CN119540322A - Copper foil width detection device and method based on visual recognition algorithm - Google Patents
Copper foil width detection device and method based on visual recognition algorithm Download PDFInfo
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Abstract
The invention discloses a copper foil width detection device and method based on a visual recognition algorithm, wherein the device comprises two cameras which are respectively positioned at two sides of a copper foil to be detected, fixed on a bridge frame and used for collecting image data of edges at two sides of the copper foil; the rear end analysis server receives image data from the camera, performs image data preprocessing, calculates the width of the copper foil through a visual recognition algorithm, and transmits the result to the display screen for display. The device for detecting the width of the copper foil by using the visual recognition algorithm can fully cover the width of the whole copper foil, the images of the edges of the two sides of the copper foil are shot by the camera, and the width is measured by using the image processing algorithm, so that the device has the advantages of non-contact, real-time and high efficiency.
Description
Technical Field
The invention relates to the technical field of industrial automatic detection of copper foil width, in particular to a copper foil width detection device and method based on a visual recognition algorithm.
Background
In the copper foil production process, the width of the copper foil is an important quality index. In order to ensure that the width of each roll of copper foil meets the design requirements, online inspection of the copper foil is required. However, measurement of copper foil width presents certain challenges. The conventional width detection method generally depends on manual measurement or contact type measurement equipment, and the method has the problems that firstly, human errors are easily introduced in manual measurement and the efficiency is low, and secondly, the contact type measurement equipment can provide higher precision, but the detection process is complex and the online real-time detection cannot be realized. In addition, the contact measurement may damage the surface of the copper foil, affecting the quality of the product.
With the development of industrial automation technology, a non-contact detection method based on a visual recognition algorithm is gradually applied to various industrial detection fields. The method takes the copper foil image through the camera, and performs width measurement by using an image processing algorithm, so that the method has the advantages of non-contact, real-time and high efficiency. However, the conventional visual inspection system generally uses a single-point measuring device, which can only detect a specific point of the copper foil, and cannot cover the entire width of the copper foil, so that the measurement result is limited and cannot reflect the width change condition of the entire copper foil. Meanwhile, the single-point measurement system is easily affected by noise and light variation in the production environment, so that the measurement result is unstable and the precision is not high enough. Especially under the condition that the surface of the copper foil is smooth and reflective, the measurement error of the traditional vision system is larger.
Patent document with the application number 202410658166.6 discloses a copper foil size detection device which comprises a movable seat, an image acquisition component, a position detection component and a processing component, wherein the movable seat is movably arranged on a support, the image acquisition component is arranged on the movable seat, a moving path of the image acquisition component passes through a copper foil, the image acquisition component is used for respectively acquiring images of two edges of a copper foil to be detected in size, the position detection component is used for detecting position information of the image acquisition component, the processing component is connected with the image acquisition component and the position detection component, the processing component is used for calculating a distance value between the edges and the center of the image based on the images, calculating a displacement value of the image acquisition component between acquisition positions of the two images based on the position information, and calculating the size to be detected based on the distance value and the displacement value.
According to the application scheme, the to-be-measured size of the copper foil can be calculated based on the acquired image and the displacement value of the movable seat, manual reading is not needed, the problems that manual detection is time-consuming and labor-consuming, and reading errors exist are solved. However, the method has the advantages that the method adopts the movable base, so that accurate images of the edges of the two sides of the copper foil are not easy to continuously collect, the images are not preprocessed, and accurate width values are not easy to calculate.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a device and a method for detecting a width of a copper foil based on a visual recognition algorithm, which utilize an image processing algorithm to perform non-contact, real-time and efficient continuous width measurement on the whole copper foil.
The invention aims at realizing the following technical scheme that the copper foil width detection device based on the visual recognition algorithm comprises the following components:
The two cameras are respectively positioned at two sides of the copper foil to be detected, are fixed on the bridge frame and are used for collecting image data of edges at two sides of the copper foil;
the driving device is used for conveying the copper foil and ensuring that edges at two sides of the copper foil move stably in the view field of the camera;
The rear end analysis server receives the image data from the camera, performs image data preprocessing, calculates the width of the copper foil through a visual recognition algorithm, and transmits the result to the display screen for display.
As still further aspects of the present invention, the method further includes:
And the alarm device is used for giving out an audible and visual alarm when the width of the copper foil calculated by the rear-end analysis server exceeds a preset range.
