CN111507943B - Method for detecting broken filaments of polyester filaments - Google Patents
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- 238000012545 processing Methods 0.000 description 6
- 229920000297 Rayon Polymers 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
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- 206010020112 Hirsutism Diseases 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
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- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
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- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
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Abstract
The invention relates to a method for detecting broken filaments of polyester filaments, which comprises the following training stage: acquiring 1-line image x of hairless sample by linear array camera 1 (ii) a Using filter pair x 1 Filtering to obtain y 1 (ii) a To y 1 Carrying out binarization to obtain A 1 (ii) a Statistics A 1 The number of pixels included in the maximum connected region in (2) is set as the diameter d 1 (ii) a Repeating the above steps for N lines of images of the hairless sample to obtain the diameter of the hairless sample { d } n }; using Gaussian distribution pairs { d n Model mu and sigma 2 (ii) a (2) Using mu and sigma 2 And (3) detection: collecting K-line images { x) of to-be-detected sample through linear array camera k }; filtering with a filter to obtain y k (ii) a To y k Proceed binarization to obtain B k (ii) a Statistics B k Median diameter { d } k And the number of pixels equal to a' { p } k }; at { d k In (d) k μ + c σ or
C is more than or equal to 3 and less than or equal to 5; broken filaments exist in the sample to be detected; whereas, no broken filaments are present.
Description
Technical Field
The invention belongs to the field of chemical fiber filament quality detection methods, and relates to a method for detecting broken filaments of polyester filaments.
Background
The broken filaments are the main appearance defects of the polyester filament yarns, and the quantity of the broken filaments directly influences the efficiency of downstream weaving and dyeing processes and the quality of finished products. Polyester filaments are generally produced by network processing of a plurality of very small diameter monofilaments, and fuzz is formed by stretching or breaking some of the monofilaments and protruding from the surface of the yarn body due to various external forces. In actual production, the polyester broken filaments are very fine and almost invisible to naked eyes, and can only be detected by visually observing the quantity of the broken filaments on the surface and the end face of the whole spinning cake, so that the detection of the broken filaments in the spinning cake cannot be realized. The existing patent application 201611036029.0 of the method for detecting broken filaments based on image processing is to collect viscose filament images through an industrial area-array camera and carry out a series of image processing operations on the viscose filament images to realize separation and detection of broken filaments, although the detection of the number and the length of the broken filaments can be accurately realized, the calculated amount is large, the detection speed is limited, and the method cannot be used for high-speed online detection.
Therefore, it is very important to develop a method for detecting a hair color with high detection accuracy, high efficiency, and stable detection results.
Disclosure of Invention
The invention provides a method for detecting broken filaments of polyester filaments, and aims to solve the problems in the prior art. The invention realizes the purpose of quickly and accurately detecting the position of broken filaments by acquiring the images of the polyester filaments through the linear array camera and quickly processing and analyzing each row of data.
