CN114466183A - Copper foil flaw detection method and device based on characteristic spectrum and electronic equipment - Google Patents
Copper foil flaw detection method and device based on characteristic spectrum and electronic equipment Download PDFInfo
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- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 title claims abstract description 409
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- H04N17/00—Diagnosis, testing or measuring for television systems or their details
- H04N17/002—Diagnosis, testing or measuring for television systems or their details for television cameras
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Abstract
The application provides a copper foil flaw detection method and device based on a characteristic spectrum and electronic equipment. The method comprises the following steps: the electronic equipment can acquire a sampling picture of each copper foil shot by the camera from the camera. The electronic device may input the sampled picture into an outlier detection algorithm. The electronic equipment can realize the quality detection of the copper foil through the abnormal point detection algorithm, and determine whether the surface of the copper foil comprises abnormal points, thereby determining the quality index and the abnormal point information of the copper foil. The electronic equipment can generate a control instruction according to the quality index and the abnormal point information of the copper foil, and the control instruction is used for instructing the copper foil processor to perform different processing on the copper foils with different qualities. The method improves the abnormality detection efficiency of the copper foil and improves the processing efficiency of the abnormal copper foil.
Description
Technical Field
The application relates to the field of image processing, in particular to a copper foil flaw detection method and device based on a characteristic spectrum and electronic equipment.
Background
With the rapid development of the electronic information industry, the demand of copper foil is increasing. Copper foil is an important material in the manufacture of circuit boards and lithium ion batteries. Also, the quality of the copper foil is directly related to the service life and performance of the product. It can be seen that quality inspection of the copper foil is critical.
At present, the quality detection of the copper foil is mainly realized by the appearance detection of the copper foil. The less the appearance of the copper foil is abnormal such as voids, the better the quality of the copper foil is. Wherein, the appearance detection of the copper foil can be realized by manual detection.
However, manual inspection on a copper foil processor has a problem of low inspection efficiency.
Disclosure of Invention
The application provides a copper foil flaw detection method and device based on a characteristic spectrum and electronic equipment, and aims to solve the problem of low detection efficiency in the prior art.
In a first aspect, the present application provides a method for detecting defects of a copper foil based on a characteristic spectrum, comprising:
acquiring a sampling picture of a copper foil;
detecting to obtain the quality index and abnormal point information of the copper foil according to the sampling picture and the abnormal point detection algorithm;
and generating a control instruction according to the quality index and the abnormal point information of the copper foil, wherein the control instruction is used for instructing the copper foil processor to perform different processing on the copper foils with different qualities. Optionally, the determining the quality index of the copper foil according to the sampling picture includes:
cutting the sampling picture of the copper foil to obtain a target picture of the copper foil by using a contour detection algorithm;
detecting abnormal point information of the copper foil from the target picture of the copper foil by using different abnormal point detection algorithms;
and determining the quality index of the copper foil according to the abnormal point information of the copper foil.
Optionally, the using a target detection algorithm to obtain the abnormal point information of the copper foil from the target picture of the copper foil by detection includes:
acquiring color pictures of six channels of the target picture according to the HSV color channel and the RGB color channel;
detecting at least one abnormal point of the copper foil corresponding to the abnormal point detection algorithm from each color picture by using different abnormal point detection algorithms;
and merging the abnormal points of the color pictures of the target picture to obtain the abnormal point information of the target picture at the abnormality.
Optionally, the outlier detection algorithm specifically determines the outlier of each of the color pictures by Prewitt edge detection on a logarithm of illumination of the color pictures.
Optionally, the determining the quality index of the copper foil according to the abnormal point information of the copper foil includes:
accumulating the area of each abnormal point in the abnormal point information to obtain the abnormal area of the copper foil;
determining the abnormal density of the copper foil according to the abnormal area and the area of the copper foil;
and determining the quality index of the copper foil according to the abnormal density and the number of the abnormal points of the copper foil.
Optionally, the acquiring a sampling picture of the copper foil includes:
sampling from the copper foil processor according to a preset sampling frequency to obtain at least one copper foil picture of each copper foil;
determining the position information of the copper foil in each copper foil picture by using a contour detection algorithm;
and selecting a picture from at least one copper foil picture of the copper foil as a sampling picture of the copper foil according to the position information of the copper foil.
In a second aspect, the present application provides a copper foil defect detecting apparatus based on a characteristic spectrum, comprising:
the acquisition module is used for acquiring a sampling picture of the copper foil;
the processing module is used for detecting and obtaining the quality index and the abnormal point information of the copper foil according to the sampling picture and the abnormal point detection algorithm; and generating a control instruction according to the quality index and the abnormal point information of the copper foil, wherein the control instruction is used for instructing the copper foil processor to perform different processing on the copper foils with different qualities.
Optionally, the processing module is specifically configured to:
cutting the sampling picture of the copper foil to obtain a target picture of the copper foil by using a contour detection algorithm;
detecting abnormal point information of the copper foil from the target picture of the copper foil by using different abnormal point detection algorithms;
and determining the quality index of the copper foil according to the abnormal point information of the copper foil.
