation data that may demonstrate the feasibility of parts despite the containment of deviations with an otherwise uncertain impact. Therefore, further steps toward digitalization of the composite production process chain, especially on the characterization of the production quality, are aspired. In this contribution, a vision system based on a Microsoft Azure Kinect RGB-D camera is introduced which is used to digitalize the composite preform configuration from machine vision data by evaluating the achieved local fiber orientation as result of the complex preform draping process by digital image processing. A digital workflow is introduced that enables to feed the captured real-world data back into a digital environment where numerical simulations with the “as-built” fiber orientation can be carried out. The obtained results are used for assessing production quality and composite performance in the presence of possible deviations. The system, which consists of a camera array of consumer grade, can acquire real-world data and then transfer the data into a virtual environment.

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Section: State Of the Artmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

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Machine vision system for digital twin modeling of composite structures

Döbrich

Brauner

2023

Front. Mater.

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“…This system generates an STL file that can be compared to the as-planned (undeformed) geometry via manual overlay so that the maximum deviation between the geometries can be minimized. The global comparison was done similar to previous studies [ 20 ] using MeshLab and the built-in Hausdorff distance. The obtained result was then scaled to the measured maximum distance based on a comparison of the as-planned geometry and the STL file obtained from scanning.…”

Section: Implementation and Application On A Structural Levelmentioning

confidence: 99%

A Manufacturing Process Simulation of Toughened Cyanate-Ester-Based Composite Structures with Respect to Stress Relaxation

et al. 2022

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The objectives of this study were to experimentally determine the effects of the stress relaxation of a cyanate-ester-based composite, derive and integrate constitutive equations into commercial FEM software, and apply this approach to understand the formation of residual stress in a typical aerospace structure—namely, a stiffened panel. In preliminary studies, a cyanate-ester-based composite with increased fracture toughness for high-temperature applications was developed. High curing temperatures up to 260 °C will inevitably lead to high process-induced stresses. To assess the magnitude of impact on the development of internal stresses, the relaxation behavior of the neat resin was measured and characterized. The system was toughened, and the effect of stress relaxation increased as the temperature got closer to the glass transition temperature of the toughener, which was approximately 240 °C. With the use of an incremental linear viscoelastic model, the relaxation behavior was integrated into a process model with a holistic approach. A stiffened panel was manufactured and used as the validation use case. The displacement field was validated with an optical 3D measuring system, and good agreement was found between the simulated and experimental results. The maximum difference between the elastic and the viscoelastic solution was found to be 15%. Furthermore, the stress magnitude in the transverse material direction resulted in a more critical value higher than the material strength.

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