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Digital method for detecting yarn diameter and yarn evenness

A technology for evenness and yarn, applied in image data processing, instruments, calculations, etc., can solve the problems of subjective factors, complicated and cumbersome processes, and difficulty in evaluating yarn grade quality, and achieve the effect of improving accuracy.

Pending Publication Date: 2019-09-17
YANTAI NANSHAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the commonly used yarn diameter and unevenness detection methods, the process is complicated and cumbersome, and is easily affected by the subjective factors of the testing staff, which makes it difficult to evaluate the quality of yarn grades; in addition, capacitive yarn unevenness The measurement method is also easily affected by various factors such as the test environment and the temperature and humidity of the sample to be tested, and it is also difficult to truly and accurately evaluate the yarn quality

Method used

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  • Digital method for detecting yarn diameter and yarn evenness
  • Digital method for detecting yarn diameter and yarn evenness
  • Digital method for detecting yarn diameter and yarn evenness

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0040] Embodiment 1, to the cotton yarn that ring-spinning, carding process is combing, and yarn density is 14.21tex for yarn forming mode, Epson V700 Photo type scanner is connected with computer by USB3.0 data cable, and scanner is distinguished The rate is set to 1200dpi, and a monochrome image with an image resolution of 500pi×500pi is obtained. Such as figure 1 shown.

[0041] Gray-scale processing: Under the windows system and the MATLAB software environment, the arithmetic weighting algorithm as shown in formula (1) written by the inventor is used to convert the RGB image into a gray-scale image.

[0042] The method of the arithmetic weighted average algorithm is to carry out weighted average according to the values ​​of the RGB image on the three channels of R, G, and B according to a certain weighted proportion, and then map the weighted value to obtain the gray value to obtain the gray image. The sensitivity of the human sensory system to different colors is differ...

Embodiment 2

[0068] Embodiment 2, for such as Figure 5 As shown in the image after median filtering, the adaptive threshold segmentation method is used to segment the yarn and the background, and a position is selected between the two peaks, for example, the position in the middle of the two peaks. In general, choosing the peak is more reliable than the valley, which can reduce the interference of noise, the obtained image segmentation effect is more ideal, and the yarn backbone image is clearer. Such as Figure 6 shown.

[0069] right Figure 6 The image segmented by the adaptive threshold segmentation method is subjected to morphological processing, such as Figure 7 shown.

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
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Abstract

The invention provides a digital method for detecting yarn diameter and yarn evenness. The method comprises the steps of collecting a yarn image, preprocessing the image, segmenting the preprocessed image, carrying out morphological processing on the segmented image, and analyzing and calculating the morphologically processed image. The method is characterized in that image preprocessing is completed in a windows system and an MATLAB software environment, and the method comprises three steps of gray processing, gray correction and self-adaptive median filtering, wherein the gray scale processing adopts a compiled arithmetic weighting algorithm program function, the gray scale correction calls an imhist function in MATLAB to calculate an image gray scale score, a corresponding histogram is obtained, equalization processing is carried out on the histogram, and the adaptive median filtering denoising algorithm is used for processing a yarn image, so that the yarn diameter can be accurately and efficiently calculated, and the yarn evenness rate of the yarn can be measured.

Description

technical field [0001] The invention relates to the technical field of textiles, in particular to a digital method for detecting yarn diameter and evenness unevenness. Background technique [0002] Yarn diameter and evenness unevenness are important parameters that affect the appearance quality of yarn, fabric and clothing style, and play a pivotal role in the process design and production of textiles. Yarn appearance parameters mainly include yarn hairiness, fineness, diameter irregularity, etc. These parameters not only directly affect the physical properties of yarn strength, stretchability, abrasion resistance, etc., but also affect the apparent style of the fabric. In the commonly used yarn diameter and unevenness detection methods, the process is complicated and cumbersome, and is easily affected by the subjective factors of the testing staff, which makes it difficult to evaluate the quality of yarn grades; in addition, capacitive yarn unevenness The measurement metho...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/62G06T5/00G06T5/40
CPCG06T7/0004G06T7/62G06T5/40G06T2207/30124G06T5/90G06T5/70
Inventor 王晓侯如梦高晓艳刘美娜辛斌杰
Owner YANTAI NANSHAN UNIV
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