CN116912249A - Sealant sealing quality detection method, device, equipment and medium thereof - Google Patents
Sealant sealing quality detection method, device, equipment and medium thereof Download PDFInfo
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- 238000007789 sealing Methods 0.000 title claims abstract description 85
- 239000000565 sealant Substances 0.000 title claims abstract description 63
- 238000001514 detection method Methods 0.000 title claims abstract description 61
- 239000003292 glue Substances 0.000 claims abstract description 116
- 238000004026 adhesive bonding Methods 0.000 claims abstract description 74
- 239000000084 colloidal system Substances 0.000 claims abstract description 52
- 238000000034 method Methods 0.000 claims abstract description 33
- 230000007480 spreading Effects 0.000 claims abstract description 10
- 238000003892 spreading Methods 0.000 claims abstract description 10
- 238000007781 pre-processing Methods 0.000 claims abstract description 4
- 238000012545 processing Methods 0.000 claims description 20
- 238000004364 calculation method Methods 0.000 claims description 12
- 238000003860 storage Methods 0.000 claims description 12
- 238000004891 communication Methods 0.000 claims description 10
- 210000000988 bone and bone Anatomy 0.000 claims description 8
- 239000011248 coating agent Substances 0.000 claims description 5
- 238000000576 coating method Methods 0.000 claims description 5
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- 238000004590 computer program Methods 0.000 claims description 4
- 230000011218 segmentation Effects 0.000 claims description 3
- 238000005259 measurement Methods 0.000 abstract description 3
- 238000004422 calculation algorithm Methods 0.000 description 6
- 238000004519 manufacturing process Methods 0.000 description 6
- 230000005540 biological transmission Effects 0.000 description 5
- 238000005286 illumination Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
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- 241001292396 Cirrhitidae Species 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000013135 deep learning Methods 0.000 description 2
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- 230000003044 adaptive effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
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- 238000010295 mobile communication Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Chemical compound O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G06T7/10—Segmentation; Edge detection
- G06T7/136—Segmentation; Edge detection involving thresholding
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20092—Interactive image processing based on input by user
- G06T2207/20104—Interactive definition of region of interest [ROI]
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Abstract
The application relates to the technical field of seal quality detection, in particular to a method, a device, equipment and a medium for detecting seal quality of sealant, wherein the method comprises the following steps: acquiring two images before and after gluing; preprocessing two images to obtain a gluing area; judging whether the gluing area has gluing or not through a target detection model, and if so, entering the next step; acquiring a colloid outline of the gluing area, judging whether the gluing area has broken glue according to the colloid outline, and if the gluing area has no broken glue, entering the next step; calculating the width value of the colloid outline, comparing the width value with a preset width value, judging whether glue overflow exists in the glue spreading area, and if the width value of the colloid outline is within the range of the preset width value, avoiding glue overflow and entering the next step; and calculating skeleton lines of the gluing area, obtaining the ratio of the skeleton lines on the colloid, comparing the ratio with a preset threshold value, judging whether the gluing area has less glue, and if the gluing area has no less glue, ensuring that the sealing quality of the sealing glue is qualified, thereby improving the detection efficiency, and having high measurement accuracy and high applicability.
Description
Technical Field
The application relates to the technical field of seal quality detection, in particular to a method, a device and equipment for detecting seal quality of sealant and a medium thereof.
Background
The automobile lamp is an indispensable component of an automobile as a tool for illumination and safety signal transmission. In order to improve the usability of the lamp, the lamp is required to have good sealing quality. If the sealing quality of the automobile lamp is poor, water vapor can be invaded, so that the illumination of the automobile lamp, the service life of the automobile lamp and the appearance of the automobile lamp are affected, and the driving safety is endangered. In the production and manufacturing process of the automobile lamp, the bonding strength of the sealant is good, sealing protection is realized by using the sealant, and when the automobile lamp is used, the sealant is uniformly smeared on the first assembly part, and the sealant layer formed by the sealant is bonded with the second assembly part in a sealing way. Because the quantity of the sealant can not be controlled in real time in the production process, the sealing quality of the sealant can not be ensured, and if the sealing quality is problematic, the performance and the service life of the equipment can be directly affected, and the operation reliability of the equipment can be further affected.
The modern high-speed production line is low in human eye recognition or recognition efficiency, in addition, high labor cost forces production enterprises to change, such as the quality detection efficiency of a machine vision assistance product, and a vision detection system is introduced to enable a machine to replace manual detection so as to improve the production detection efficiency. The sealing quality detection of the sealant can be carried out by human eyes, but the efficiency of the quality of the artificial vision is low because the staff is easy to be tired under long-time work. In order to improve the detection efficiency, in the prior art, machine vision is adopted to detect the sealing quality of the sealant, for example, the sealing quality detection of the sealant based on the deep learning and the halcon processing technology is adopted, and although the detection process of the two methods is high in detection efficiency, a large number of data sets are required to be acquired in the detection process based on the deep learning, time and effort are consumed for marking samples, and when the background is changed, a model is required to be retrained, so that the applicability is not high; the sealant detection technology based on the halcon processing technology cannot identify the less colloid state, and has the problems that the qualified products misjudge the unqualified products, and the detection accuracy is low.