A copper foil width detection method based on a visual recognition algorithm applied to the device, the method comprising the steps of:
S1, keeping edges on two sides of a copper foil to stably move in the visual fields of two cameras;
S2, respectively acquiring image data of two sides of the copper foil by using two cameras, and sending the image data to a back-end analysis server;
s3, preprocessing the image data by using a back-end analysis server;
s4, calculating the width of the copper foil through a visual recognition algorithm, and transmitting the result to a display screen for display;
And S5, when the calculated width of the copper foil exceeds a preset range, sending out an audible and visual alarm.
As still further aspects of the present invention, the preprocessing of the image data in S3 includes graying, denoising, and image enhancement preprocessing of the image data.
As still further aspect of the present invention, the image data is subjected to gray-scale preprocessing, including converting a captured color image into a gray-scale image, where the formula is:
Gray=0.299×R+0.587×G+0.114×B (1)
Wherein R, G, B are respectively the red, green, blue channels of the image.
As still further aspect of the present invention, the image data is subjected to denoising preprocessing, including smoothing an image using a gaussian filter to reduce noise interference, where a calculation formula is:
where σ is the standard deviation of the gaussian function.
As a still further proposal of the invention, the image data is subjected to image enhancement pretreatment, which comprises the steps of using self-adaptive histogram equalization to improve the contrast of the image and enhance the local detail characteristics of the image, and the steps are as follows:
S31, dividing an image into a plurality of small block areas, wherein the size of each small block area is MXN, and independently carrying out histogram equalization on each small block area, wherein a conversion function formula of the histogram equalization is as follows:
Wherein I is the pixel value of the small block area, H (j) is a histogram, L is the number of gray levels, and M×N is the number of pixels of the small block area;
s32, uniformly distributing the exceeding part to all other bins for any bin in the histogram if the frequency exceeds a threshold value;
And S33, performing bilinear interpolation and merging on the equalization results of the adjacent small areas to obtain a final enhanced image.
As a still further scheme of the invention, the visual recognition algorithm uses a Sobel operator to recognize the edge of an object in an image, performs image edge detection, recognizes the edge position of the copper foil, and uses morphological operation to improve the edge continuity.
As still further aspects of the present invention, the identifying edges of the copper foil in the image using the Sobel operator includes the steps of:
Calculating gradient information in the horizontal direction and the vertical direction of the image by using two convolution kernels respectively;
The convolution kernel gradient information G x is used for detecting the edge of the image in the horizontal direction, G x emphasizes the gray level change in the horizontal direction, and the gradient information of the image in the horizontal direction can be obtained by carrying out convolution operation on G x and the image;
The convolution kernel gradient information G y is used for detecting the edge of the image in the vertical direction, G y emphasizes the gray level change in the vertical direction, and the gradient information of the image in the vertical direction can be obtained by carrying out convolution operation on G y and the image;
according to gradient information of the horizontal direction and the vertical direction of the image, acquiring the gradient size and the gradient direction of the image, and detecting edges, wherein:
The image gradient size calculation formula is:
the image gradient direction calculation formula is:
Wherein G x is gradient information in the horizontal direction, and G y is gradient information in the vertical direction.
As still further aspect of the present invention, the calculating the width of the copper foil includes calculating the actual distance by calculating the pixel distances of the edges on both sides of the copper foil in the image based on the edge detection result, wherein:
The pixel distance calculation formula is:
Width(in pixels)=|x2-x1| (6)
Wherein x 1 and x 2 are the detection results of boundary lines on two sides of the copper foil;
the actual distance and pixel distance conversion formula is:
W=Width(in pixels)×d (7)
where W is the actual distance and d is the conversion factor of the pixel distance to the actual distance.
The invention has the beneficial effects that:
1. The device for detecting the width of the copper foil by using the visual recognition algorithm can fully cover the width of the whole copper foil, continuously collect images of the edges of the two sides of the copper foil by using the camera, and measure the width by using the image processing algorithm, and has the advantages of continuity, non-contact, real-time and high efficiency.
2. According to the invention, the acquired image is preprocessed, including denoising, graying and image enhancement, noise interference can be reduced by the preprocessed image, and the accuracy of edge detection is improved.
3. According to the invention, the edge of an object in an image is identified by adopting a visual identification algorithm and a Sobel operator, and the gradient in the horizontal direction and the vertical direction of the image is utilized to detect the edge, so that the detection position is accurate, the influence of noise and light change in the production environment is not easy to cause, the measurement result is stable, and the precision is high.
