CN113804702B - Copper wire arrangement detection method based on visual intelligent analysis - Google Patents
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- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 title claims abstract description 98
- 238000001514 detection method Methods 0.000 title claims abstract description 39
- 230000000007 visual effect Effects 0.000 title claims abstract description 16
- 238000000034 method Methods 0.000 claims abstract description 21
- 229910052802 copper Inorganic materials 0.000 claims description 12
- 239000010949 copper Substances 0.000 claims description 12
- 238000006073 displacement reaction Methods 0.000 claims description 8
- 238000001914 filtration Methods 0.000 claims description 6
- 230000009466 transformation Effects 0.000 claims description 4
- 230000011218 segmentation Effects 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 abstract description 14
- 238000005491 wire drawing Methods 0.000 abstract description 8
- 238000003384 imaging method Methods 0.000 abstract description 4
- 230000002159 abnormal effect Effects 0.000 abstract description 3
- 238000012423 maintenance Methods 0.000 abstract description 3
- 238000007689 inspection Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000004804 winding Methods 0.000 description 2
- 230000003044 adaptive effect Effects 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
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- 238000007781 pre-processing Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 208000024891 symptom Diseases 0.000 description 1
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- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
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- G06T7/10—Segmentation; Edge detection
- G06T7/136—Segmentation; Edge detection involving thresholding
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
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- G06T2207/20056—Discrete and fast Fourier transform, [DFT, FFT]
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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Abstract
The invention discloses a copper wire arrangement detection method based on visual intelligent analysis, which comprises the following steps: acquiring a copper wire alignment image to be detected under a blue auxiliary light source, and detecting the wire diameter of the copper wire alignment image to be detected based on a preset detection model; judging whether the wire diameter of the current copper wire exceeds a preset wire diameter threshold value or not based on the obtained wire diameter detection result; and if the wire diameter of the current copper wire exceeds a preset wire diameter threshold value, sending out alarm information. When the system is used, the high-speed camera and the laser camera are used for collecting copper wire information of the wire drawing process of the production line, algorithm analysis is carried out according to the visual imaging system and the image recognition system, the quality of the wire drawing copper wire of the production line can be monitored in real time, the states of finished products and the process of the production line can be displayed to a platform manager in real time through platform information collection, and an alarm notice is sent when the products are abnormal, so that workers are informed of quality maintenance.
Description
Technical Field
The invention belongs to the technical field of machine vision analysis, and particularly relates to a copper wire winding displacement detection method based on vision intelligent analysis.
Background
At present, the quality of copper wires in factories is monitored, mainly through manual inspection, when the distribution of finished coil wires is uneven and the thickness is not uniform, the finished coil wires are judged to be defective, and the copper wires are rewound and returned to the furnace; along with the upgrading and transformation of the current industrial industry, the requirements on quality are continuously improved, and the manual inspection and detection cannot meet the high standard requirements on quality, and meanwhile, precious human resources are occupied, so that the production efficiency of enterprises is influenced, and the production cost of the enterprises is also increased; meanwhile, the manual detection has the following defects:
First, feedback is not timely, equipment state cannot be concerned in real time, and when the quality of a product line changes, the product line cannot be processed timely.
Secondly, the detection is inaccurate, whether the quality of the copper coil on the production line is qualified or not is checked only through manual inspection, when personnel subjectively judge that the copper coil is missing, finished products leave the factory along with goods to a supply chain link, and the goods with poor quality can be returned in batches, so that the enterprise cost and reputation are greatly influenced.
Thirdly, experience and quality inspection information cannot be summarized, a detection log is not formed by manual detection quality, the product yield is not understood in terms of macroscopic trend, and a method and a cutting port are not provided for analyzing the problem symptoms.
Disclosure of Invention
The invention provides a copper wire arrangement detection method based on visual intelligent analysis, which is used for at least solving one of the technical problems.
