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The colours and patterns of coloured textiles are usually obtained via dyeing or printing processes. However, these processes consume large amounts of electricity and cause water pollution, which affects the ecological environment. The hand feel of dyed fabrics is superior to that of printed fabrics. Three-channel rotor spinning is a highly flexible, adaptable and sustainable method for producing coloured textiles by blending precoloured fibres during the spinning process. Additionally, the process requires approximately half the water required for fabric dyeing or printing. Herein, the colour characteristics, as well as the advantages, of the coloured textiles produced by the new method are demonstrated. Three types of Stearns-Noechel models are modified to describe the relationship between the blending ratios and resulting textile colours. The colour-matching accuracy is high. As demonstrated by the results, the threechannel rotor spinning method can effectively promote coloured textile engineering.Processes which make coloration cheaper, simpler and highly flexible, in addition to being more sustainable, have never been more attractive. The approach outlined in this Feature article could be one of them. It involves AbstractThe colours and patterns of coloured textiles are usually obtained via dyeing or printing processes. However, these processes consume large amounts of electricity and cause water pollution, which affects the ecological environment. The hand feel of dyed fabrics is superior to that of printed fabrics. Three-channel rotor spinning is a highly flexible, adaptable and sustainable method for producing coloured textiles by blending precoloured fibres during the spinning process. Additionally, the process requires approximately half the water required for fabric dyeing or printing. Herein, the colour characteristics, as well as the advantages, of the coloured textiles produced by the new method are demonstrated. Three types of Stearns-Noechel models are modified to describe the relationship between the blending ratios and resulting textile colours. The colour-matching accuracy is high. As demonstrated by the results, the three-channel rotor spinning method can effectively promote coloured textile engineering.

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.

Two‐component and three‐component color blended yarns were spun by red, yellow, and blue wool slivers using a three‐channel rotor spun machine, and the corresponding plain fabrics were knitted. The color‐matching models of K‐M theory were built with the relative method and the least squares method, respectively. Colors and blending ratios of the fabrics were predicted by the model. The results showed that the average color differences of the samples predicted by the two methods are both about 1.0 and the mean value of the proportional error is below 3%. The least squares method has a better color‐matching effect for the three‐component sample, and the relative value method has better color‐matching results for the two‐component sample. When the tolerance range is 2.0, the pass rates of the samples predicted by either the relative value method or the least squares method reach 100%.

Model de asortarea culorilor țesăturilor produse cu fire multicolore de lână filate cu rotor Firele multicolore de lână au fost filate prin tehnologia de filare cu rotor cu 3 canale și a fost studiată caracteristica de culoare a țesăturii obţinută din aceste fire. Firele cu diferite rapoarte de amestecare a culorilor sunt filate din semitorturi pure de lână roșie, galbenă și albastră și apoi țesute. Modelarea amestecului de culori pentru ţesătura obţinută, corespunzător teoriei constante duble Kubelka-Munk, a fost realizată folosind două metode distincte: metoda celor mai mici pătrate și metoda valorii relative. Modelul a fost verificat prin calcularea diferenței de culoare dintre proba de țesătură și proporția de amestecare a fibrelor colorate. Rezultatele au arătat că diferențele medii de culoare ale probelor obţinute prin modelare sunt mai mici de 1,0, folosind oricare dintre metode. Eroarea medie a raportului de amestecare a fibrelor colorate, calculată utilizând modelul prin metodele de mai sus, este de 1,77% și, respectiv, de 2,38%. Se poate concluziona că, în comparație cu metoda valorii relative, metoda celor mai mici pătrate este mai bună pentru modelul K-M, în scopul predincţiei efectului de amestecare a culorilor și pentru raportul de amestecare al probelor. Cuvinte-cheie: teoria K-M, efect de amestecare, predincţie, diferența de culoare, raport de amestecare Color matching model of woven fabric produced by multi-color blended rotor spun wool yarn Multi-color blended wool yarn was spun by three-channel rotor spinning technology, and the color feature of the corresponding woven fabric was studied. Blended yarns with different color mixing ratios are spun by pure rovings of red, yellow and blue wool, and then woven as fabric. The color blending model of Kubelka-Munk double constant theory for the woven fabrics was established using two methods: least squares method and relative value method. The model was verified by calculating color difference of the fabric sample and the blending proportion of colored fiber. The results showed that mean color differences of the samples predicted by the model is less than 1.0 using either method. The average blending ratio error of the colored fibers calculated using the model by the above methods is 1.77% and 2.38%, respectively. It can be obtained that compared with relative value method, the least squares method is better for K-M model to predict color blending effect and the blending ratio of the samples.