HSV Color Stereo Construction And Color Yarn Color Prediction Based On Numerical Control Color Blending Spinning

Color yarn is a characteristic yarn that presents rich and colorful three-dimensional effects in appearance,and has a production history of over 30 years in China.Color spinning technology is a spinning technology that involves spinning two or more colored fibers into a certain hue,lightness,and saturation according to a certain mixing ratio.Due to the use of fiber dyeing before spinning process,color spinning technology greatly reduces pollution in the production process and conforms to the production development concept of green and environmental protection.However,due to the inability to achieve intelligent control of yarn color during the spinning stage,there are significant limitations in the actual use of the product.By using a multi-channel digital ring spinning machine to asynchronously draft,gradient color matching,merge and twist three different colored rovings,and achieving the online control of the blending ratio of colored fibers in mixed colored yarns,providing a technical means for the spinning of colored yarns.The color matching of color yarn and fabric involves mixing two or more colored fibers to achieve a visual style and color effect that is consistent with the target yarn or fabric through spinning processes such as carding,drawing,roving,and spinning.Previous color matching models and theories were based on certain assumptions,and the color value of color spun yarn is influenced by multiple factors and has significant nonlinearity,based on these theories,there are often significant deviations in predicting the color values of color spun yarns,so it is necessary to establish a neural network prediction model based on full color gamut chromatography.The main research content and conclusion of this article are as follows:1)Construction of HSV grid color model based on HSV color model: Based on any four primary colors,construct a four primary grid based color mixing model,and assemble it to obtain an eight primary color HSV color stereo model.Divide it into grids and represent the equal lightness surface,equal saturation surface,and equal hue surface in the color stereo.Establish color value algorithms for equal lightness surface,equal hue surface,and equal saturation surface;Use Visual Basic software to visualize the color spectrum of equal lightness surface,equal saturation surface,and equal hue surface,and establish a color decomposition algorithm to obtain the composition and proportion of the four primary colors of any color;2)A full color gamut blending model based on four primary colors of magenta,cyan,yellow,and gray is constructed,and a three factor regulation mechanism of draft ratio,blending ratio,and yarn color value is constructed based on three channel spinning.A spinning method for full color gamut colored yarn is proposed: Based on the dual coupling mixing mode of quaternion variables,four primary colors are Discretization with 12.5% discrete gradient,and a grid model of full color domain based on four primary colors and a control mode based on any four primary colors in eight primary colors are constructed;Introduce the system composition and yarn forming principle of a three channel digital spinning machine,construct a three element control mechanism based on the draft ratio,color mixing ratio,and yarn color value of the three channel digital spinning machine,as well as the process theory and method for spinning full color gamut colored yarn,laying the foundation for subsequent prediction model construction;3)Three series of color yarns with equal lightness,equal hue,and equal saturation were spun to validate the proposed spinning theory: Design the spinning process of full color gamut blended yarn based on four primary color fiber full color gamut chromatography,and spin the blended yarn on a digital ring spinning machine.Analyze the evenness,hairiness,and strength indicators of the blended yarn,and compare it with ordinary natural color yarn to analyze the feasibility of using the full color gamut blended model to spin the colored yarn;Afterwards,using a weft knitting circular machine,the mixed yarn is made into a fabric color card sample,and the color of the fabric is tested using a spectrophotometer;4)Constructed a BP neural network prediction model to predict the color and color ratio of blended yarn: A full color gamut color mixing chromatography based on the dual coupling color mixing mode of four primary colors was constructed with a 12.5% discrete gradient,and this was used as the sample space for the BP neural network color matching model.Based on blending ratio to predict color and color to predict the blending ratio of four primary colors,two prediction models were designed.The sub samples in the sample space were predicted separately,and the mean square error of the four primary color formula ratio and the color difference value of the fabric after sampling were analyzed.It is found that the Mean squared error between the actual color mixing ratio and the predicted color mixing ratio is less than 0.03,and the CMC2:1 color difference is about 2,and validated the feasibility of the color matching model,providing a basis for establishing a computer color prediction model based on the color measurement results of a spectrophotometer.