A parameterized unit cell model for 3D braided composites considering transverse braiding angle variation

Zhang, Weijie; Yan, Shibo; Yan, Ying; Li, Yiding

doi:10.1177/00219983211053909

Cited by 5 publications

(4 citation statements)

References 24 publications

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“…Glass fiber plain weave fabric is formed by interweaving warp and weft yarns; the internal spacing of warp and weft yarns is more uniform, with high stability, and it is commonly used in numerous industries to make composite materials. The yarn angle (the angle between the warp and weft yarns) is an important parameter affecting the mechanical properties of woven composites [1][2][3][4][5]. It is also possible to determine whether there are folds and foreign objects in the glass fiber plain weave fabric by analyzing the angles.…”

Section: Introductionmentioning

confidence: 99%

Yarn Angle Detection of Glass Fiber Plain Weave Fabric Based on Machine Vision

Hou,

Wang,

et al. 2024

Applied Sciences

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To address the issue of low accuracy in the yarn angle detection of glass fiber plain weave fabrics, which significantly impacts the quality and performance of the final products, a machine vision-based method for the yarn angle detection of glass fiber fabrics is proposed. The method involves pre-processing the image with brightness calculation, threshold segmentation, and skeleton extraction to identify the feature region. Line segment detection is then performed on this region, using the Hough transform. The concept of a “line segment evaluation index” is introduced, and it was used as a criterion for assessing the quality and relevance of detected line segments. Moreover, the warp and weft yarn extrusion area contours refer to the reconstructed outlines of yarn areas, achieved by combining the center of mass extraction with morphological operations and used to accurately determine the yarn angle. Tested under a range of challenging scenarios, including varied lighting conditions, fabric densities, and levels of image noise, this method has demonstrated robust stability and maintained high accuracy. These tests mimic real-world manufacturing environments, where factors such as ambient light changes and material inconsistencies can affect the quality of image capture and analysis. The proposed method has high accuracy, as shown by MSE and a Pearson’s r of 0.931. By successfully navigating these complexities, the proposed machine vision-based approach offers a significant enhancement in the precision of yarn angle detection for glass fiber fabric manufacturing, thus ensuring improved quality and performance of the final products.

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Section: Introductionmentioning

confidence: 99%

Yarn Angle Detection of Glass Fiber Plain Weave Fabric Based on Machine Vision

Hou,

Wang,

et al. 2024

Applied Sciences

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“…[1] Methods for predicting the mesostructure of the braided preforms are the focus of considerable research on braided composite materials, [2][3][4][5][6] because the parameters of the mesostructure of the preform, such as the braiding angle, braiding pattern, the distance between the yarns, and cross section of the yarns determine the mechanical properties of the braided composites. The mesostructure of braided preforms in a majority of publications [7][8][9][10] relies on highly idealized geometric assumptions, for example, constant cross section, parallel yarn paths, or polygonal cross section, for the ease of modeling of the structures. In the manufacturing process of braided preforms, yarn deformation such as bending, shifting, and nesting are introduced, which are on top of the idealized mesostructure of the braids.…”

Section: Introductionmentioning

confidence: 99%

High‐fidelity modeling of the braiding process for generating the realistic mesostructure of preforms in braided composites

Yan

et al. 2023

Polymer Composites

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An accurate method for modeling the braided preforms is vital for the mesoscopic performance analysis of tubular composites. This study proposed a high‐fidelity virtual braiding model for the general braiding process, which further considers the fiber‐level deformation of the yarns during the braiding process to generate the realistic mesostructure of preforms in tubular composites. The method uses the digital element approach previously proposed for weaving processes to model the braiding yarn. The whole braiding process, including the deposition zone and convergence zone, is incorporated into the model to account for the effect of interaction in these zones on the preform mesostructure. Two braiding processes were simulated with the proposed virtual braiding method. The simulated geometry of the braided preforms and the yarn paths in the convergence zone agree well with the reported experimental results. To facilitate the performance analysis of braided composite structures, further automated generation of solid cell instances based on the obtained braided preforms was studied. Importantly, this work could reduce the considerable effort required for characterizing the mesostructure via the costly micro‐CT scans for braided composites, and the generated geometry of the braided preform is more precise than the widely used highly idealized models.

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“…Therefore, they are widely used in fields such as aerospace, automotive manufacturing, and architectural engineering [3,4]. Their mechanical properties can be simulated using finite element methods by dividing unit cell models [5,6]. The 3D braiding process can be divided into track-and-column 3D braiding and rotary 3D braiding.…”

Section: Introductionmentioning

confidence: 99%

Structural modelling of rotary three-dimensional braiding preforms

Wang,

Long,

Wang

et al. 2023

Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023)

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This work aims to study the modelling method of braiding preforms based on the rotary 3D braiding process. In the rotary 3D braiding process, the carrier is driven by the horn-gear through its alternating rotation, thus yarns interlacing to form the braiding preform. Encoding the horn-gear and the carrier to study the movement law of the carrier. The trajectory of the carrier and the height of the braiding node jointly determine the spatial topology structure of the braiding preform. The yarn trajectory is fitted and optimized using the cubic B-spline curve, Python script is written to drive CATIA to establish a solid model of the braiding preform and a fabric structure simulation interface is developed using PyQt5. Experiments on the braiding of irregular components are conducted to compare the actual braiding fabric with the corresponding model. The result indicates that the braiding algorithm could accurately record the coordinates of the trajectory points of the carrier; The fitted yarn trajectory conforms to the actual trajectory of the yarn; The simulated preform structure is consistent with the actual braiding preform. Therefore, it can be concluded that the modelling method is suitable for structural simulation of various cross-section braiding preforms.

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A parameterized unit cell model for 3D braided composites considering transverse braiding angle variation

Cited by 5 publications

References 24 publications

Yarn Angle Detection of Glass Fiber Plain Weave Fabric Based on Machine Vision

Yarn Angle Detection of Glass Fiber Plain Weave Fabric Based on Machine Vision

High‐fidelity modeling of the braiding process for generating the realistic mesostructure of preforms in braided composites

Structural modelling of rotary three-dimensional braiding preforms

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