Drawings
FIG. 1 is a schematic diagram of a copper foil width detection device based on a visual recognition algorithm;
FIG. 2 is a flow chart of a method for detecting the width of a copper foil based on a visual recognition algorithm;
fig. 3 is a schematic diagram of a method for detecting the width of a copper foil based on a visual recognition algorithm.
110. Camera 120, bridge frame 130, driving device 140, display screen 150, back end analysis server 160, copper foil 170, foil producing machine 180 and alarm device.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar symbols indicate like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the invention.
As shown in fig. 1, the invention discloses a copper foil 160 width detection device based on a visual recognition algorithm, comprising:
the two cameras 110 are respectively positioned at two sides of the copper foil 160 to be detected and fixed on the bridge 120, and collect image data of edges at two sides of the copper foil 160.
And a driving device 130, wherein the driving device 130 is used for conveying the copper foil 160, so as to ensure that the edges of the two sides of the copper foil 160 move smoothly in the visual field of the camera 110.
The back-end analysis server 150, the back-end analysis server 150 receives the image data from the camera 110, performs image data preprocessing, calculates the width of the copper foil 160 through a visual recognition algorithm, and transmits the result to the display screen 140 for display.
And an alarm 180 for giving an audible and visual alarm when the back end analysis server 150 calculates that the width of the copper foil 160 is out of a preset range.
The two cameras 110 are respectively positioned at two sides of the copper foil 160 to be detected, the cameras 110 can adopt high-resolution industrial cameras to ensure the precision and definition of image data, the cameras 110 collect the image data of the edges of the two sides of the copper foil 160, each camera 110 is fixed on the bridge 120, the bridge 120 can be made of metal materials, good rigidity and stability are achieved, the cameras 110 can be ensured to stably shoot the image data of the edges of the copper foil 160, the bridge 120 is fixed above the raw foil camera 170, and the cameras 110 can be ensured to stably shoot the image data of the edges of the copper foil 160.
The driving device 130 is used for conveying the copper foil 160, the driving device 130 can form a roller mechanism by utilizing a linear motor, a belt, a roller and other devices, so that the edge of the copper foil 160 can be ensured to stably move in the field of view of the camera 110, and offset or shake is reduced in the moving process.
The display screen 140 is used for displaying images and detection results acquired by the camera 110 in real time, so that an operator can conveniently monitor and adjust the images, the rear-end analysis server 150 is internally provided with image processing software, the width of the copper foil 160 is calculated by utilizing a visual recognition algorithm through preprocessing the image data acquired by the camera 110, the results are transmitted to the display screen 140, and when the results exceed a set value, the display screen 140 and the alarm device 180 can simultaneously perform alarm operation.
As shown in fig. 2, the present invention also discloses a method for detecting the width of the copper foil 160 based on a visual recognition algorithm by using the device, which comprises the following steps:
S1, keeping the edges of the two sides of the copper foil 160 to move smoothly in the fields of view of the two cameras 110;
S2, respectively acquiring image data of two sides of the copper foil 160 by using the two cameras 110, and sending the image data to the back-end analysis server 150;
s3, performing image data preprocessing on the collected image data by using a back-end analysis server 150;
s4, calculating the width of the copper foil 160 through a visual recognition algorithm, and transmitting the result to the display screen 140 for display;
And S5, when the calculated width of the copper foil 160 exceeds a preset range, an audible and visual alarm is sent out.
As shown in fig. 3, preprocessing the image data includes preprocessing the image data by graying, denoising and image enhancement, and the preprocessed image can reduce noise interference and improve the accuracy of edge detection.
The method comprises the steps of carrying out graying pretreatment on image data, wherein the graying pretreatment comprises the step of converting a shot color image into a gray image, and the formula is as follows:
Gray=0.299×R+0.587×G+0.114×B (1)
Wherein R, G, B are respectively the red, green, blue channels of the image.
The denoising preprocessing is carried out on the image data, the image is smoothed by using a Gaussian filter, noise interference is reduced, and a calculation formula is as follows:
where σ is the standard deviation of the gaussian function.
Further, image enhancement preprocessing is performed on the image data, wherein the image enhancement preprocessing comprises the steps of using adaptive histogram equalization (CLAHE) to improve the contrast of the image and enhance local detail characteristics of the image, and the steps are as follows:
Firstly, dividing an image into a plurality of small block areas, wherein the size of each small block area is M multiplied by N, independently carrying out histogram equalization on each small block area, and the conversion function formula of the histogram equalization is as follows:
Where I is the pixel value of the small block region, H (j) is the histogram, L is the number of gray levels, and mxn is the number of pixels of the small block region.