In order to achieve the purpose, the invention adopts the following scheme:
a method for detecting polyester filament yarn broken filaments comprises the following steps:
(1) a training stage:
(1.1) acquiring 1 line of images of the hairless sample by using a line scan camera, and recording the images as x 1 ，x 1 ∈R m (R m Is a real space of m dimensions, representing x 1 Is a vector of dimension m, m being a positive integer);
(1.2) Using filters F vs. x 1 Performing a filtering operation to obtain y 1 (ii) a Filter F ═ 11111]；y 1 ∈R m (R m Is a real space of m dimensions, representing y 1 Is a vector of m dimensions, m being a positive integer);
(1.3) calculating y 1 Is the average value of
(1.4) binarization: by using
For y 1 Proceed binarization by more than
The assigned value of the pixel point is a and is less than or equal to
The pixel point is assigned as b to obtain a binary image A 1 ；
(1.5) obtaining diameter: statistics A 1 And A is a connected region of 1 The number of pixels contained in the maximum communication area in the polyester fiber is taken as the diameter of the polyester filament and is recorded as d 1 ；
(1.6) acquiring N-line images of the hairless sample through the line scan camera, and recording the N-line images as { x n N, N is a positive integer, 1,2,3, … …; x is the number of n ∈R m (R m Is a real space of m dimensions, x n Is a vector of dimension m, m being a positive integer); repeating the steps (1.1) - (1.5); the diameter of the polyester filament in the N-line image of the hairless sample is noted as { d n }；
(1.7) modeling: using pairs of Gaussian distributions { d n Modeling is carried out to obtain the mean value mu and the variance sigma of the Gaussian distribution parameters 2 The calculation formula is as follows:
(2) using the parameters mu and sigma obtained during the training phase 2 The detection is carried out by the following steps:
(2.1) respectively acquiring K-line images of the sample to be detected through the linear array camera, and recording the K-line images as { x k Where K is 1,2,3, … …, K being a positive integer; x is a radical of a fluorine atom k ∈R m (R m Is a real space of m dimensions, x k Is a vector of m dimensions, m being a positive integer);
(2.2) Using filters F vs. x k Performing a filtering operation to obtain y k (ii) a Filter F ═ 11111]；y k ∈R m (R m Is a real space of m dimensions, representing y k Is a vector of m dimensions, m being a positive integer);
(2.3) calculating y k Average value of (2) is
(2.4) binarization: by using
For y k Carry out binarization to be greater than
The assigned value of the pixel point is a' and is less than or equal to
The pixel point is assigned as B' to obtain a binary image B k ；
(2.5) obtaining diameter: statistics B k And B is a region of communication in k The number of pixels contained in the maximum communication area in the polyester fiber is taken as the diameter of the polyester filament and is recorded as d k ；
The diameter of the polyester filament yarn in the K-line image of the sample to be detected is { d } k }；
(2.6) statistics B k The number of the middle pixel points equal to a' is recorded as p k ；
Then systemEach binary image B obtained by counting K lines of images of a sample to be detected k The number of middle pixels equal to a' is marked as { p k }；
(2.7) judging broken filaments: at { d k In (f), when d k Mu + c σ or
C is more than or equal to 3 and less than or equal to 5; broken filaments exist in the K-line image of the sample to be detected; otherwise, no broken filament exists in the K-row image of the sample to be detected; wherein σ is σ 2 Solving by opening the square root; the smaller the value of c is, the stricter the judgment condition is, but the misjudgment rate is increased;
the hairless sample and the sample to be tested are filament products with the same specification, and products with different specifications need to be trained and tested again according to the method;
the linear array scanning direction of the linear array camera is perpendicular to the movement direction of polyester filaments in the sample.
According to the method for detecting the broken polyester filament yarns, a is 1, and b is 0.
According to the method for detecting the broken polyester filament yarns, a 'is 1, and b' is 0.
In the above method for detecting the polyester filament broken filaments, the value range of K is as follows: k is more than or equal to 1 and less than or equal to 10. When the K value is larger, the simultaneous judgment of multiple lines of images is indicated, and the detection precision is favorably improved.
The method for detecting the broken polyester filament yarn is characterized in that the value range of N is as follows: 5000 < N < 20000, the larger the N, the better, but the larger the N, the more time-consuming.
The conception of the invention is as follows:
the invention adopts a linear array camera to collect a single-line or multi-line image, and carries out rapid processing and analysis on the single-line or multi-line image, which comprises the following steps: firstly, carrying out single-line or multi-line image analysis on a hairless sample to obtain the diameter of a filament in the hairless sample, and modeling the filament to obtain a parameter value for judging whether a sample to be detected has hairiness; and further, analyzing the single-line or multi-line image of the sample to be detected, judging whether the single-line or multi-line image of the sample to be detected has broken filaments or not through comparison between the sample to be detected and the modeling data, and obtaining the position of the broken filaments in the sample to be detected through the position of the single-line or multi-line image in the sample to be detected. In the invention, Gaussian distribution is adopted to model the diameter of a hairless sample (filament) during modeling, the preparation expression of random variation of the diameter is realized, the false detection caused by noise interference is overcome, and the stability and the accuracy of hairless detection are improved; in addition, compared with the mode of acquiring images by an area-array camera, the detection efficiency of the invention is higher, and the requirement on acquisition conditions is lower, because the image acquisition speed of the area-array camera is limited by the sampling frame frequency, clear acquisition of high-speed moving filament images cannot be realized, and secondly, the requirement on uniformity of a light source is very high due to large image acquisition area of the area-array camera; and the linear array camera is adopted, so that the acquired images can be processed line by line, and the detection precision and stability are greatly improved.
