Weidong Gao

Theoretical study of fiber tension distribution at the spinning triangle

The spinning triangle is a critical region in the spinning process of yarn. Its geometry influences the fiber tension distribution and thus affects the properties of spun yarns. In conventional ring spinning, on the one hand, the spinning triangles are often asymmetric due to the frictional contacts of fibers with the bottom roller, which interferes with the twist propagation into the spinning triangle zone, and thus leads to the migration of the axis fiber at the front roller nip. On the other hand, the yarn spinning tension has an obvious angle with the vertical axis perpendicular to the nip line. Therefore, in this paper, a theoretical model of the fiber tension distributions in the general spinning triangle has been proposed by considering both the inclination angle of the spinning tension and the migration of the axis fiber at the front roller nip according to the principle of minimum potential energy. Two shape parameters were introduced to describe the skew level of the geometry of the spinning triangle in the analysis. The effects of shapes of the spinning triangle on the fiber tension distributions were investigated. The results show that the fiber tension distribution at the spinning triangle tends to more non-uniformity with increasing the asymmetry of the spinning triangle. The effects of both shape parameters on the fiber tension distributions are similar under the assumption that the spinning triangle height H is constant. In addition, a more long-narrow shape of the spinning triangle shows more uniform fiber distributions.

Numerical simulation of a three-dimensional flow field in compact spinning with a perforated drum: Effect of a guiding device

Compact spinning with a perforated drum is one of the most important kinds of pneumatic compacting. It utilizes the transverse air force in a perforated drum to condense the fiber bundle in order to effectively eliminate the spinning triangle and improve the qualities of spun yarns. Therefore, the emphasis in research on a flow field in the condensing zone is always on the difficulty of pneumatic compact spinning. In this paper, the three-dimensional flow field of compact spinning of a perforated drum with a guiding device is investigated using Fluent software. First, a three-dimensional model, using AutoCAD Software, of the condensing zone is given. Then, the numerical simulations, by using Fluent software, of the three-dimensional flow field in compact spinning of a perforated drum with three guiding devices (type A, type B, and type C) and without a guiding device are presented, respectively. It is shown that the effective range of the negative pressure in the condensing zone of the compact spinning system with a perforated drum and guiding device increases significantly as compared with that of compact spinning without a guiding device. The flow field distribution is symmetric with respect to the central line of air-suction flume. The fiber strands move toward the center under the left–right symmetric transverse air force, which achieves transverse converging effects. Meanwhile, the static pressure shows a wavy distribution due to the influence of round holes. Furthermore, it is proved that the comprehensive effect of the type C guiding device is the best. Finally, the theoretical results obtained are illustrated by spinning experiments.

Multi-perspective measurement of yarn hairiness using mirrored images

Most photoelectric and imaging methods for yarn hairiness measurements often provide underestimated data of hairy fibers measured from light projection, which ignores the spatial orientations and shapes of protruding fibers. In this project, a three-dimensional (3D) system was developed to detect hairy fibers from multiple perspectives and to reconstruct a 3D model for the yarn that permits fibers to be traced spatially. The system utilized two angled planar mirrors to view a yarn from five different perspectives simultaneously, and a digital camera to capture the multiple images in one panoramic picture. The image-processing techniques were used to dissect the panoramic picture into five sub-images containing separate views of the yarn, and to segment the sub-images to obtain yarn silhouettes showing the edges of the yarn and hairy fibers. A 3D model of the yarn could be built by merging the five silhouettes with the angles defined by the scene geometry of the dual mirrors. From the 3D model, hairy fibers protruding from the yarn core could be traced in the space for accurate length measurements. The system represents a simple and practical solution for the 3D measurement of yarn hairiness.