The invention provides a copper wire arrangement detection method based on visual intelligent analysis, which comprises the following steps: acquiring a copper wire alignment image to be detected under a blue auxiliary light source, and detecting the wire diameter of the copper wire alignment image to be detected based on a preset detection model, wherein the wire diameter detection comprises the following steps: step a, spatial filtering treatment is carried out on the copper wire flat cable image to be detected, so that a treated copper wire flat cable image to be detected is obtained; step b, setting a discrete convolution form of norms of two areas of copper wire spacing with a distance t, wherein the expression of the discrete convolution is as follows:
Where v (x) is the point of the discrete sequence, v (x+t) is the distance to move the discrete sequence by t, k (z) is the point of the mirror sequence, v (x+z) is the distance to move the discrete sequence by z, v (x+t+z) is the distance to move the discrete sequence by t+z, S t is a displacement value, which is a convolution multiplication operator; according to Fourier transform solution, performing two-dimensional rapid transformation to obtain: wherein F is a Fourier series, Is thatThe Fourier series function of the points, F (s t) is the series function of Fourier s t; step c, self-adaptive threshold segmentation is carried out to obtain a binarization image, a copper wire target and a background are segmented, and an inter-class threshold value is obtained according to an algorithm formula, wherein the algorithm formula is as follows: g=ω oω1(u0-u1) ∈2, where g is an inter-class threshold value, ω o、ω1 is a sine function value, and u 0、u1 is a desired value; step d, straight line fitting, obtaining pixel coordinates of the straight line in the image, calculating the copper wire pixel distance,Wherein den is interpolation, lambda is a coefficient to be determined, dxx and Dyy are respectively the product value of the linear mean differences between x coordinates, the product value of the linear mean differences between y coordinates, and D xy is the product value of the linear mean differences between point coordinates; and e, calibrating and calculating to obtain a physical wire diameter value of the copper wire, wherein the expression for calculating the physical wire diameter value of the copper wire is as follows: In the method, in the process of the invention, For the purpose of the calibration value,For fitting the standard deviation value, m and n are limit values of discrete points at two ends of the straight line respectively; judging whether the wire diameter of the current copper wire exceeds a preset wire diameter threshold value or not based on the obtained wire diameter detection result; and if the wire diameter of the current copper wire exceeds a preset wire diameter threshold value, sending out alarm information.
In some embodiments of the present invention, wherein the expression for calculating the displacement value is: Where s t is the displacement value, v (x) is the selected discrete point, and v (x+t) is the distance by which the selected discrete point moves.
In some embodiments of the invention, the method further comprises: and obtaining a copper wire alignment image to be detected under a blue auxiliary light source, and carrying out uniform wire alignment detection on the copper wire alignment image to be detected based on a preset detection model.
In some embodiments of the present invention, performing wire arrangement uniformity detection on the copper wire arrangement image to be detected based on a preset detection model includes: step 1, performing spatial filtering treatment on the copper wire flat cable image to be detected to obtain a treated copper wire flat cable image to be detected; step 2, obtaining a vertical point B (x 2, y 2) of a straight line adjacent to any point A (x 1, y 1) and any point A (x 1, y 1) to a certain straight line on the certain straight line, and obtaining respective straight line equations; step 3, obtaining a perpendicular bisector equation between any point A (x 1, y 1) and a perpendicular bisector B (x 2, y 2), wherein the perpendicular bisector equation is as follows: y= - (x 2-x 1)/(y 2-y 1) x+ (x 2-x 1)/(y 2-y 1) (x1+x2)/2+ (y1+y2)/2; step 4, obtaining the distance between copper wires of the copper wire coil based on an Euclidean distance formula, and determining whether the copper wires of the copper wire coil are uniformly distributed or not by comparing calibrated copper wire distance values, wherein the Euclidean distance formula is as follows: Where ρ is the Euclidean distance between point (X 2,y2) and point (X 1,y1), and |X| is the Euclidean distance of point (X 2,y2) to the origin.