Has the advantages that:
(1) the method for detecting the broken filaments of the polyester filaments adopts the linear array camera to acquire filament images, detects whether broken filaments exist in a sample to be detected or not through rapid processing and analysis of a single-line image, and can detect the positions and the quantity of the broken filaments;
(2) the method for detecting the broken filaments of the polyester filaments can overcome the defects of low manual detection speed and the like, and can meet the requirement of efficient and stable detection of the broken filaments in the polyester filaments in practical application.
Drawings
FIG. 1 is an image of a hairless sample collected in example 1;
FIG. 2 is an image of a fuzz collected in example 1.
FIG. 3 is an image of a hairless sample collected in example 2;
fig. 4 is an image of a haired yarn acquired in example 2, in which 1 is a row for judging whether a haired yarn is present.
Detailed Description
The present invention will be further described with reference to the following embodiments. It should be understood that these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Further, it should be understood that various changes or modifications of the present invention can be made by those skilled in the art after reading the teaching of the present invention, and these equivalents also fall within the scope of the claims appended to the present application.
Example 1
A method for detecting polyester filament yarn broken filaments comprises the following steps:
(1) a training stage:
(1.1) acquiring 1 line of images of a hairless sample (polyester filament with the specification of 189dtex/96f) through a linear array camera, and recording the images as x 1 ，x 1 ∈R 1024 ；
(1.2) Using filters F vs. x 1 Performing a filtering operation to obtain y 1 (ii) a Filter F ═ 11111]；y 1 ∈R 1024 ；
(1.3) calculating y 1 Is the average value of
(1.4) binarization: by using
To y 1 Carry out binarization to be greater than
Is assigned a value of 1, less than or equal to
The pixel point is assigned to be 0 to obtain a binary image A 1 ；
(1.5) obtaining diameter: statistics A 1 And A is a connected region of 1 The number of pixels contained in the maximum connected region in the middle is taken as the diameter of the polyester filament yarn and is respectively marked as d 1 ＝41；
(1.6) acquiring 5000 lines of images (wherein the images of continuous 300 lines are shown in figure 1) of the hairless sample by the line scan camera, and recording the images as x n Where n is 1,2,3, … … 5000, n is a positive integer, x n ∈R 1024 (ii) a Repeating the steps (1.1) - (1.5); the diameter of the polyester filament in the 5000 line image of the hairless sample is noted as { d } n }；
(1.7) modeling: using pairs of Gaussian distributions { d n Modeling to obtain mu and sigma 2 ：
(2) Using parameters mu and sigma obtained during the training phase 2 The detection is carried out by the following steps:
(2.1) respectively acquiring 10 lines of images of a sample to be detected (polyester filament yarn with the specification of 189dtex/96f) through a linear array camera, and recording the images as { x k Where k is 1,2,3, … …, 10; x is the number of k ∈R 1024 ；
(2.2) Using filters F vs. x k Performing a filtering operation to obtain y k (ii) a Filter F ═ 11111]；y k ∈R 1024 ；
(2.3) calculating y k Is the average value of
(2.4) binarization: by using
To y k Carry out binarization to be greater than
Is assigned a value of 1, less than or equal to
The value of the pixel point is set to be 0, and a binary image B is obtained k ；
(2.5) Obtaining the diameter: statistics B k And B is a region of communication in k The number of pixels contained in the maximum communication area in the polyester fiber is taken as the diameter of the polyester filament and is recorded as d k ；
The diameter of the polyester filament yarn in the 10 lines of the acquired images of the sample to be detected is { d k }＝{32,31,33,35,31,36,35,37,35,33}；
(2.6) statistics B k If the number of the middle pixel points is equal to 1, each binary image B obtained from 10 lines of images of the sample to be detected k The number of middle pixels equal to 1 is marked as { p k }＝{35,33,35,38,32,42,38,37,36,38}
(2.7) judging broken filaments: at { d k In due to
Then there are broken filaments in the 10 rows of images of the sample to be tested, and the images of the broken filaments are shown in fig. 2 (in order to completely display the area of the broken filaments, fig. 2 includes 21 10 rows of images in which the broken filaments exist continuously).