Research on the Compact-Siro Spun Yarn Structure

Compact-Siro spinning technology is one of the most widely used spinning methods. It is conducted on a compact ring frame by simultaneously feeding two rovings into the drafting zone at a predetermined separation. In fact, Compact-Siro spinning incorporates the features of both Compact and Siro-spinning systems. In this paper, the structure of CompactSiro spun yarn is investigated. By using a DZ3 video microscope, the horizontal structure of Compact-Siro spun yarn, Sirospun yarn, Compact yarn and Ring spun yarn were obtained. It is shown that compared with Compact single yarn, Compact-Siro spun yarn has a more compact and clear surface structure, a more uniform and smooth shape, and less hairiness. Then the cross section structure of Compact yarn and Compact-Siro spun yarn were obtained by using Hardy’s Y172 thin cross-section sampling device and the DZ3 video microscope. It is shown that compared with Sirospun yarn, the cross-section of Compact-Siro spun yarn is smoother and closer to being circular. Meanwhile in the Compact-Siro spun yarn body, the fibers of two substrands show axial symmetrical distribution approximately, which is beneficial for spun yarn qualities, especially for improving the yarn evenness and hairiness. Finally the results obtained were illustrated in spinning experiments.

Image analysis for seam-puckering evaluation:

Seam puckering is often considered an undesirable wrinkling appearance along a seamline, and is a problem that concerns fabric, sewing machine and sewing thread manufacturers. Until now, the standardized evaluation method for seam-puckering grading is still a visual-based, subjective method. This research project was aimed at developing a computer-vision system for automatic seam-puckering evaluation to improve the consistency and efficiency of grading. Fabric seam images were captured by a customized image acquisition system, and the seam images and the optimal image parameters, such as length and width, were determined according to the results of human inspection. The seamline was located with edge detection and Hough transform techniques. After rotating and cropping the image, the projection profile was then obtained and smoothed with the locally scatter-plot smoothing (LOESS) algorithm. Five characteristic features were extracted from the smoothed profile. Finally, an artificial neural network classifier was created to realize the automatic assessment of the seam-puckering grade. The experimental results proved that the proposed system can achieve accurate seam-puckering grades, and has the potential to replace the current manual evaluation.

Instrumental evaluation of fabric abrasive wear using 3D surface images

Abstract Fabric abrasive wear consists of both fuzzing and pilling phenomena, which are often assessed subjectively by comparing the sample to the photographic standards. This paper introduces a stereovision system to generate the three-dimensional (3D) image of surface appearance for objective evaluation of fabric wear. The 3D information of a fabric surface obtained from the stereovision system can be used to extract the fuzzing and pilling parameters that are insusceptible to fabric structures, colors, and fiber contents. Ten types of fabrics were treated on a standard fabric abrasion testing machine (the Martindale Tester) and visually graded. From the 3D images of these fabrics, the fabric fuzziness was quantified using a set of surface roughness parameters, such as the root mean square roughness (Rq), the mean roughness depth (Rz), bearing ratio (tp), and skewness (Rsk), and the fabric pilling was measured by density (D), height (H), size (S), and area ratio (AR) of individual pills. The results from the 10 tested samples demonstrated that the 3D measurements can characterize fuzzing and pilling appearance of fabric and quantify the degree of fabric abrasive wear.

Objective Fuzziness Assessment of Multi-Colored Fabrics Using 3D Images

A quantitative evaluation method based on a three-dimensional (3D) laser-scanning technique is presented for the objective assessment of fabric fuzziness. Fabric fuzziness, referring to severity of protruding fibers on a fabric surface, has a direct effect on fabric serviceability and needs to be evaluated routinely for quality assurance. In this research, the characterization of fabric fuzziness was realized by using a customized laser scanning system that can produce the 3D surface image of a fabric in a high resolution, and by analyzing the parameters of roughness amplitude distributions extracted from the 3D image. Multi-colored fabrics with different levels of fuzziness were first visually evaluated to obtain the subjective fuzziness grades in reference to a set of expert-rated cotton samples. Then, the fabrics were scanned by the laser system and the surface roughness parameters were calculated from the 3D images for the regression analysis with the subjective fuzziness grades. The result of multivariable regression analysis indicated that the fuzziness grade has a strong correlation with the roughness parameters, and can be estimated automatically after a fabric is scanned. The system demonstrated its fuzziness ratings are invariant to fabrics’ colors, prints, and structures.