Design of quantification methods for cross-sectional uniformity of functional fiber blended yarns

Abstract

The fiber distribution in yarn structure influences the mechanical, aesthetic, and functional properties of textile products, but methods for characterizing this distribution remain limited. The uniformity of fiber distribution is mostly quantified by the blend irregularity and migration index. Asymmetric and segregated distributions are commonly identified in cross sections of fibers in yarn; however, detecting uniform, wrapped, or core distributions in side-view images is challenging. Therefore, a more effective and versatile method is required for the quantification of cross-sectional uniformity in blended yarns. In this study, two methods for quantifying fiber distribution uniformity were proposed and evaluated. In the window variation method (WVM), which is based on cell counting, windows are randomly selected, and the uniformity of one type of fiber in a yarn cross section calculated according to the variation of the fiber ratio in each window. In the dilation method (DLM), uniformity is quantified according to the dilation area of the targeted fiber. To evaluate these quantification methods, we conducted antibacterial performance tests on 12 chitosan/cotton yarn samples and compared the results with indexes. Comparison of the two methods reveals that the WVM exhibits greater potential because the threshold yarn area ratio and the weights of the corresponding windows can be programmed to achieve certain quantification goals, while the DLM is simple and fast, with fewer variables than the WVM.

Design Thinking Applied to Home Textiles Innovation: A Case Study in an Elderly Centre in Hong Kong

“…Therefore, biological tests were utilized to evaluate the bio-functions, antimicrobial properties and wound healing abilities of the chitosan textiles. Chitosan textile in its original form considerably improves the proliferation of fibroblast cells [49][50][51][52][53][54]. For the wound healing test, healthy inbred albino Wistar strain 5-week male rats were used for the study and chitosan textile reduced the time of the first stage and the total time of wound healing by 2-3 days out of 13 days, as shown in Figure 1.…”

Chitosan Natural Polymer Material for Improving Antibacterial Properties of Textiles

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Image-based textile decoding

“…Compared with the simple Fourier transform, the change in the density of the weft can be obtained more accurately. Luo and Li [34] employed image processing techniques for quantifying fiber distribution uniformity in blended yarns based on cell counting and dilation area estimation. Meng et al [35] realized their goal of estimating the yarn density of multi-color woven fabrics by deep learning.…”