Example 2
A method for detecting polyester filament yarn broken filaments comprises the following steps:
(1) a training stage:
(1.1) acquiring 1 line of images of a hairless sample (polyester filament, 167dtex/128f) by a linear array camera, and recording the images as x 1 ，x 1 ∈R 1024 ；
(1.2) Using filters F vs. x 1 Performing a filtering operation to obtain y 1 (ii) a Filter F ═ 11111]；y 1 ∈R 1024 ；
(1.3) calculating y 1 Is the average value of
(1.4) binarization: by using
For y 1 Carry out binarization to be greater than
Is assigned a value of 1, less than or equal to
The value of the pixel point is 0 to obtain a binary image A 1 ；
(1.5) obtaining diameter: statistics A 1 And A is a connected region of 1 The number of pixels contained in the maximum connected region in the middle is taken as the diameter of the polyester filament yarn and is respectively marked as d 1 ＝32；
(1.6) acquiring 20000 rows of images (wherein the images of 300 continuous rows are shown in FIG. 3) of the hairless sample by the line scan camera, and recording as { x n Where n is 1,2,3, … … 20000, n is a positive integer, x n ∈R 1024 (ii) a Repeating the steps (1.1) - (1.5); the diameter of the polyester filament in 20000 rows of image of the sample without broken filament is marked as { d n }；
(1.7) modeling: using pairs of Gaussian distributions { d n Modeling is carried out to obtain the mean value mu and the variance sigma of the parameters of Gaussian distribution 2 ：
(2) Using the parameters mu and sigma obtained during the training phase 2 The detection is carried out by the following steps:
(2.1) respectively acquiring 1 line of images of a sample to be detected (polyester filament with the specification of 167dtex/128f) through a linear array camera, and marking as { x } 1 }，x 1 ∈R 1024 ；
(2.2) Using filters F vs. x 1 Performing a filtering operation to obtain y 1 (ii) a Filter F ═ 11111]；y 1 ∈R 1024 ；
(2.3) calculating y 1 Is the average value of
(2.4) binarization: by using
For y 1 Carry out binarization to be greater than
Is assigned a value of 1, less than or equal to
The value of the pixel point is set to be 0, and a binary image B is obtained 1 ；
(2.5) obtaining diameter: statistics B 1 And B is a region of communication in 1 The number of pixels contained in the maximum communication area in the polyester fiber is taken as the diameter of the polyester filament and is recorded as d 1 ＝89；
(2.6) statistics B 1 If the number of the middle pixel points is equal to 1, obtaining a binary image B from the 1-line image of the sample to be detected 1 The number of the middle pixel points equal to 1 is recorded as p k ＝89；
(2.7) judging broken filaments: at { d 1 In due to d 1 If the image is more than μ + c σ (i.e. 89 is more than 61.72, where c is 4), the image of the broken filament in 1 line of the sample to be tested is shown in fig. 4 (in order to completely display the area of the broken filament, fig. 4 shows the images of the adjacent lines in front and back).