Optionally, the processing module is specifically configured to:
acquiring color pictures of six channels of the target picture according to the HSV color channel and the RGB color channel;
detecting at least one abnormal point of the copper foil corresponding to the abnormal point detection algorithm from each color picture by using different abnormal point detection algorithms;
and merging the abnormal points of the color pictures of the target picture to obtain the abnormal point information of the target picture at the abnormality.
Optionally, the outlier detection algorithm specifically determines the outlier of each of the color pictures by Prewitt edge detection on a logarithm of illumination of the color pictures.
Optionally, the processing module is specifically configured to:
accumulating the area of each abnormal point in the abnormal point information to obtain the abnormal area of the copper foil;
determining the abnormal density of the copper foil according to the abnormal area and the area of the copper foil;
and determining the quality index of the copper foil according to the abnormal density and the number of the abnormal points of the copper foil.
Optionally, the obtaining module is specifically configured to:
sampling from the copper foil processor according to a preset sampling frequency to obtain at least one copper foil picture of each copper foil;
determining the position information of the copper foil in each copper foil picture by using a contour detection algorithm;
and selecting a picture from at least one copper foil picture of the copper foil as a sampling picture of the copper foil according to the position information of the copper foil.
In a third aspect, the present application provides an electronic device, comprising: a memory and a processor;
the memory is used for storing a computer program; the processor is used for executing the copper foil flaw detection method based on the characteristic spectrum in any one of the possible designs of the first aspect and the first aspect according to the computer program stored in the memory.
In a fourth aspect, the present application provides a copper foil defect detection system based on characteristic spectrum, comprising: a copper foil processor, a camera for collecting a sampling picture of the copper foil, and an electronic device as in any one of the possible designs of the third aspect and the third aspect;
the copper foil processor is used for conveying copper foils of different grades to different packing areas according to control instructions.
In a fifth aspect, the present application provides a readable storage medium, in which a computer program is stored, and when the computer program is executed by at least one processor of an electronic device, the electronic device executes the method for detecting defects in a copper foil based on a characteristic spectrum in any one of the possible designs of the first aspect and the first aspect.
In a sixth aspect, the present application provides a computer program product, the computer program product includes a computer program, and when the computer program is executed by at least one processor of an electronic device, the electronic device executes the method for detecting defects in a copper foil based on a characteristic spectrum in any one of the possible designs of the first aspect and the first aspect.
According to the copper foil flaw detection method based on the characteristic spectrum, a sampling picture of each copper foil obtained by shooting through a camera is obtained from the camera; inputting the sampling picture into an abnormal point detection algorithm; the quality detection of the copper foil is realized through the abnormal point detection algorithm, and whether the surface of the copper foil comprises abnormal points or not is determined, so that the quality index and the abnormal point information of the copper foil are determined; and generating a control instruction according to the quality index and the abnormal point information of the copper foil, wherein the control instruction is used for instructing a copper foil processor to carry out different processing means on the copper foils with different qualities, so that the effects of improving the abnormality detection efficiency of the copper foil and improving the processing efficiency of the abnormal copper foil are realized.
Drawings
In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a copper foil detection assembly according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of a copper foil detection assembly according to an embodiment of the present disclosure;
FIG. 3 is a flowchart of a method for detecting defects in a copper foil based on a characteristic spectrum according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a color channel according to an embodiment of the present application;
FIG. 5 is a schematic view of a defect copper foil picture provided in accordance with an embodiment of the present application;
FIG. 6 is a schematic diagram of a black-and-white channel according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of a copper foil defect detecting apparatus based on a characteristic spectrum according to an embodiment of the present application;
fig. 8 is a schematic hardware structure diagram of an electronic device according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of a copper foil defect detection system based on a characteristic spectrum according to an embodiment of the present application.
Detailed Description
To make the purpose, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be clearly and completely described below with reference to the drawings in the present application, and it is obvious that the described embodiments are some, but not all embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged where appropriate. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope herein.
The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
Also, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context indicates otherwise.
It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used in this specification, specify the presence of stated features, steps, operations, elements, components, items, species, and/or groups, but do not preclude the presence, or addition of one or more other features, steps, operations, elements, components, items, species, and/or groups thereof.
The terms "or" and/or "as used herein are to be construed as inclusive or meaning any one or any combination. Thus, "A, B or C" or "A, B and/or C" means "any of the following: a; b; c; a and B; a and C; b and C; A. b and C ". An exception to this definition will occur only when a combination of elements, functions, steps or operations are inherently mutually exclusive in some way.
Copper foil is an important material in the manufacture of circuit boards and lithium ion batteries. With the rapid development of the electronic information industry, the demand of copper foil is increasing. Also, the quality of the copper foil is directly related to the service life and performance of the product. It can be seen that quality inspection of the copper foil is critical. The quality detection of the copper foil is mainly realized by appearance detection of the copper foil. The less the appearance of the copper foil is abnormal such as voids, the better the quality of the copper foil is. At present, most of the detection of the appearance abnormity of the copper foil at home and abroad depends on manual detection. However, the production speed of the copper foil on the copper foil processor is fast. The speed of the loading machine of the copper foil processor can reach 25 m/min. The problem that the detection speed cannot catch up with the speed of the copper foil processor probably exists in manual detection, and the problems of low efficiency and high labor intensity exist. In addition, the appearance of the copper foil is different in abnormal types, the difference between the abnormalities of different copper foils is small, and the distinguishing characteristics are not obvious. The human labor has a problem of high subjectivity in performing the appearance inspection. The existence of the situations causes the problem that the detection efficiency of manual detection on the copper foil processor is low.
