Manufacturing Color-Blended Slub Yarn: Computer Numerically Controlled Ring-Spinning Frame and Kubelka-Munk Double Constant Theory

In the present work, we used the computer numerically controlled (CNC) ring-spinning frame to produce the color-blended slub yarns made from three different colored rovings with a 10% blending gradient. The blending ratio of rovings was determined by Kubelka-Munk (K-M) double constant theory. The as-manufactured yarns were made into knit fabrics with a circular knitting machine. The relative value method was used to solve the absorption and scattering coefficients of each colored fiber, and the least-square method was used to solve for the blending ratio of color-blended slub yarn. The results show that the average color difference between predicted and measured L*a*b* values was 1.74, and the error of the blending ratio was 7.38%, which are within the acceptable ranges for color matching of yarns.

Manufacturing a ring spun slub yarn using multi-channel drafting technique

In this paper, we propose a novel method for manufacturing a ring-spun slub yarn through multi-channel drafting using a computer numerically controlled (CNC) ring spinning frame. Through controlling the speeds of the feeding rollers, the apron rollers and the spindle, we can manipulate the blending ratio, linear density and twist of the spun yarn online, offering more degrees of freedom to configure fibers in the spun yarn. Furthermore, we develop a digital control system in conjunction with a CNC ring spinning machine, in which each CNC ring spinning machine serves as a drone machine that receives commands from a central computer. A self-developed management platform is designed to help the client manage these drone machines via online regulation. At last, a series of experiments are conducted to examine the impact of manufacturing parameters on the structures and properties of slub yarn. We found that the descriptive parameters that affect the breaking force of the slub yarn samples are the slub length, slub distance, slub multiplier, and roving ratio. The parameters that affect the breaking elongation are obtained as the slub length, slub distance, slub multiplier, and twist coefficient.

Measuring the Geometrical Parameters of Slub Yarn Using a Computer Vision Based Image Sequencing Technique

This article presents a computer vision method for measuring the geometrical parameters of slub yarn based on yarn sequence images captured from a moving slub yarn. An image segmentation method proposed by our earlier work was applied to segment sequence slub yarn images to obtain overlapping diameter data. Then an image stitching method was proposed to remove the overlapped data based on the normalised cross correlation (NCC) method. In order to detect the geometrical parameters of slub yarn, the frequency histogram , curve fitting, and spectrogram methods were adopted to analyse the sequence diameter data obtained. Four kinds of slub yarn with different geometrical parameters were tested using the method proposed and Uster method. The experimental results show that the detection results for slub amplitude, slub length, slub distance, and slub period obtained using the method proposed were consistent with the set values and Uster results.

Multisection color-blended wool yarn produced by a new three-channel spinning method

By dynamically controlling the feeding amount and feeding ratio of the three feeding rollers with program logical control system under the requirements of yarn spinning parameters, it is possible to effectively configure the final yarn density and the blending ratio of three components to produce multisegment gradient yarns, segment-color yarn, and segment-color slub yarn named as multisegment blending yarns. The yarn-spinning new method was proposed. Different kinds of fancy yarns including gradient yarns, segment color yarns, and slub yarns were produced. The fiber blending effects were demonstrated by slices of yarn cross section, and the surface morphology of yarns were figured out by the photo of yarns. Integrally knitting seamless sweater and different type of pattern were designed and knitted by multisegment blending yarns. The free change of colors along the length direction on a single yarn provides an effective method for integrated rapid design and production of sweaters through mutual design of the overall pattern and the structure of the fabric.

Evaluation of an Intelligent Computer Method for the Automatic Mosaic of Sequential Slub Yarn Images

This paper is the second part of a series reporting the recent development of a computerised method for automatic mosaic sequential yarn images. In our earlier work, an effective method for stitching sequence slub yarn images automatically was developed based on image processing and the normalised cross correlation (NCC) method. 100 image pairs of two kinds of slub yarn were measured in certain specific conditions, such as the frame rate, size of stitching template, etc., and the measurement results were evaluated with the manual method. In this paper, the effects of various influencing factors are numerically examined, including the stitching template size, threshold value, frame rate, and computing time of the mosaic algorithm. The feasibility and accuracy of the fully computerized method were evaluated further under the various influencing parameters. One hundred percent cotton ring spun single slub yarns of 27.8, 15.6, and 9.7 tex were prepared and used for the evaluation. The measurement results obtained by the method proposed are analysed and compared with those measured manually by Adobe Photoshop. The experimental results show that the method proposed can accurately find the stitch position and has a high consistency with the manual method when the matching template is 100 × N pixels, the threshold value T1 ∈ [20, 40] and T2 ∈ [51, 80], and the frame rate is greater than 40 fps.

An intelligent computer method for automatic mosaic of sequential slub yarn images based on image processing

In order to analyze the parameters of slub yarn from sequential images accurately, an automatic image mosaic method is proposed in this paper. In this method, a series of overlapping yarn images, which are captured from a moving slub yarn, are stitched into a panorama automatically. Background subtraction, image segmentation and judgment template traversal methods are applied to preprocess the sequential images for obtaining a test image. Subsequently, certain rows in the bottom of the test image are used as a template image to match the next image. The matching coefficient matrix is calculated between the template image and next image based on the normalized cross-correlation method. In the matrix, the coordinates of the peak value are found as the optimal matching points. Two kinds of slub yarn images captured under 40 fps are stitched by using the proposed method and the manual method, respectively. Finally, an objective method is formulated to evaluate the qualities of the image mosaic by the proposed method. The experimental results show that the proposed method can find the match position accurately and is highly consistent with the manual method.

Multi-objective optimization of parametric combination of injected slub yarn for producing knitted and woven fabrics with least abrasive damage

Purpose This study aims to optimize the parametric combination of injected slub yarn to achieve least abrasive damage on fabrics produced from it. Design/methodology/approach Single base injected slub yarn structural parameters, vis-à-vis slub length, slub thickness and slub frequency, were varied during preparation of yarn samples under this research work. A total of 17 yarn samples were produced according to the Box and Bhenken design of the experiment. Subsequently knitted and woven (using injected slub yarns in the weft only) fabric samples were prepared from these yarns. Yarn and fabric samples were abraded with standard instruments to see the impact of yarn structural parameters on abrasive damage of fabric in terms of fabric mass loss and appearance deterioration. From the test results, empirical models relating to slub parameters and fabric abrasion behavior were developed through a backward elimination regression approach. Subsequently, a set of optimal parametric combinations was derived with multi-objective evolutionary algorithms by using MATLAB software. This was followed by ranking all optimal solutions through technique for order preference by similarity to idle solution (TOPSIS) score analysis. Findings The injected slub yarn’s structural parameters have a strong influence on the abrasive damage of knitted and woven fabric. It is seen that the best suitable parametric combination of slub parameters for achieving the least abrasive damage is not the same for knitted and woven fabric. Practical implications The spinner can explore this concept to find out the best suitable parametric combination during pattern making of injected slub yarn through MATLAB solution followed by TOPSIS score analysis based on their priority of criteria level to ensure better abrasion behavior of fabric produced. Originality/value Optimization of parametric combination of injected slub yarns will help to ensure production of fabric with most resistance to abrasion for specific applications. The studies showed that the optimal solution for woven and knitted fabrics is different. The result indicates that in the case of knitted fabric, comparatively lesser slub thickness is found to be suitable for getting better fabric abrasion resistance, whereas in the case of woven fabric, comparatively higher slub thickness is found suitable for the same.