Study On Properties And Blending Efect Of Digital Rotor Spun Color-Blend Wool Yam

The color spinning yarn presents a unique color space mixing effect in appearance,full of obscure three-dimensional effect and texture.It can reduce environmental pollution due to its shorted production process,and meet consumers’ individualized and green consumption concept.As a new method of producing color mixed yarn,digital rotor spinning technology synchronizes color mixing during spinning.Its production process is shorter,and it’s production has the advantage of small batch,various type and frequent replacement,thus it has a good developing prospect.However,the digital rotor spinning technology also has the problems of complicated and low efficient color matching procedures.Based on the theoretical model of computer color matching,this paper studies the color prediction model and formula prediction algorithm of knitting fabrics and woven fabrics produced by digital rotor-spun color blended wool yarn,and provides a theoretical reference for further research on computer intelligent color matching of digital rotor-spun color blended wool fabrics.This paper briefly introduces the unique three-channel feeding device and color mixing method of the digital rotor spinning machine,which uses the online control system to develop various color yarns with different blending ratio or linear density.The distribution of colored fibers in the yarn were observed with the microscope.The basic properties such as hairiness,strength and strip dryness of the mixed yarns with the same linear density and blending ratio were tested.The results showed that the fibers of different colors are evenly distributed in the yarn in a single fiber or small bundle shape,indicating that the new color mixing method of digital rotor spinning can effectively mix colored fibers.The properties of different color mixing yarns with different mixing ratios are slight difference,but the difference is not significant,indicating that blending ratios have little influence on the properties of yarns.Red,yellow and blue wool fibers are used to spin the mixed yarn with a gradient of 10%,and color chart of the yarn and fabric are made.The color of the fabric and its changing prinples were demonstrated by the color chart.Knitted fabrics and woven fabrics exhibit different fabric styles due to the different weaving methods.Then,the color matching rules of digital rotor spun color-wool-blended knitted fabrics and woven fabrics are studied by Kubelka-Munk double constant theoretical model,Stearns-Noechel model and Friele model respectively.Based on the Kubelka-Munk double constant theory,the absorption coefficient K and the scattering coefficient S of the monochromatic fabric are calculated by the least squares method and the relative value method respectively.The color difference of the samples is almost the same with the above mentioned two methods.On the other hand,the relative value method is more stable in predicting the color of the samples.Therefore,the fabric color is matched on the basis of the K and S values obtained by the relative value method.The average ratio errors of the knitted sample and the woven sample are 2.87% and 2.78%,respectively.The average color difference of predicted samples is respectively is 0.531 and 0.441,which indicates that the color matching results are good.Knitting fabrics and woven fabrics have the same M value of 0.190 for the optimal parameters of the Stearns-Noechel model.The average error of the sample fabrics is 3.66% and 4.93% with the full-spectrum color matching method,which is slightly larger than the relative value method.The average color difference of the predicted sample is 0.25 and 0.287,which is small,and the color difference of each sample is less than 0.5,indicating that the prediction result is ideal.In the band above 600 nm,the linear correlation between M value and wavelength is strong,and the correlation between other bands is poor.The optimal parameters σ for the Friele model of knitted fabrics and woven fabrics are 0.125 and 0.141,respectively.The average error of the samples is 3.94% and 2.95%,and the predicted average color difference is 0.59 and 0.8.Compared with other the two models,the color difference predicted by Friele model is larger,and the color matching accuracy is poorer.