In the prior art, a black-and-white picture of the copper foil can be obtained by using a traditional black-and-white camera, and the black-and-white picture can be detected by a visual technology. However, for some anomalies with similar appearance but different colors, they are often not distinguishable by gray scale difference in black and white pictures. Different types of abnormalities generally have different influences on the functions of the copper foil, so that the abnormality cannot be detected, and the judgment of the influence on the functions of the copper foil caused by the abnormalities is possibly inaccurate. Or, when using color pictures, RGB color pictures have a problem that imaging distortion is relatively serious in the case of stroboscopic light source. In addition, the conventional technique has a problem that the abnormality after detection cannot be classified. For example, the anomalies of blue spot copper plating and black line tailing are generally not distinguished by the prior art.
In order to solve the problems, the application provides a copper foil flaw detection method based on a characteristic spectrum. This application uses the camera that can shoot true colour to shoot the copper foil picture. The acquisition of the true-color copper foil picture can effectively solve the problem of missing detection of the color difference abnormality of the traditional black-and-white picture. In addition, this application carries out the light filling through the linear light source of high brightness white light near the camera, has guaranteed the quality that the image acquireed, has avoided the image distortion problem that RGB stroboscopic imaging leads to. In this application, the camera can be through the copper foil picture including copper foil outward appearance original image under gathering the quantitative length camera field of vision. After the camera collects the copper foil picture, the copper foil picture can be uploaded to the electronic equipment. The electronic equipment can preprocess the copper foil picture, so that the copper foil picture can be divided into standard graphs. The electronic device can also determine an anomaly classification of the copper foil by comparison with a standard image. The electronic equipment can also compare colors through HSV spectrum color characteristics to determine the abnormal classification of the copper foil. According to the method, the detection of the copper foil picture is realized by using a true color camera and a holocon-based multi-channel (RGB HSV six channels) simultaneous detection algorithm. Among them, HSV is closer to people's perception experience to the colour than RGB, HSV very directly perceived the hue, the vividness and the light and shade degree of expression colour, conveniently carries out the contrast of colour, under HSV colour space, more easily tracks the object of a certain colour than RGB, better differentiation is taken the colour anomaly and is copperized categorised. Therefore, the detection rate of abnormal belt color and copper plating is greatly improved by using the HSV channel and can reach more than 95%. The effective control of the copper foil on the copper foil processor is realized.
In addition, the method is applicable to surface detection of copper foil, aluminum foil, dip-dyed glass fiber cloth and other products.
The technical solution of the present application will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
Fig. 1 shows a schematic structural diagram of a detection assembly of a copper foil according to an embodiment of the present application. The inspection assembly of the copper foil may be disposed on the copper foil handler. The detection assembly of the copper foil can be shown in fig. 1 and comprises an image acquisition unit, an acquisition module, a processing module, an intelligent classification module and a memory. The image acquisition unit is used for periodically shooting copper foil pictures. The acquisition module is used for acquiring a copper foil picture for displaying the appearance of the copper foil under the visual field of the quantitative length camera. Specifically, in the periodically taken copper foil pictures, multiple copper foil pictures can be corresponded to each copper foil. The acquisition module can select one copper foil picture from the multiple copper foil pictures as a sampling picture. The processing module is used for preprocessing the collected copper foil picture and stretching the sampled picture into a standard rectangular picture. Specifically, the processing module may detect the position of the copper foil in the sampling picture through contour detection. The processing module can also cut the sampling picture according to the position of the copper foil to obtain a target picture. The intelligent classification module can identify and classify the abnormity in the target picture after receiving the target picture. Specifically, the accurate classification of the intelligent classification module can obtain an accurate classification image of the copper foil picture through standard image features. And comparing colors through spectral color characteristics to determine the detection result of the copper foil picture. The spectral colors are HSV spectra.
The memory can be connected with the intelligent classification module and stores the detection result of the intelligent classification module. The detection result may include a classification result. The classification result may include a classification result of whether the article is a non-defective article and a classification result of an abnormality type. The memory can also be connected with the image acquisition unit to acquire and store the copper foil picture.
As shown in fig. 2, the image capturing unit may include a camera and a fill-in light. Wherein, the camera can be used for shooing the copper foil picture. The speed of the copper foil processor can reach 25m/min, so that the camera can be a high-frequency camera or a moving camera to realize the snapshot of the fast-moving copper foil. The camera can also be a color intelligent camera used for shooting true color copper foil pictures. The light source of the light supplement lamp is a high-brightness white light linear light source. The light supplement lamp is used for illuminating the surface of the copper foil so as to improve the definition of a copper foil picture shot by the camera and enable the abnormity in the copper foil picture to be more obvious.
