Analysis of yarn fiber volume fraction in textile composites using scanning electron microscopy and X-ray micro-computed tomography

Abstract

Variation of yarn fiber volume fraction, induced by the compression between adjacent yarns during the manufacturing process of textile composites, is difficult to be determined by using a single imaging method. A method combining scanning electron microscopy and micro-computed tomography is proposed to quantify the variation of yarn fiber volume fraction of textile composites, which is decomposed into systematic trend and stochastic deviation. The method takes the advantages of high resolution of scanning electron microscopy and wide 3D view of micro-computed tomography. Average fiber cross-sectional areas are acquired by analyzing hundreds of fiber cross-sectional areas in scanning electron microscopic images. Yarn cross-sectional area is determined by fitting ellipse to the labeled yarn cross-section in slices of micro-computed tomography images. The results of E-glass/epoxy and carbon/epoxy specimens show that their systematic trends of yarn fiber volume fraction combined with standard deviations of stochastic deviation, relative to the respective global means, fluctuate between [−11.4%, 15.3%] and [−12.9%, 10.7%], respectively. Yarn FVF varies in specimen obviously and needs to be considered in mechanical property prediction.

MATLAB Algorithms for Diameter Measurements of Textile Yarns and Fibers through Image Processing Techniques

“…The cross-sectional images of the yarn can be obtained by slicing the yarn using a microtome and then imaging these slices using an optical microscope [18,19]. In addition to the microtome approach, the yarn's slices can be obtained by micro-computed tomography scanning machines, where the yarn is three-dimensionally (3D) scanned and a digital actual 3D model of the yarn is constructed [20][21][22]. The cross-section images/slices can be reconstructed from that scan, the computed tomography slices give insight into the internal and external structure of the yarn; hence, these slices can be useful for modeling and understanding the parameters of the textile yarn.…”

A review of applications of CT imaging on fiber reinforced composites

“…Yu X.W. et al 25 proposed a method to quantify the variation of yarn fiber volume fraction of textile composites. Average fiber crosssectional areas were acquired by analyzing hundreds of fiber cross-sectional areas in scanning electron microscopic images.…”

“…Besides, there were many studies referring to analysis of fiber misalignment, spatial distributions, and hence volume fraction in textile structural composites. 15,[23][24][25] Liu et al 15 studied on 3D spatial distribution of steel fibers in fiber reinforced cementitious composites through micro-CT technique. The curves of fiber orientation distribution and fiber spacing distribution in cementitious composites were obtained and the orientation factor and dispersion coefficient of fiber were also determined.…”

“…[7][8][9] XCT has been widely used for qualitative and quantitative assessments in the fields of fiber reinforced composites. [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] Compared to other destructive and 2D visualization techniques, such as scanning electron microscopy, optical microscopy, etc., XCT can provide information on the internal microstructure in both 2D and 3D formats. 26 Moreover, other non-destructive techniques, such as ultrasonic C-scan and Acoustic Emission, could detect the defects in the interior, but they cannot capture the high-resolution damage mechanisms which can be achieved using XCT.…”

Multiple ellipsoidal/elliptical inhomogeneities embedded in infinite matrix by equivalent inhomogeneous inclusion method

“…However, in the problem of two spherical hard inhomogeneities with small separation distance, the accuracy of the stress concentration predicted by EIM worsened significantly as the polynomial eigenstrains increased from two to three orders [19]. In real composite materials, the fibers distribute near each other [27,28]. This paper determines the elastic field of multiple inhomogeneities with small separation distance by the equivalent inhomogeneous inclusion method (EIIM).…”