Intelligent manufacturing of color blended yarn: Color matching algorithm and manufacturing process through computer numerically controlled ring spinning system

Cui, Peng; Yue-xing, Liu; Sun, Xianqiang

doi:10.1177/15589250211006539

Cited by 6 publications

(7 citation statements)

References 23 publications

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“…A 3 nh YS3060 spectrophotometer was applied to acquire RGB color values of fibers or yarns under the condition of D65 light source, 10° field of view, SCI mode, 8 mm aperture, and each sample was measured five times and the average value was obtained. 18,19 According to the standard ISO 2060:1994, the yarn length was measured by YG086 Lea’s length tester with a test length of 100 m. The mass of yarn was measured by AL204 electronic balance, and each of them were measured 10 times, and the weight was averaged to get their yarn linear density, and again the average values were taken separately for the yarn linear densities with different hues at the same saturation, different saturation at the same hue, and different hues, lightness and saturation. Subsequently, the YG133B/Pro-H evenness tester was employed to test the evenness with a testing speed of 400 m/min and a length of 400 m, complying with standard ISO 16549:2004.…”

Section: Testing and Analysis Of Colored Yarnsmentioning

confidence: 99%

Construction of circular-shaped chromatic model and spinning of full color gamut colored yarn by digital blending of three primary colored fibers

Sun

Liu²,

Zhang³

et al. 2022

Textile Research Journal

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This paper focuses on the construction of the theory of the spinning process for full color gamut colored yarn. A color stereo model of full color gamut reflecting the variation of hue, lightness and saturation in the process of color mixing is established by digital blending of three primary colored fibers so as to realize the visualization of full color gamut gridded color mixing chromatography. A three-channel computer numerical control spinning method incorporating the yarn color, the blending ratios of three primary colored fibers and multichannel coupling drafting ratios and other parameters is proposed according to the digital twin theory that enables the realization of the spinning of full color gamut colored yarn. A novel spinning technique which mainly consists of controlling the hue, brightness and saturation is used to manufacture full color gamut colored yarns according to the three-channel computer numerical control spinning platform. Three series of colored yarns of different hues with equal saturation, different brightness with equal hues, and different saturation with equal hues were prepared as experimental verification, and the yarn indicators such as color, linear density, unevenness, surface hairiness, and tensile strength were measured, and the reasons for their fluctuations were analyzed.

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Section: Testing and Analysis Of Colored Yarnsmentioning

confidence: 99%

Construction of circular-shaped chromatic model and spinning of full color gamut colored yarn by digital blending of three primary colored fibers

Sun

Liu²,

Zhang³

et al. 2022

Textile Research Journal

View full text Add to dashboard Cite

show abstract

“…The reflectance values of the yarns were obtained using a 3nh YS6010 spectrophotometer under a D65 light source, 10° field of view, 25.4 mm aperture, and in the SCI mode; each sample was measured five times and the average value was determined. 26…”

Section: Experimental Analysismentioning

confidence: 99%

Research on colored yarns for a full color phase mixing model and the Stearns–Noechel color prediction approach

Sun

Shen

et al. 2022

Textile Research Journal

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Using the binary coupled mixing algorithm as the foundation, the full color phase mixing mode of six primary colored fibers is proposed, a full color phase mixing model containing 60 grid points is established, and the corresponding color mixing chromatography is provided. Inside the construction of the full color phase mixing model, 30 grid points are chosen in a gradient of 20%, and 30 colored yarns of six color systems are spun according to the mixing ratios of the binary primary colored fibers corresponding to the grid points. Taking 30 colored yarns as samples, the approach of determining the reflectance conversion coefficient ( M value) with the spectral wavelength and the mixing ratios of binary primary colored fibers as independent variables is derived by the Stearns–Noechel algorithm; a method for predicting the colors of fabrics by the mixing ratios of fibers and predicting the mixing ratios of fibers by the colors of fabrics is proposed. It is demonstrated that the reflectance conversion coefficient in the Stearns–Noechel color prediction equation is related to both the spectral wavelength and the mixing ratios of the primary colored fibers; the colors of the forming yarns can be forecasted using the mixing ratios of the primary colored fibers in the full color phase mixing model, and the mixing ratios of the primary colored fibers in the model can also be predicted by the colors of the yarns.

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“…Recently, many scientists have studied the colour differences of dyed fabrics to improve the automatic production of these fabrics. 1,2 For example, Wang et al 3 proposed a method for producing qualified dyed fabrics with unqualified dyed yarns. Xin et al 4 proposed a method to classify the colour textures of coloured fabrics based on a double-sided back propagation neural network and co-occurrence matrix.…”

Section: Introductionmentioning

confidence: 99%

Classifying colour differences in dyed fabrics using an improved hunger games search optimised random vector functional link

Zhang

Zhou

2022

Journal of Engineered Fibers and Fabrics

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This study proposes an algorithm for classifying colour differences in dyed fabrics using random vector functional link (RVFL) optimised using an improved hunger games search (HGS) algorithm to replace the inefficient traditional classification methods. First, to prevent the HGS algorithm from easily arriving at the local optimal solution, we used the grey wolf optimiser (GWO) to generate the solution set of the HGS algorithm. Subsequently, to reduce the impact of the randomness of the input weight and hidden layer offset on the classification accuracy of RVFL, we used the improved HGS to optimise these two parameters of RVFL. Finally, the RVFL optimised using the improved HGS algorithm is used for classifying the colour differences of dyed fabrics. The performance of the proposed classification algorithm is compared with HGS algorithms improved using the whale optimiser, sine cosine algorithm, and Harris hawks optimiser. The results revealed that the proposed algorithm possesses several advantages, including the maximum, minimum, and average classification errors; good stability; and fast convergence.

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Intelligent manufacturing of color blended yarn: Color matching algorithm and manufacturing process through computer numerically controlled ring spinning system

Cited by 6 publications

References 23 publications

Construction of circular-shaped chromatic model and spinning of full color gamut colored yarn by digital blending of three primary colored fibers

Construction of circular-shaped chromatic model and spinning of full color gamut colored yarn by digital blending of three primary colored fibers

Research on colored yarns for a full color phase mixing model and the Stearns–Noechel color prediction approach

Classifying colour differences in dyed fabrics using an improved hunger games search optimised random vector functional link

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