In addition, the detection assembly can also comprise a fixed frame. The fixed frame is arranged on two sides of the copper foil processor before rolling. The fixed frame is used for fixing a camera and a light supplement lamp in the image acquisition unit.
In the present application, the electronic device is used as an execution subject to execute the copper foil defect detection method based on the characteristic spectrum of the following embodiment. Specifically, the execution body may be a hardware device of the electronic device, or a software application implementing the following embodiments in the electronic device, or a computer-readable storage medium installed with the software application implementing the following embodiments, or code of the software application implementing the following embodiments.
Fig. 3 shows a flowchart of a method for detecting defects of a copper foil based on a characteristic spectrum according to an embodiment of the present application. On the basis of the embodiments shown in fig. 1 and fig. 2, as shown in fig. 3, with the electronic device as an execution subject, the method of the present embodiment may include the following steps:
and S101, acquiring a sampling picture of the copper foil.
In this embodiment, the electronic device may obtain a sampling picture of each copper foil taken by the camera from the camera. Or when the camera has a high shooting frequency, the camera can also acquire a plurality of copper foil pictures of each copper foil. The electronic equipment can screen a copper foil picture from the multiple copper foil pictures as a sampling picture.
In one example, the process of acquiring the sample picture may include the following steps:
step 1, the electronic equipment can acquire at least one copper foil picture of each copper foil by sampling from a copper foil processor by a camera according to a preset sampling frequency. Since the copper foil moves on the copper foil processor when the camera is shooting, the position of the copper foil is different in different copper foil pictures.
And 2, the electronic equipment can determine the position information of the copper foil in each copper foil picture by using a contour detection algorithm. Or, the electronic device can also determine the position information of the copper foil in each copper foil picture through a target detection algorithm. The contour detection algorithm or the target detection algorithm may be an existing algorithm or an improved algorithm.
And 3, the electronic equipment can select one picture from at least one copper foil picture of the copper foil as a sampling picture of the copper foil according to the position information of the copper foil. For example, when a copper foil picture usually includes only one copper foil, the electronic device may delete the copper foil pictures including a plurality of copper foils to obtain a plurality of consecutive copper foil pictures targeting the same copper foil. The electronic device can compare the copper foil pictures and select the copper foil picture with the highest definition from the copper foil pictures. For another example, when a copper foil picture includes a plurality of copper foils, the electronic device may use the copper foil whose position error from the center point of the copper foil picture is smaller than the preset value as the target copper foil in the copper foil picture. The electronic device may take a picture of the copper foil where the target copper foil exists as a sampling picture.
And S102, detecting to obtain the quality index and the abnormal point information of the copper foil according to the sampling picture and the abnormal point detection algorithm.
In this embodiment, after acquiring the sampling picture, the electronic device may input the sampling picture into the abnormal point detection algorithm. The electronic equipment can realize the quality detection of the copper foil through the abnormal point detection algorithm, and determine whether the surface of the copper foil comprises abnormal points, thereby determining the quality index and the abnormal point information of the copper foil.
In one example, a specific process of detecting, by an electronic device, a quality index and abnormal point information of a copper foil according to a sampling picture may include the following steps:
step 1, the electronic device can determine the position information of the copper foil in the sampling picture by using a contour detection algorithm. The electronic equipment can cut out a target picture of the copper foil from the sampling picture according to the position information.
And 2, the electronic equipment can use different abnormal point detection algorithms to detect and obtain the abnormal point information of the copper foil from the target picture of the copper foil.
In this step, the electronic device may obtain three color pictures according to the three RGB channels of the target picture. The electronic equipment can also convert the target picture of the RGB into a target picture in HSV format. The electronic device can split the target picture in the HSV format to obtain three color pictures of three channels. Six color pictures of the six channels may be as shown in fig. 4. Fig. 4(a) is a color picture of an R channel, fig. 4(B) is a color picture of a G channel, fig. 4(c) is a color picture of a B channel, fig. 4(d) is a color picture of an H channel, fig. 4(e) is a color picture of an S channel, and fig. 4(f) is a color picture of a V channel.
Various abnormal point detection algorithms can be preset in the electronic equipment. Each anomaly detection algorithm may be a detection algorithm generated for one or more anomalies. For example, the anomaly detection algorithm may be a trained deep learning algorithm for detecting holes in the surface of the copper foil. For another example, the abnormal point detection algorithm may be an algorithm based on color abnormality detection, and is used for detecting an area where the copper foil surface plating is peeled off. For another example, the anomaly detection algorithm can be a bump detection algorithm for detecting pits or bumps on the surface of the copper foil. The electronic device may input each color picture into a respective outlier detection algorithm. The electronic device can obtain a detection result of each color picture for each anomaly. The detection result comprises at least one abnormal point.
The electronic device can summarize the detection results of the multiple color pictures input into the same abnormal point detection algorithm to obtain the abnormal point information of the abnormality. The outlier merging process includes adding a new outlier to the outlier information and merging the collocated outliers into one outlier. The visual appearance of the abnormal point on the surface of the copper foil is generally an area. Therefore, when merging a plurality of outliers at the same position, the electronic device can select the outlier with the largest area as the outlier at the position. Alternatively, the electronic device may merge two outliers into one outlier when the two outliers have an overlapping region.