In some embodiments of the present invention, wherein the expression of the linear equation is:
(y-y 1)/(x-x 1) = (y 2-y 1)/(x 2-x 1); k= (y 2-y 1)/(x 2-x 1), where y is an ordinate value, x is an abscissa value, and k is a straight line slope.
According to the copper wire arranging detection method based on visual intelligent analysis, when the copper wire arranging detection method is used, copper wire information of a wire drawing process of a production line is collected by using a high-speed camera and a laser camera, algorithm analysis is carried out according to a visual imaging system and an image recognition system, the quality of the wire drawing copper wire of the production line can be monitored in real time, the states of finished products and the process of the production line can be displayed to a platform manager in real time through platform information collection, and an alarm notification is sent out when the products are abnormal, so that workers are informed of quality maintenance.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a copper wire diameter detection according to an embodiment of the present invention;
FIG. 2 is a front-to-back diagram of filtering noise for an embodiment of the present invention;
FIG. 3 is a diagram of a binarized image obtained by adaptive thresholding in accordance with an embodiment of the present invention;
FIG. 4 is a line fitting diagram of an embodiment of the present invention;
fig. 5 is a flowchart of a copper wire winding uniformity detection according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The application discloses a copper wire arrangement detection method based on visual intelligent analysis, which comprises the following steps: obtaining a copper wire alignment image to be detected under a blue auxiliary light source, and detecting the wire diameter of the copper wire alignment image to be detected based on a preset detection model, wherein as shown in fig. 1, the wire diameter detection comprises the following steps:
Step a, spatial filtering treatment is carried out on the copper wire alignment image to be detected, so that a treated copper wire alignment image to be detected (shown in figure 2) is obtained;
Step b, setting a discrete convolution form of norms of two areas of copper wire spacing with a distance t, wherein the expression of the discrete convolution is as follows: Where v (x) is the point of the discrete sequence, v (x+t) is the distance to move the discrete sequence by t, k (z) is the point of the mirror sequence, v (x+z) is the distance to move the discrete sequence by z, v (x+t+z) is the distance to move the discrete sequence by t+z, S t is a displacement value, which is a convolution multiplication operator; according to Fourier transform solution, performing two-dimensional rapid transformation to obtain: wherein F is a Fourier series, Is thatThe Fourier series function of the points, F (s t) is the series function of Fourier s t;
step c, self-adaptive threshold segmentation is carried out to obtain a binarized image (shown in fig. 3), a copper wire target and a background are segmented, and an inter-class threshold value is obtained according to an algorithm formula, wherein the algorithm formula is as follows: g=ω oω1(u0-u1) ∈2, where g is an inter-class threshold value, ω o、ω1 is a sine function value, and u 0、u1 is a desired value;
Step d, straight line fitting, obtaining the pixel coordinates (shown in figure 4) of the straight line in the image, calculating the copper wire pixel distance, Wherein den is interpolation, lambda is a coefficient to be determined, dxx and Dyy are respectively the product value of the linear mean differences between x coordinates, the product value of the linear mean differences between y coordinates, and D xy is the product value of the linear mean differences between point coordinates;
And e, calibrating and calculating to obtain a physical wire diameter value of the copper wire, wherein the expression for calculating the physical wire diameter value of the copper wire is as follows: In the method, in the process of the invention, For the purpose of the calibration value,For fitting the standard deviation value, m and n are limit values of discrete points at two ends of the straight line respectively; judging whether the wire diameter of the current copper wire exceeds a preset wire diameter threshold value or not based on the obtained wire diameter detection result; and if the wire diameter of the current copper wire exceeds a preset wire diameter threshold value, sending out alarm information.
According to the method, the high-speed camera and the laser camera are used for collecting copper wire information of the wire drawing process of the production line, algorithm analysis is carried out according to the visual imaging system and the image recognition system, the quality of the wire drawing copper wire of the production line can be monitored in real time, the states of finished products and the process of the production line can be displayed to a platform manager in real time through platform information collection, and an alarm notification is sent out when the products are abnormal, so that workers are informed of quality maintenance.