Claims (3)
1. A method for detecting polyester filament yarn broken filaments is characterized by comprising the following steps:
(1) a training stage:
(1.1) acquiring 1 line of images of the hairless sample by using a line scan camera, and recording the images as x 1 ，x 1 ∈R m ，R m Is a real space of m dimensions, representing x 1 Is a vector of m dimensions, m being a positive integer;
(1.2) Using filters F vs. x 1 Performing a filtering operation to obtain y 1 (ii) a Filter F ═ 11111]；y 1 ∈R m ；
(1.3) calculating y 1 Average value of (1), noteIs composed of
(1.4) binarization: by using
For y 1 Proceed binarization by more than
Is assigned a value of 1, less than or equal to
The value of the pixel point is 0 to obtain a binary image A 1 ；
(1.5) obtaining diameter: statistics A 1 And A is a connected region of 1 The number of pixels contained in the maximum communication area in the polyester fiber is taken as the diameter of the polyester filament and is recorded as d 1 ；
(1.6) acquiring N-line images of the hairless sample through the line scan camera, and recording the N-line images as { x n Wherein N is 1,2,3, … …, N; x is a radical of a fluorine atom n ∈R m (ii) a Repeating the steps (1.1) - (1.5); the diameter of the polyester filament in the N-line image of the hairless sample is noted as { d n }；
(1.7) modeling: using pairs of Gaussian distributions { d n Modeling is carried out to obtain mean value mu and variance sigma of Gaussian distribution parameters 2 ：
(2) Using parameters mu and sigma obtained during the training phase 2 The detection is carried out by the following steps:
(2.1) respectively collecting K lines of samples to be detected by a linear array cameraImage, noted as { x k Where K is 1,2,3, … …, K; x is the number of k ∈R m ；
(2.2) Using filters F vs. x k Performing a filtering operation to obtain y k (ii) a Filter F ═ 11111]；y k ∈R m ；
(2.3) calculating y k Is the average value of
(2.4) binarization: by using
For y k Carry out binarization to be greater than
Is assigned a value of 1, less than or equal to
The assigned value of the pixel point is 0, and a binary image B is obtained k ；
(2.5) obtaining diameter: statistics B k And B is a region of communication in k The number of pixels contained in the maximum communication area in the polyester fiber is taken as the diameter of the polyester filament and is recorded as d k ；
The diameter of the polyester filament yarn in the K lines of images of the sample to be detected is { d k }；
(2.6) statistics B k The number of the middle pixel points equal to 1 is recorded as p k ；
Then each binary image B obtained by counting K lines of images of the sample to be detected k The number of middle pixels equal to 1 is marked as { p k }；
(2.7) judging broken filaments: at { d k In (f), when d k μ + c σ or
C is more than or equal to 3 and less than or equal to 5; broken filaments exist in the K lines of images of the sample to be detected; otherwise, the sample to be testedNo broken filament exists in the K lines of images;
the hairless sample and the sample to be detected are filament products with the same specification;
the linear array scanning direction of the linear array camera is perpendicular to the movement direction of polyester filaments in the sample.
2. The method for detecting the broken polyester filament yarns according to claim 1, wherein the value range of K is as follows: k is more than or equal to 1 and less than or equal to 10.
3. The method for detecting the broken polyester filament yarns according to claim 1, wherein the value range of N is as follows: n is more than or equal to 5000 and less than or equal to 20000.
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| CN103759662A (en) * | 2013-12-31 | 2014-04-30 | 东华大学 | Dynamic textile yarn diameter rapid-measuring device and method |
| CN106709927A (en) * | 2016-12-27 | 2017-05-24 | 浙江大学 | Method for extracting target from acoustic image under complex background |
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| CN103759662A (en) * | 2013-12-31 | 2014-04-30 | 东华大学 | Dynamic textile yarn diameter rapid-measuring device and method |
| CN106709927A (en) * | 2016-12-27 | 2017-05-24 | 浙江大学 | Method for extracting target from acoustic image under complex background |
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| 图像处理技术在粘胶长丝毛丝自动检测系统中的应用;余恒炜等;《自动化技术与应用》;20171231;第36卷(第09期);第90-92页 * |
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