The outlier detection algorithm may specifically determine an outlier of each color picture by Prewitt edge detection on the logarithm of the illumination of the color picture. The calculation formula of the Prewitt edge detection method for the logarithm of the illumination can be as follows:
A＝(log(W(x+1，y-1))+log(W(x+1，y))+log(W(x+1，y+1)))-(log(W(x-1，y-1))+log(W(x-1，y))+log(W(x-1，y+1)))；
B＝(log(W(x-1，y+1))+log(W(x，y+1))+log(W(x+1，y+1)))-(log(W(x-1，y-1))+log(W(x，y-1))+log(W(x+1，y-1)))；
C(x,y)＝|A|+|B|。
specifically, as shown in fig. 5(a), a picture of a copper foil including scratch-type defects and a binary image thereof, fig. 5(b) a picture of a copper foil including irregular type defects and a binary image thereof, and fig. 5(c) a picture of a copper foil including stain-type defects and a binary image thereof. Aiming at the average illumination intensity change of the production environment, the electronic equipment adopts a normalized internal standard method gray level correction algorithm in the application. The algorithm firstly quantifies a detection target by taking a local background of a copper foil picture as an internal standard. Then, the electronic device normalizes the copper foil picture by using a certain fixed gray level. The electronic device can correct the images under different illumination intensities to be in the same state, so as to perform abnormality judgment. The method ensures that the change of the average illumination intensity does not influence the detection result any more, and can adapt to the condition of unstable average illumination intensity on the industrial detection site. In addition, in order to solve the problem of uneven light intensity of each part of the copper foil, the method of Prewitt edge detection using the logarithm (optical density) of light intensity is also adopted when the image is segmented by using the edge detection. The area boundary obtained by the method is irrelevant to the illumination intensity of each part of the object to be detected.
In order to avoid floating point operation and increase processing speed, the logarithm operation adopts a table look-up method to determine the result.
The electronic device may calculate A, B, C three values according to the above formula. The electronic equipment can carry out bivariate processing on the image according to the threshold value, and further obtains a more ideal detection effect. Wherein the threshold may be determined empirically. The Prewitt edge detection method for the logarithm of the illumination can improve the accuracy of image segmentation and further improve the defect detection effect of the copper foil.
And 3, the electronic equipment can determine the quality index of the copper foil according to the abnormal point information of the copper foil. The quality index is used to indicate the overall quality of the copper foil. For example, when the copper foil includes only one type of abnormality, the electronic device may accumulate the area of each abnormal point in the abnormal point information of the abnormality to obtain the abnormal area of the copper foil. The electronic device can determine the abnormal density of the copper foil according to the ratio of the abnormal area to the area of the copper foil. The electronic equipment can determine the quality index of the copper foil according to the weighted sum of the abnormal density and the number of the abnormal points of the copper foil. Wherein, the weight of the abnormal density and the number of abnormal points can be determined empirically. For another example, when the copper foil only includes a plurality of anomalies, the electronic device may calculate a quality index for each anomaly, respectively. The electronic device may use the average of the quality indicators of each anomaly as the final quality indicator.
And S103, generating a control instruction according to the quality index and the abnormal point information of the copper foil, wherein the control instruction is used for instructing the copper foil processor to perform different processing on the copper foils with different qualities.
In this embodiment, the electronic device may determine whether the copper foil is a qualified product according to the quality index of the copper foil. For example, when the quality index is less than the first threshold, the copper foil may be a good product. And when the quality index is larger than or equal to the first threshold value, the copper foil is a defective product. Wherein the first threshold value may be determined from empirical values. When the copper foil is qualified, the electronic device can generate a control command. The control instructions can instruct the copper foil processor to continue to wind the copper foil.
When the copper foil is a defective product, the copper foil is usually processed in different ways for different abnormalities. Therefore, the electronic equipment can determine the abnormal type of the copper foil according to the abnormal point information of the copper foil. When the copper foil has only one anomaly, the electronic device can determine that the copper foil belongs to the anomaly. When the copper foil has multiple anomalies, the electronic equipment can determine the anomaly corresponding to the largest quality index as the anomaly type of the copper foil according to the quality index of each anomaly. The quality index of the abnormality indicates that the abnormality occurs most frequently and has the largest area in the copper foil.
The electronic equipment can convey the copper foil to different packaging ports for packaging according to the abnormal type of the copper foil, so that the unqualified products can be processed uniformly.
In one example, the electronic device can also record the abnormality information so as to analyze the abnormality of the copper foil. For example, after the statistics, the abnormality mainly occurring in the copper foil of the copper foil processor may be determined based on the statistical result. The manager can optimize the copper foil processor according to the abnormality so as to improve the qualification rate of the copper foil.
