Compact-siro spun with lattice apron combines compact spinning and siro spinning, and is widely put into practice. In this paper, compact-siro spun models with the parallel shaped slots, oblique parallel shaped slots and V-shaped slots were simulated. Based on the airflow data in the condensing zone, the geometrical model of single fiber is built, and then the trajectory of single fiber can be got. The morphological changes and movement process of fiber strands in the flow field of condensing zone were verified by the comparison experiments of yarn morphology, hairiness, tensile and evenness properties. The results showed that the V-shaped slot achieved the optimal agglomeration effect and yarn performance. The theory analysis gives foundation and explanation for the experiment, and also provides a theoretical basis for optimizing the properties of compact-siro yarn in production practice.
During the air flow twisting process of jet vortex spinning, the moving characteristics of flexible free-end fiber are complex. In this paper, the finite element model of the fiber is established based on elastic thin rod element. According to the air pressure and velocity distribution in the airflow twisting chamber of jet vortex spinning, this paper analyzes the undetermined coefficients of the finite element kinetic differential equation of the free-end fiber following the principle of mechanical equilibrium, energy conservation, mass conservation and momentum conservation. Based on numerical simulation, this paper gets the trajectory of the free-end fiber. Finally, the theoretical result of the free-end fiber trajectory by finite element simulating is tested by an experimental method. This paper has proposed a new method to study the movement of the fiber and learn about the process and principle of jet vortex spinning.
In this study, the wicking properties of ring and compact-siro ring spun staple yarns were compared. The twist level, which is related to the structure of the staple yarns, was found to significantly influence the wicking property of the two kinds of yarn. Polyester staple fibers with 1.33 dtex × 38 mm were selected as the staple fiber material, and the effect of the twist level on the wicking property was investigated using the capillary rise method. The results show that with a decreasing twist coefficient, the wicking height increases with a decrease in yarn compactness. The compact-siro spun yarn showed better wicking properties owing to it special ply yarn structure. Furthermore, the tension property of the yarns decreased significantly with a decrease in the twist coefficient. Compact-siro spinning was carried out to obtain staple yarns with lower twist coefficients, and the yarns showed great improvement in terms of yarn strength, fiber straightness, and wicking properties. Thus, compact-siro spinning is an efficient method to improve the wicking properties of staple yarns.
This study was aimed at investigating the process optimization of foam sizing for cotton yarns. In this work, effects of major foam-sizing process factors including size concentration, blowing ratio, stirring speed, pre-wetting temperature, pre-drying temperature, squeezing pressure and drying temperature were studied on the hairiness (more than 3 mm) and abrasion resistance of foam-sized yarns. The combination of Plackett-Burman, steepest ascent path analysis and Box-Behnken design were adopted to optimize the foam-sizing process of cotton yarns. Results revealed that size concentration, blowing ratio and squeezing pressure were significant factors that affected the hairiness and abrasion resistance. Optimum hairiness and abrasion resistance were obtained when the cotton yarns were sized at size concentration of 19.33%, blowing ratio of 4.27 and squeezing pressure of 0.78kN. The theoretical values and the observed values were in reasonably good agreement and the deviation was less than 1%. Verifcation and repeated trial results showed that it has good reproducibility and imparts the foam sizing process of cotton yarns.
In this article, a computerized method is proposed for simulating digital woven fabric (DWF) based on sequential yarn images captured from a moving yarn. A mathematical model of woven fabric structure is established by assuming that the crimped shape of yarns in weave structure is elastica, and the cross-sections of yarn in sequence image and fabric are circular and ellipse, respectively. The sequential yarn images, which are preprocessed and stitched first by image processing methods, are resized based on the mathematical model. Then a light intensity curve, which consists of radial curve model and axial curve model, is used to simulate the gray texture distribution of interlacing points in radial and axial directions. Finally, a Boole Matrix model is used to control the woven pattern. In the experiment, a slub yarn and a normal yarn samples with same count are applied to simulate gray texture fabrics. Then the gray fabrics are transformed to color fabrics based on three color maps. The fabric simulations are confined to single fabrics of plain, 2/2 matt, and 1/3 twill weaves.
In this study, a new detection algorithm for yarn-dyed fabric defect based on autocorrelation function and grey level co-occurrence matrix (GLCM) is put forward. First, autocorrelation function is used to determine the pattern period of yarn-dyed fabric and according to this, the size of detection window can be obtained. Second, GLCMs are calculated with the specified parameters to characterise the original image. Third, Euclidean distances of GLCMs between being detected images and template image, which is selected from the defect-free fabric, are computed and then the threshold value is given to realise the defect detection. Experimental results show that the algorithm proposed in this study can achieve accurate detection of common defects of yarn-dyed fabric, such as the wrong weft, weft crackiness, stretched warp, oil stain and holes.
Unlike the normal sizing method, the foam sizing had been proven to be a low-add-on technology. To investigate the effect of foam sizing, film thickness, sized-yarn evenness, and size penetration rate were necessary to evaluate the performances of foam-sized yarns. However, the conventional image analysis of sized-yarn cross sections primarily relied on artificial testing with a low efficiency. This paper proposed a novel dynamic method to measure the sized-yarn properties including film thickness, sized-yarn evenness, and size penetration rate based on yarn sequence images captured from a moving yarn. A method of dynamic threshold module was adopted to obtain threshold for segmenting yarns in the sequence images. K-means clustering algorithm was applied to segment pixels of the images into yarn and background. To further remove burrs and noise in the images, two judgment templates were carried out to extract the information of yarn core. The film thickness, sized-yarn evenness, and size penetration rate were measured based on the yarn core of each frame in sequence images. In order to compare with the experimental results of the dynamic method, the yarn properties of the same samples were tested by static and artificial testing. Results revealed that the proposed method could efficiently and accurately detect the film thickness, sized-yarn evenness, and size penetration rate.