Method for measuring yarn evenness based on cross section perimeters of yarns

Abstract

The invention relates to a method for measuring yarn evenness based on cross section perimeters of yarns. Unevenness of yarn appearance can be understood and represented from the point of view of the relation between yarns and fabrics, an elliptic yarn cross section model is used as a base, a biaxial CCD camera is used for obtaining images of yarns in two directions which are mutually perpendicular, and further cross section perimeters of yarns and the concrete measurement and calculation method for yarn evenness based on cross section perimeters of yarns are provided. The method can be used for effectively reducing influences of irregular cross sections, hairiness and the like of yarns on evenness measurement of yarn appearance, and is not influenced by temperature and humidity, atmospheric conditions and other extraneous conditions, as well as yarn blending state of optical property differences and the like. Influence of yarn cross section on yarn evenness and a deformation relation in a process from yarn to fabric are fully considered, and the method is good for evaluating consistency between yarn appearance evenness and fabric appearance evenness; and the method can be applied to the fields of objective evaluation of yarn appearance quality and prediction of fabric appearance quality.

Description

technical field [0001] The invention belongs to the field of yarn quality testing methods, in particular to a method for measuring yarn dryness uniformity based on the circumference of a yarn section. Background technique [0002] Yarn dryness evenness is an important indicator for evaluating yarn quality, has an important impact on the appearance quality of fabrics, and is an important factor in determining yarn grade and price. Due to the uneven distribution of fibers in the yarn, the yarn often exhibits periodic or non-periodic unevenness such as knots, thick places, details, and unevenness. Uneven yarn dryness can usually be divided into uneven quality and uneven volume. Uneven yarn quality is caused by uneven fiber fineness and fiber number differences, which is the basis for uneven yarn; fiber volume Unevenness is caused by uneven fiber quality and differences in fiber volume fraction, and is externally manifested as uneven yarn appearance. Uneven appearance of yarn ...

AI Technical Summary

Problems solved by technology

The former can determine the yarn diameter by the difference of electrical signals before and after occlusion, but it cannot eliminate the measurement error caused by yarn hairiness. The latter uses the principle of collected images to further count the number of effective pixels to determine the yarn diameter. Image can be used The processing technology eliminates the error introduced by yarn hairiness, but the disadvantage of this method is that the calculation amount is large and the real-time processing effect is poor

[0004] However, both the photoelectric method and the capacitance method are difficult to obtain the yarn cross-section information, especially the cross-sectional area and cross-sectional circumference of the yarn.

Images