According to the copper foil flaw detection method based on the characteristic spectrum, the electronic equipment can acquire the sampling picture of each copper foil shot by the camera from the camera. The electronic device may input the sampled picture into an outlier detection algorithm. The electronic equipment can realize the quality detection of the copper foil through the abnormal point detection algorithm, and determine whether the surface of the copper foil comprises abnormal points, thereby determining the quality index and the abnormal point information of the copper foil. The electronic equipment can generate a control instruction according to the quality index and the abnormal point information of the copper foil, and the control instruction is used for instructing the copper foil processor to perform different processing on the copper foils with different qualities. In the application, the sampling picture of the copper foil is obtained, and the copper foil is detected through the sampling picture, so that the abnormity detection efficiency of the copper foil is improved, and the processing efficiency of the abnormal copper foil is improved.
In addition to the above embodiments, the present embodiment can also acquire a black-and-white picture taken by a black-and-white camera and a copper foil picture taken by a color camera. Wherein a black and white picture can be as shown in fig. 6.
The electronic device can detect the abnormality of the surface of the copper foil by using the black-and-white picture and the copper foil picture respectively. In the following examples, the detection rate and detection accuracy of copper plating abnormality were compared, and the detection results of the three tests can be shown in table 1.
TABLE 1
The copper foil of group 1 included 24 copper platings. The experimental data show that 25 coppering pictures are detected. After manual review, 24 of the 25 coppers were judged correctly, and 1 was judged incorrectly. Therefore, the copper plating detection rate is 100%, and the detection accuracy is 96%. Black and white pictures detected 45 copperes. After manual review, only 3 of them were tested correctly for copper plating. Therefore, the copper plating detection rate was 12.5%, and the copper plating accuracy was 6.67%.
The copper foil of group 2 included 15 copper platings. As can be seen from the experimental data, 15 copper platings were detected in the color pictures. After manual review, all 15 coppering were judged to be correct. Therefore, the detection rate of copper plating was 100%, and the detection accuracy was 100%. Black and white pictures detected 38 copperes. Only 5 of these were tested correctly by manual review. Therefore, the copper plating detection rate was 33.3%, and the copper plating accuracy was 13.16%.
The copper foil of group 3 included 13 copper platings. Experimental data shows that 13 coppering pictures are detected, and the 13 coppering pictures are judged to be correct through manual review. Therefore, the detection rate of copper plating was 100%, and the detection accuracy was 100%. 52 coppering were detected in black and white pictures. Only 4 of these were tested correctly by manual review. Therefore, the copper plating detection rate was 30.77% and the copper plating accuracy was 7.67%.
Through the comparison, the quality of the copper foil picture acquired after light supplement is carried out through the high-brightness white light linear light source is high. And the accuracy of the abnormal detection of the copper foil by comparing colors through HSV spectral color characteristics is high. The application adopts the detection scheme of the color intelligent camera, uses the multi-channel simultaneous detection, greatly improves the detection rate of abnormal belt color and copper plating, can reach more than 95 percent, and can effectively realize the management and control of the copper foil and copper foil processor.
Fig. 7 is a schematic structural diagram of a copper foil defect detecting apparatus based on a characteristic spectrum according to an embodiment of the present application, and as shown in fig. 7, the copper foil defect detecting apparatus 10 based on a characteristic spectrum according to the present embodiment is used for implementing operations corresponding to electronic devices in any of the above method embodiments, and the copper foil defect detecting apparatus 10 based on a characteristic spectrum according to the present embodiment includes:
and the acquisition module 11 is used for acquiring a sampling picture of the copper foil.
The processing module 12 is used for detecting and obtaining the quality index and the abnormal point information of the copper foil according to the sampling picture and the abnormal point detection algorithm; and generating a control instruction according to the quality index and the abnormal point information of the copper foil, wherein the control instruction is used for instructing the copper foil processor to perform different processing on the copper foils with different qualities.
In one example, the processing module 12 is specifically configured to:
cutting a sampling picture of the copper foil to obtain a target picture of the copper foil by using a contour detection algorithm;
detecting abnormal point information of the copper foil from a target picture of the copper foil by using different abnormal point detection algorithms;
and determining the quality index of the copper foil according to the copper foil abnormal point information.
In one example, the processing module 12 is specifically configured to:
acquiring a plurality of color pictures of a target picture according to the color channels;
detecting at least one abnormal point of the copper foil corresponding to the abnormal point detection algorithm from each color picture by using different abnormal point detection algorithms;
and combining the abnormal points of the multiple color pictures of the target picture to obtain the abnormal point information of the target picture.
In one example, the processing module 12 is specifically configured to:
accumulating the area of each abnormal point in the abnormal point information to obtain the abnormal area of the copper foil;
determining the abnormal density of the copper foil according to the abnormal area and the area of the copper foil;
and determining the quality index of the copper foil according to the abnormal density and the number of the abnormal points of the copper foil.
In one example, the obtaining module 11 is specifically configured to:
and sampling from a copper foil processor according to a preset sampling frequency to obtain at least one copper foil picture of each copper foil.
And determining the position information of the copper foil in each copper foil picture by using a contour detection algorithm.
And selecting one picture from at least one copper foil picture of the copper foil as a sampling picture of the copper foil according to the position information of the copper foil.
The copper foil flaw detection apparatus 10 based on the characteristic spectrum provided in the embodiment of the present application may implement the above method embodiment, and specific implementation principles and technical effects thereof may be referred to the above method embodiment, which is not described herein again.