Then for any bin in the histogram, if the frequency exceeds the threshold value, the exceeding part is uniformly distributed into all other bins, so that the excessive amplification of some gray levels can be prevented, and the noise can be restrained.
Because the image is composed of a plurality of small block areas, in order to avoid blocking effect, the equalization results of the adjacent small block areas are subjected to bilinear interpolation and merging, and a final enhanced image is obtained.
And (3) performing a visual recognition algorithm on the preprocessed image data, wherein the visual recognition algorithm comprises the steps of using a Sobel operator to recognize edges of objects in an image, performing image edge detection, recognizing edge positions of the copper foil 160, and then using morphological operation to improve edge continuity.
Using the Sobel operator to identify the edges of the copper foil 160 in the image, two 3x3 convolution kernels may be used to calculate gradient information in the horizontal and vertical directions of the image, respectively, to detect the edges.
The convolution kernel gradient information G x is used to detect the edge of the image in the horizontal direction, G x emphasizes the gray level change in the horizontal direction, and the gradient information of the image in the horizontal direction can be obtained by performing convolution operation on G x and the image.
The convolution kernel gradient information G y is used to detect the edge of the image in the vertical direction, G y emphasizes the gray scale change in the vertical direction, and the gradient information of the image in the vertical direction can be obtained by performing convolution operation on G y and the image.
And acquiring the gradient size and the gradient direction of the image according to the gradient information of the image in the horizontal direction and the vertical direction, and detecting the edge.
The image gradient size calculation formula is:
the image gradient direction calculation formula is:
Wherein G x is gradient information in the horizontal direction, and G y is gradient information in the vertical direction.
Morphological operation can be performed on the edge detection result, small holes among edges are filled, and edge continuity is improved.
Based on the edge detection result, the actual distance can be obtained by calculating the pixel distances of the edges on both sides of the copper foil 160 in the image, and then the back-end analysis server corrects the calculation result to ensure the accuracy.
The pixel distance calculation formula is:
Width(in pixels)=|x2-x1| (6)
Here, (x 1,y1) and (x 2,y2) are the boundary line detection results of both sides of the copper foil 160, and the calculation was performed by taking the width directions x 1 and x 2.
The actual distance and pixel distance conversion formula is:
W=Width(in pixels)×d (7)
where W is the actual distance and d is the conversion factor of the pixel distance to the actual distance.
The detection result is transmitted to the display screen 140 for real-time display, so that the monitoring of operators is facilitated, the display screen 140 can display real-time images and width values to provide visual detection results, and when the detected width exceeds a preset range, the system can control the alarm lamp to automatically send an alarm signal through the intermediate relay to remind the operators to adjust.
Further, in order to facilitate subsequent analysis and quality control, data can be stored and analyzed, all detection data can be stored in a server, and each detection data and each detection result can be stored in association with corresponding production batch information, so that subsequent quality tracing and problem analysis are facilitated. The quality tracing function can help enterprises to realize comprehensive monitoring and management of the production process, and production efficiency and product quality are improved.
Further, in the process of transmitting image data, in order to ensure the stability and real-time of data transmission, high-speed ethernet or optical fiber transmission may be used.
Furthermore, before the whole device is used, the device can be corrected, and the distortion parameters and the shooting angles of the camera can be considered in the correction process so as to improve the measurement accuracy.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.
In the present invention, unless expressly stated or limited otherwise, a first feature "up" or "down" a second feature may be the first and second features in direct contact, or the first and second features in indirect contact via an intervening medium. Moreover, a first feature being "above," "over" and "on" a second feature may be a first feature being directly above or obliquely above the second feature, or simply indicating that the first feature is level higher than the second feature. The first feature being "under", "below" and "beneath" the second feature may be the first feature being directly under or obliquely below the second feature, or simply indicating that the first feature is less level than the second feature.
Claims (10)
1. The utility model provides a copper foil width detection device based on visual recognition algorithm which characterized in that includes:
Two cameras (110) which are respectively positioned at two sides of the copper foil (160) to be detected and fixed on the bridge (120) and collect image data of the edges at two sides of the copper foil (160);
A driving device (130) for conveying the copper foil (160) to ensure that the edges of both sides of the copper foil (160) move smoothly in the field of view of the camera (110);
the back-end analysis server (150) receives the image data from the camera (110), performs image data preprocessing, calculates the width of the copper foil (160) through a visual recognition algorithm, and transmits the result to the display screen (140) for display.
