Color matching of fiber blends: Stearns‐Noechel model of digital rotor spun yarn

Abstract

Stearns‐Noechel model was utilized as a primary reference to study color matching principles of digital rotor spun yarn. Three primary colored (red, yellow and blue) cotton fibers were used to spin blended yarns. Spectral reflectance of the two‐component and three‐component samples was measured with data color spectrophotometer. For these samples, the Stearns‐Noechel model parameter M was determined. Four methods were employed to calculate the M value to improve accuracy of the model, 1.Classical method, named as M1; 2.Optimizing the M1 value obtained by the classical method considering the wavelength factor, named as M2; 3.Simplified M2 according to the linear correlation with the wavelength, named as M3; 4. Simplified M2 according to the segmentation correlation with the wavelength, named as M4. The study shows that average color difference of the two‐component decreases from 2.7 to 1.48, and for three‐component samples from 3.32 to 1.66, by using M2 instead of M1. While calculated using M3, the color difference of the two types of samples will be 1.73 and 2.19, correspondingly. This cannot meet color matching needs. As for M4, the average color difference of the two categories will be 1.54 and 1.91, better than the result obtained using M1 and M3, worse than M2.

Colour matching for smart and sustainable spinning of coloured textiles

“…On this basis, models that demonstrate the relationships between the blending recipes and desired colours are built to improve efficiency, and studies have been conducted in this field for decades. Among them, 8‐10 Stearns and Noechel proposed an empirical formula based on the summation formula to explain the blending colour characteristics of fabrics produced by precoloured black and white wool fibres. Their formula—named the S‐N model—was developed with extensive experimental data.…”

Towards the design of a blending system for precoloured fibres

“…However, to develop a commercially viable system it is necessary to have models that can predict the colour of blends, given the colour of the primaries used in the blend and their proportional amounts. Fortunately, a number of methods have been shown to be able to predict the colour of fibre blends with varying degrees of success, including the Stearns‐Noechel model, the Friele model, the Kubelka‐Munk model and artificial neural networks …”

“…2 However, to develop a commercially viable system it is necessary to have models that can predict the colour of blends, given the colour of the primaries used in the blend and their proportional amounts. Fortunately, a number of methods have been shown to be able to predict the colour of fibre blends with varying degrees of success, including the Stearns-Noechel model, 3,4 the Friele model, 5,6 the Kubelka-Munk model [7][8][9] and artificial neural networks. [10][11][12][13] However, in addition to the problem of colour prediction, there is also the issue of how many primaries are required to essentially cover the normal gamut of coloured textiles, and how these should these be distributed in colour space.…”

K‐M theory of fabric knitted by three‐channel rotor spun wool yarn

“…Color matching blends of precolored fibers have been researched for decades. Several methods have been introduced to describe the color blending of precolored fibers, such as Kubelka‐Munk theory, Friele equation and Stearns‐Noechel model . In recent years, many people have used K‐M to study blending effects with different fiber materials and have achieved satisfactory results.…”

“…Several methods have been introduced to describe the color blending of precolored fibers, such as Kubelka-Munk theory, 4,5 Friele equation 6,7 and Stearns-Noechel model. [8][9][10] In recent years, many people have used K-M to study blending effects with different fiber materials 11,12 and have achieved satisfactory results. According to the previous study of K-M, there were two methods for solving the absorption coefficient (K) and the scattering coefficient (S) of monochromatic fibers in color blended yarns or fabrics, namely, the least squares method and the relative value method.…”