Fig. 8 shows a hardware structure diagram of an electronic device according to an embodiment of the present application. As shown in fig. 8, the electronic device 20 is configured to implement the operations corresponding to the electronic device in any of the method embodiments described above, where the electronic device 20 of this embodiment may include: memory 21, processor 22 and communication interface 24.
A memory 21 for storing a computer program. The Memory 21 may include a Random Access Memory (RAM), a Non-Volatile Memory (NVM), at least one disk Memory, a usb disk, a removable hard disk, a read-only Memory, a magnetic disk or an optical disk.
And the processor 22 is used for executing the computer program stored in the memory so as to realize the copper foil flaw detection method based on the characteristic spectrum in the embodiment. Reference may be made in particular to the description relating to the method embodiments described above. The Processor 22 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.
Alternatively, the memory 21 may be separate or integrated with the processor 22.
When the memory 21 is a separate device from the processor 22, the electronic device 20 may also include a bus 23. The bus 23 is used to connect the memory 21 and the processor 22. The bus 23 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.
The communication interface 24 may be connected to the processor 21 via a bus 23. The communication interface 24 can be connected to a camera for obtaining a copper foil picture taken by the camera. The communication interface 24 may also be coupled to a copper foil processor for sending control instructions to the copper foil processor.
The electronic device provided by this embodiment can be used to perform the above-mentioned copper foil defect detection method based on the characteristic spectrum, and its implementation manner and technical effect are similar, and this embodiment is not described herein again.
Fig. 9 is a schematic structural diagram illustrating a characteristic spectrum-based copper foil defect detection system according to an embodiment of the present application. As shown in fig. 9, the characteristic spectrum-based copper foil defect detecting system 30 may include: a copper foil processor 31, a camera 32 for taking a sample picture of the copper foil, and an electronic device 33 as in fig. 7.
Wherein, the camera can be fixed on the copper foil processor. The copper foil processor may include a conveyor belt thereon. The copper foil processor can transfer the copper foils on a conveyor belt of the copper foil processor by winding the copper foils. The speed at which the belt conveys the copper foil may be 25 m/min. Fixed frames are arranged on two sides of a winding inlet of the copper foil processor. The fixed bolster of these both sides can be used for fixed camera, and in an example, can also include the light filling lamp. The light supplement lamp is used for providing a light source for image acquisition.
The copper foil picture acquired by the camera is the copper foil appearance original image under the view field of the camera with the quantitative length. The camera can upload the copper foil picture to an acquisition module in the electronic equipment. The acquisition module in the electronic equipment can select a sampling picture from at least one copper foil picture. The processing module in the electronic device can preprocess the sampling picture and cut out a target picture including copper foil in the sampling picture. The processing module can also divide the target picture to obtain a plurality of preset length and width target picture fragments. The segmentation can enable the target picture to adapt to the identification requirement of the intelligent classification module under the condition of ensuring the resolution of the target picture. The intelligent classification module in the electronic equipment is used for detecting abnormal points in the target picture, and realizing abnormal judgment and abnormal classification.
The intelligent classification module in the electronic equipment can compare the colors of the target picture through HSV spectrum color characteristics. The electronic equipment can determine the area with the abnormality on the surface of the copper foil through the color comparison, thereby realizing the abnormality detection of the copper foil. The anomaly detection may be an online detection. The electronic equipment can upload the detection result to the server in real time. Alternatively, the electronic device may also be connected to a local memory. The electronic equipment can send the detection result to the memory, and the storage of the copper foil picture and the detection result is realized. The copper foil processor can also transfer different grades of copper foil to different baling areas according to control instructions.
The administrator can acquire the stored detection results and the copper foil pictures from the memory or from the server. Therefore, the subsequent statistics and analysis of the detection result are realized.
The electronic device provided by this embodiment can be used to perform the above-mentioned copper foil defect detection method based on the characteristic spectrum, and its implementation manner and technical effect are similar, and this embodiment is not described herein again.
The present application also provides a computer-readable storage medium, in which a computer program is stored, and the computer program is used for implementing the methods provided by the above-mentioned various embodiments when being executed by a processor.
The computer-readable storage medium may be a computer storage medium or a communication medium. Communication media includes any medium that facilitates transfer of a computer program from one place to another. Computer storage media may be any available media that can be accessed by a general purpose or special purpose computer. For example, a computer readable storage medium is coupled to the processor such that the processor can read information from, and write information to, the computer readable storage medium. Of course, the computer readable storage medium may also be an integral part of the processor. The processor and the computer-readable storage medium may reside in an Application Specific Integrated Circuit (ASIC). Additionally, the ASIC may reside in user equipment. Of course, the processor and the computer-readable storage medium may also reside as discrete components in a communication device.
In particular, the computer-readable storage medium may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random-Access Memory (SRAM), Electrically-Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
The present application also provides a computer program product comprising a computer program stored in a computer readable storage medium. The computer program can be read by at least one processor of the device from a computer-readable storage medium, and execution of the computer program by the at least one processor causes the device to implement the methods provided by the various embodiments described above.