2. The visual recognition algorithm-based copper foil width detection device according to claim 1, further comprising:
And the alarm device (180) is used for giving an audible and visual alarm when the back-end analysis server (150) calculates that the width of the copper foil (160) exceeds a preset range.
3. A method for detecting the width of a copper foil based on a visual recognition algorithm applied to the apparatus of claim 1 or 2, comprising the steps of:
s1, keeping the edges of the two sides of the copper foil (160) to move stably in the fields of view of the two cameras (110);
S2, respectively acquiring image data of two side edges of the copper foil (160) by using two cameras (110), and sending the image data to a back-end analysis server (150);
S3, preprocessing the acquired image data by using a back-end analysis server (150);
s4, calculating the width of the copper foil (160) through a visual recognition algorithm, and transmitting the result to a display screen (140) for display;
And S5, when the calculated width of the copper foil (160) exceeds a preset range, giving out an audible and visual alarm.
4. The method for detecting the width of the copper foil based on the visual recognition algorithm according to claim 3, wherein the preprocessing of the image data in the step S3 comprises the steps of graying, denoising and image enhancement preprocessing of the image data.
5. The method for detecting the width of the copper foil based on the visual recognition algorithm according to claim 4, wherein the image data is subjected to gray scale preprocessing, and the method comprises the steps of converting a photographed color image into a gray scale image, wherein the formula is as follows:
Gray=0.299×R+0.587×G+0.114×B (1)
Wherein R, G, B are respectively the red, green, blue channels of the image.
6. The method for detecting the width of the copper foil based on the visual recognition algorithm according to claim 4, wherein the image data is subjected to denoising preprocessing, the method comprises smoothing the image by using a Gaussian filter to reduce noise interference, and the calculation formula is as follows:
where σ is the standard deviation of the gaussian function.
7. The method for detecting the width of the copper foil based on the visual recognition algorithm according to claim 4, wherein the image data is subjected to image enhancement preprocessing, the image contrast is improved by using self-adaptive histogram equalization, and local detail characteristics of the image are enhanced, and the method comprises the following steps:
S31, dividing an image into a plurality of small block areas, wherein the size of each small block area is MXN, and independently carrying out histogram equalization on each small block area, wherein a conversion function formula of the histogram equalization is as follows:
Wherein I is the pixel value of the small block area, H (j) is a histogram, L is the number of gray levels, and M×N is the number of pixels of the small block area;
s32, uniformly distributing the exceeding part to all other bins for any bin in the histogram if the frequency exceeds a threshold value;
And S33, performing bilinear interpolation and merging on the equalization results of the adjacent small areas to obtain a final enhanced image.
8. A method for detecting the width of a copper foil based on a visual recognition algorithm according to claim 3, wherein the visual recognition algorithm uses a Sobel operator to recognize the edge of an object in an image, performs image edge detection, recognizes the edge position of the copper foil (160), and uses morphological operations to improve the edge continuity.
9. The method for detecting the width of the copper foil based on the visual recognition algorithm according to claim 8, wherein the step of recognizing the edge of the copper foil (160) in the image using the Sobel operator comprises the steps of:
Calculating gradient information in the horizontal direction and the vertical direction of the image by using two convolution kernels respectively;
The convolution kernel gradient information G x is used for detecting the edge of the image in the horizontal direction, G x emphasizes the gray level change in the horizontal direction, and the gradient information of the image in the horizontal direction can be obtained by carrying out convolution operation on G x and the image;
The convolution kernel gradient information G y is used for detecting the edge of the image in the vertical direction, G y emphasizes the gray level change in the vertical direction, and the gradient information of the image in the vertical direction can be obtained by carrying out convolution operation on G y and the image;
according to gradient information of the horizontal direction and the vertical direction of the image, acquiring the gradient size and the gradient direction of the image, and detecting edges, wherein:
The image gradient size calculation formula is:
the image gradient direction calculation formula is:
Wherein G x is gradient information in the horizontal direction, and G y is gradient information in the vertical direction.
10. The method for detecting the width of the copper foil based on the visual recognition algorithm according to claim 9, wherein the calculating the width of the copper foil (160) comprises obtaining the actual distance by calculating the pixel distances of the edges on both sides of the copper foil (160) in the image based on the edge detection result, wherein:
The pixel distance calculation formula is:
Width(in pixels)=|x2-x1| (6)
Wherein x 1 and x 2 are the boundary line detection results of the two sides of the copper foil (160);
the actual distance and pixel distance conversion formula is:
W=Width(in pixels)×d (7)
where W is the actual distance and d is the conversion factor of the pixel distance to the actual distance.
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