In some optional embodiments, a copper wire alignment image to be detected is obtained under a blue auxiliary light source, and the copper wire alignment image to be detected is subjected to uniform wire alignment detection based on a preset detection model.
As shown in fig. 5, performing uniform detection on the copper wire alignment image to be detected based on a preset detection model includes: step 1, after an image recognition system acquires a high-quality copper wire image, performing image preprocessing, removing image noise points, segmenting copper wires and a background on a wire reel, and performing a denoising algorithm in the same step a;
Step 2, the laser camera obtains distance information of copper wire arrangement on the wire spool, judges whether copper wires are uniformly arranged according to the distance information, and a distance algorithm is to obtain discrete sampling points on 2 adjacent straight lines respectively;
step 3, fitting the straight lines as in step d, taking any point A (x 1, y 1) of the adjacent straight lines on one straight line, and then taking a second point B (x 2, y 2) by making a perpendicular to the other straight line to obtain respective straight line equations:
(y-y1)/(x-x1)＝(y2-y1)/(x2-x1)；k＝(y2-y1)/(x2-x1)，
Where y is the ordinate, x is the abscissa, and k is the slope of the line.
According to the vertical theorem: the slope of the perpendicular bisector is:
-1/k＝-1/[(y2-y1)/(y2-y1)]＝-(x2-x1)/(y2-y1)；
Passing through midpoint C (x 3, y 3) of AB;
x3＝(x1+x2)/2，y3＝(y1+y2)/2；
and 4, obtaining a perpendicular bisector equation between two points, wherein the perpendicular bisector equation is set as follows:
y＝[-(x2-x1)/(y2-y1)]x+b；
substituting x3 and y3:
(y1+y2)/2＝-(x2-x1)/(y2-y1)*(x1+x2)/2+b；
b＝(x2-x1)/(y2-y1)*(x1+x2)/2+(y1-y2)/2；
And obtaining a perpendicular bisector equation:
y＝-(x2-x1)/(y2-y1)x+(x2-x1)/(y2-y1)*(x1+x2)/2+(y1+y2)/2；
From the perpendicular equation, the intersection point B (x 2, y 2) of the perpendicular and the second straight line can be found.
And 5, obtaining the distance between the copper wires of the copper wire coil according to the Euclidean distance formula, and determining whether the copper wires of the copper wire coil are uniformly distributed or not by comparing the calibrated copper wire distance values, and whether the quality of the copper wire coil is qualified or not.
European distance formula:
Where ρ is the Euclidean distance between point (X 2,y2) and point (X 1,y1), and |X| is the Euclidean distance of point (X 2,y2) to the origin.
The distance from the current point to the other straight line can be obtained:
dist＝sqrt((x1-x2)^2+(y1-y2)^2)。
According to the method, the quality of the wire-drawing copper wire arrangement of the production line can be monitored in real time by collecting copper wire information of the wire-drawing process of the production line by using the high-speed camera and the laser camera and performing algorithm analysis according to the visual imaging system and the image recognition system.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (5)
1. A copper wire arranging detection method based on visual intelligent analysis is characterized by comprising the following steps:
Acquiring a copper wire alignment image to be detected under a blue auxiliary light source, and detecting the wire diameter of the copper wire alignment image to be detected based on a preset detection model, wherein the wire diameter detection comprises the following steps:
step a, spatial filtering treatment is carried out on the copper wire flat cable image to be detected, so that a treated copper wire flat cable image to be detected is obtained;
Step b, setting a discrete convolution form of norms of two areas of copper wire spacing with a distance t, wherein the expression of the discrete convolution is as follows:
where v (x) is the point of the discrete sequence, v (x+t) is the distance to move the discrete sequence by t, k (z) is the point of the mirror sequence, v (x+z) is the distance to move the discrete sequence by z, v (x+t+z) is the distance to move the discrete sequence by t+z, S t is a displacement value, which is a convolution multiplication operator;
according to Fourier transform solution, performing two-dimensional rapid transformation to obtain:
wherein F is a Fourier series, Is thatThe Fourier series function of the points, F (s t) is the series function of Fourier s t;