Embodiments of the present application further provide a chip, where the chip includes a memory and a processor, where the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that a device in which the chip is installed executes the method in the above various possible embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of modules is merely a division of logical functions, and an actual implementation may have another division, for example, a plurality of modules may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.
Wherein the modules may be physically separated, e.g. mounted at different locations of one device, or mounted on different devices, or distributed over multiple network elements, or distributed over multiple processors. The modules may also be integrated, for example, in the same device, or in a set of codes. The respective modules may exist in the form of hardware, or may also exist in the form of software, or may also be implemented in the form of software plus hardware. The method and the device can select part or all of the modules according to actual needs to achieve the purpose of the scheme of the embodiment.
When the respective modules are implemented as integrated modules in the form of software functional modules, they may be stored in a computer-readable storage medium. The software functional module is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor to execute some steps of the methods according to the embodiments of the present application.
It should be understood that, although the respective steps in the flowcharts in the above-described embodiments are sequentially shown as indicated by arrows, the steps are not necessarily performed sequentially as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least some of the steps in the figures may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, in different orders, and may be performed alternately or at least partially with respect to other steps or sub-steps of other steps.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same. Although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: it is also possible to modify the solutions described in the previous embodiments or to substitute some or all of them with equivalents. And the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.
Claims (11)
1. A copper foil defect detection method based on a characteristic spectrum is characterized by comprising the following steps:
acquiring a sampling picture of a copper foil;
detecting to obtain the quality index and abnormal point information of the copper foil according to the sampling picture and the abnormal point detection algorithm;
and generating a control instruction according to the quality index and the abnormal point information of the copper foil, wherein the control instruction is used for instructing a copper foil processor to perform different processing on the copper foils with different qualities.
2. The method according to claim 1, wherein the detecting to obtain the quality index and the abnormal point information of the copper foil according to the sampling picture and the abnormal point detection algorithm comprises:
cutting the sampling picture of the copper foil to obtain a target picture of the copper foil by using a contour detection algorithm;
detecting abnormal point information of the copper foil from the target picture of the copper foil by using different abnormal point detection algorithms;
and determining the quality index of the copper foil according to the abnormal point information of the copper foil.
3. The method of claim 2, wherein the detecting abnormal point information of the copper foil from the target picture of the copper foil by using an abnormal point detection algorithm with different abnormalities comprises:
acquiring color pictures of six channels of the target picture according to the HSV color channel and the RGB color channel;
detecting at least one abnormal point of the copper foil corresponding to the abnormal point detection algorithm from each color picture by using different abnormal point detection algorithms;
and merging the abnormal points of the color pictures of the target picture to obtain the abnormal point information of the target picture at the abnormality.
4. The method of claim 3, wherein the outlier detection algorithm determines the outliers of each of the color pictures by, in particular, Prewitt edge detection on the logarithm of the illumination of the color pictures.
5. The method of claim 2, wherein the determining the quality index of the copper foil according to the anomaly point information of the copper foil comprises:
accumulating the area of each abnormal point in the abnormal point information to obtain the abnormal area of the copper foil;
determining the abnormal density of the copper foil according to the abnormal area and the area of the copper foil;
and determining the quality index of the copper foil according to the abnormal density and the number of the abnormal points of the copper foil.
6. The method of any one of claims 1-4, wherein said obtaining a sample picture of a copper foil comprises:
sampling from the copper foil processor according to a preset sampling frequency to obtain at least one copper foil picture of each copper foil;
determining the position information of the copper foil in each copper foil picture by using a contour detection algorithm;
and selecting a picture from at least one copper foil picture of the copper foil as a sampling picture of the copper foil according to the position information of the copper foil.
7. A copper foil flaw detection device based on characteristic spectrum is characterized by comprising:
the acquisition module is used for acquiring a sampling picture of the copper foil;
the processing module is used for detecting and obtaining the quality index and the abnormal point information of the copper foil according to the sampling picture and the abnormal point detection algorithm; and generating a control instruction according to the quality index and the abnormal point information of the copper foil, wherein the control instruction is used for instructing a copper foil processor to perform different processing on the copper foils with different qualities.
8. An electronic device, characterized in that the device comprises: a memory, a processor;
the memory is used for storing a computer program; the processor is used for realizing the copper foil defect detection method based on the characteristic spectrum according to any one of claims 1 to 6 according to the computer program stored in the memory.
9. A detection system, the system comprising: a copper foil processor, a camera for acquiring a sampling picture of the copper foil, and the electronic device of claim 8;
the copper foil processor is used for transmitting copper foils with different grades to different packing areas according to control instructions.
10. A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the computer program is used for implementing the method for detecting defects in a copper foil according to any one of claims 1 to 6 based on a characteristic spectrum.
11. A computer program product comprising a computer program which, when executed by a processor, implements the method for detecting defects in a copper foil based on a characteristic spectrum according to any one of claims 1 to 6.
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| 周奇: "基于HALCON的太阳能电池片缺陷检测系统设计", 江苏大学, 16 December 2017 (2017-12-16) * |
| 张一明: "金属零部件表面瑕疵缺陷的视觉检测技术研究", 沈阳理工大学, 16 February 2020 (2020-02-16) * |
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