The short fiber content (SFC) in raw cotton is an extremely important attribute in the modern cotton classification system, because of its impact on the quality of yarn manufacturing. However, the current SFC measuring methods are costly, time-consuming and tedious for accurate and quick testing. This study aimed to develop a new way to calculate a weight-based short fiber content (SFCw) from a dual-beard specimen via image-processing and bell-shaped fibrogram modeling techniques. A sample from a cotton sliver was clamped and combed in the opposite directions to form two tapered fringes, and then scanned on a desktop scanner to generate a dual-beard image (DBI). The grayscale values in each column of the DBI were accumulated to derive a bell-shaped fibrogram representing the fiber quantity distributions over the distance from the fibrogram center. Based on the fibrogram, a special hierarchical model was proposed to calculate SFCw in two different length limits—12.7 and 16 mm—defined respectively in the USA and China’s specifications. Fifteen samples were tested to compare the SFCw results from the DBIs to those from the Advanced Fiber Information System (AFIS PRO2). Significant correlations were found between the SFCw values from DBIs and AFIS. The regressive equations for SFCw prediction were validated with six additional samples. As shown in the Bland–Altman plots, a good agreement existed between the two sets of SFCw values, demonstrating the DBI’s potential to be an accurate, rapid and portable approach for measuring SFCw, and to transform the SFCw testing from a dedicated machine to an off-the-shelf scanner.
The random beard image method is a newly developed fiber length measurement method with the advantages of speed, reliability and low cost. This paper proposed the methods of acquiring an accurate and stable fibrogram from the transmission image with the random beard image method based on the derived Kubelka–Munk theory. In the dual-beard preparation process, the optical properties of the short fiber region in the beard were changed by the napping effect. To solve this problem, an imitating experiment with five types of wool fibers was designed to obtain the optical coefficient of the maximum value of the fibrograms of 1.03. To eliminate the random error of the sample, the symmetry principle was adopted to determine the start line of the dual-fibrogram, and the weighted smoothing average fibrogram from two dual-beards is used as the final fibrogram. In addition, upon testing 20 types of wool fiber samples by the random beard image method and the international standard instrument Almeter100, the waviness coefficient of 1.10 was determined. A Z-test and Bland–Altman plot were also applied to verify the accuracy and repeatability of the random beard image method. The results show that under the significance level α = 0.05, the accuracy and the repeatability of the two methods are at the same level. This method sets the foundation for measuring the fiber length distribution parameters, especially the short fiber content.
In this paper, an economical way for accurately determining weight-based short fiber contents in raw cotton and semi-finished slivers by utilizing special bilateral beard specimens and image processing was introduced. In the specimen preparation, cotton fibers were drawn by a manual device into a sliver, then the sliver was combed to form a bilateral beard specimen, and finally the bilateral beard was scanned to generate a grayscale image from which a relative fiber number curve was extracted. An algorithm for calculating the weight-based short fiber contents based on the curve was proposed. Five types of cottons were repetitively measured to investigate the robustness of the results of [Formula: see text] and [Formula: see text], with the weight ratio of fibers shorter than 12.7 and 16 mm, respectively. The results showed that measuring two bilateral beards for each sample could keep the error rate lower than 15%, while four specimens kept the error rate lower than 10%. Compared with AFIS Pro 2, this Image-based Bilateral Beard Method provided results with lower standard deviations and variable coefficients, signifying its analogous or better robustness. In addition, 37 samples from some of the world’s major producing areas were measured by this method and AFIS Pro 2, and a Bland–Altman analysis confirmed a good agreement between the results from the two methods. As only a manual fiber drawing device and an office scanner are needed, this Image-based Bilateral Beard Method is clearly a cheap approach for accurately determining the short fiber contents in raw cotton and semi-finished slivers.
The dual-beard image method, which has been developed in recent years as a fast and economical method for fiber length measurement, consists of dual-beard specimen preparation, image processing, fibrogram extraction, and length parameter calculations. However, one of the shortcomings of this method is that it can only produce extremely limited length parameters such as mean length, coefficient of variation, modal length, and quality length (UHML, upper half mean length). This study introduces a new algorithm for converting the dual-beard fibrogram into a length distribution histogram which can be used to calculate most of the current length parameters. The algorithm is based on the short fiber content formulae but modified by theoretical analysis and experimental comparison. The length distributions of 24 cotton samples and 12 wool samples are measured by dual-beard image method with the new algorithm, and Advanced Fiber Information System (AFIS) and Almeter are employed for comparison. Comparative analysis shows that the peaks and ranges of the distribution histograms using the dual-beard method are similar to those from the reference methods, and the shapes of histograms from difference methods match well with one another. In addition, five length parameters calculated from the dual-beard distributions are verified to be consistent with those measured by AFIS and Almeter. The new algorithm employed in the dual-beard image method avoids the differential operation which amplifies the curve error, giving the dual-beard image method the ability to output more comprehensive length information.
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