Step c, self-adaptive threshold segmentation is carried out to obtain a binarization image, a copper wire target and a background are segmented, and an inter-class threshold value is obtained according to an algorithm formula, wherein the algorithm formula is as follows: g=ω oω1(u0-u1) a 2,
Wherein g is an inter-class threshold, omega o、ω1 is a sine function value, and u 0、u1 is a desired value;
Step d, straight line fitting, obtaining pixel coordinates of the straight line in the image, calculating the copper wire pixel distance,
Wherein den is interpolation, lambda is a coefficient to be determined, dxx and Dyy are respectively the product value of the linear mean differences between x coordinates, the product value of the linear mean differences between y coordinates, and D xy is the product value of the linear mean differences between point coordinates;
And e, calibrating and calculating to obtain a physical wire diameter value of the copper wire, wherein the expression for calculating the physical wire diameter value of the copper wire is as follows:
In the method, in the process of the invention, For the purpose of the calibration value,For fitting the standard deviation value, m and n are limit values of discrete points at two ends of the straight line respectively;
judging whether the wire diameter of the current copper wire exceeds a preset wire diameter threshold value or not based on the obtained wire diameter detection result;
and if the wire diameter of the current copper wire exceeds a preset wire diameter threshold value, sending out alarm information.
2. The method for detecting copper wire arrangement based on visual intelligent analysis according to claim 1, wherein the expression for calculating the displacement value is:
Where s t is the displacement value, v (x) is the selected discrete point, and v (x+t) is the distance by which the selected discrete point moves.
3. The method for detecting copper wire arrangement based on visual intelligent analysis according to claim 1, further comprising:
And obtaining a copper wire alignment image to be detected under a blue auxiliary light source, and carrying out uniform wire alignment detection on the copper wire alignment image to be detected based on a preset detection model.
4. The method for detecting copper wire flat cable based on visual intelligent analysis according to claim 3, wherein the step of uniformly detecting the flat cable of the copper wire flat cable image to be detected based on a preset detection model comprises the following steps:
Step 1, performing spatial filtering treatment on the copper wire flat cable image to be detected to obtain a treated copper wire flat cable image to be detected;
step 2, obtaining a vertical point B (x 2, y 2) of a straight line adjacent to any point A (x 1, y 1) and any point A (x 1, y 1) to a certain straight line on the certain straight line, and obtaining respective straight line equations;
step 3, obtaining a perpendicular bisector equation between any point A (x 1, y 1) and a perpendicular bisector B (x 2, y 2), wherein the perpendicular bisector equation is as follows:
y＝-(x2-x1)/(y2-y1)x+(x2-x1)/(y2-y1)*(x1+x2)/2+(y1+y2)/2；
step 4, obtaining the distance between copper wires of the copper wire coil based on an Euclidean distance formula, and determining whether the copper wires of the copper wire coil are uniformly distributed or not by comparing calibrated copper wire distance values, wherein the Euclidean distance formula is as follows:
Where ρ is the Euclidean distance between point (X 2,y2) and point (X 1,y1), and |X| is the Euclidean distance of point (X 2,y2) to the origin.
5. The method for detecting copper wire arrangement based on visual intelligent analysis according to claim 3, wherein the expression of the linear equation is:
(y-y1)/(x-x1)＝(y2-y1)/(x2-x1)；k＝(y2-y1)/(x2-x1)，
Where y is the ordinate, x is the abscissa, and k is the slope of the line.
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| CN109801302A (en) * | 2018-12-14 | 2019-05-24 | 华南理工大学 | A kind of ultra-high-tension power transmission line foreign matter detecting method based on binocular vision |
| CN111583114A (en) * | 2020-04-30 | 2020-08-25 | 安徽工业大学 | Automatic measuring device and measuring method for pipeline threads |
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