Disclosure of Invention
The application aims to solve the technical problems that: in order to solve the problems of low sealing quality speed, low applicability and low detection accuracy of the sealant in the prior art, the application provides the sealant sealing quality detection method, which improves the efficiency of sealant sealing quality detection, and has high measurement accuracy and high applicability.
The technical scheme adopted for solving the technical problems is as follows: a sealing quality detection method of sealant comprises the following steps:
s1, acquiring a first image before gluing and a second image after gluing;
s2, preprocessing the first image and the second image to obtain a gluing area;
s3, judging whether the glue coating area is coated with glue or not through a target detection model, and if so, entering the next step;
s4, acquiring a colloid outline of the gluing area, judging whether the gluing area has broken glue according to the colloid outline, and if the gluing area has no broken glue, entering the next step;
s5, calculating the width value of the colloid outlineWComparing with a preset width value, judging whether the glue spreading area has glue overflow or not, if so, determining that the width value of the glue profileWIf the glue overflow is not generated within the range of the preset width value, entering the next step;
s6, calculating skeleton lines of the gluing area, obtaining the ratio of the skeleton lines on the colloid, comparing the ratio with a preset threshold, judging whether the gluing area has less glue, and if the gluing area has less glue, judging that the sealing quality of the sealing glue is qualified;
the step S6 specifically includes the following steps:
s61, obtaining the vertex of the gluing area and the coordinates of the vertex;
s62, calculating the coordinate P of the mass center of the gluing area according to the coordinate of the vertexx，y）；
S63, dividing the gluing area according to the vertexes and the centroids to form a plurality of subareas, wherein the number of the subareas is the same as that of the vertexes;
s64, calculating a bone line of the gluing area, wherein the calculation of the bone line of the gluing area comprises the following steps: the gel profile includes a gel outer profile and a gel inner profile,obtaining pixel points A (x 1 ，y 1 ) And the pixel point a (x 1 ，y 1 ) The nearest pixel point a (x 2 ，y 2 ) Calculating the coordinates of the central points between the pixel point A and the pixel point a, traversing all the pixel points of the outer contour of the rubber body and the inner contour of the rubber body, and calculating to obtain the coordinates of all the central points, wherein the straight line formed by connecting all the central points is the skeleton line;
s65, counting the ratio of the bone lines of each sub-region on the colloid, comparing the ratio with a preset threshold, and judging whether the gluing region has less glue;
if no less glue exists, the sealing quality of the sealant is qualified;
otherwise, if the glue is few, the sealing quality of the sealant is unqualified.
Further, specifically, the step S2 specifically includes the following steps:
s21, gray processing is carried out on the first image and the second image, and a first gray image and a second gray image are obtained;
s22, subtracting the gray value of the pixel point on the second gray level image from the gray value of the pixel point on the first gray level image to obtain a differential image;
s23, performing brightness self-adaptive adjustment on the differential image;
s24, filtering the difference image with the brightness adjusted by using a filter to obtain a filtered image;
s25, dividing the filtered image into a foreground and a background by the Ojin method segmentation to obtain a binary image;
s26, calculating a maximum communication area based on the binary image, wherein the maximum communication area is a gluing area.
Further, specifically, the step S3 specifically includes the following steps:
s31, inputting the gluing area into the target detection model for detection to obtain line information and position coordinate information of the gluing area;
s32, calculating the area of the gluing area according to the line information and the position coordinate information;
s33, comparing the area value of the gluing area with a preset threshold value;
if the glue is within the preset threshold range, judging that the glue exists, and entering step S4;
otherwise, the sealing glue is glue-free, and the sealing quality of the sealing glue is unqualified.
Further, specifically, the step S4 specifically includes the following steps:
s41, extracting an inner contour and an outer contour of the glue in the glue spreading area according to the line information, wherein the glue is formed between the inner contour and the outer contour of the glue;
s42, detecting whether the inner colloid outline and the outer colloid outline are closed or not;
if the sealing is closed, the glue is not broken, and the step S5 is carried out;
otherwise, the sealing glue is broken, and the sealing quality of the sealing glue is unqualified.
Further, in particular, the width value of the gel profileWThe calculation comprises the following steps:
wherein ,x n1 the abscissa representing the outer contour of the glue body,x n2 the abscissa representing the inner contour of the glue body,y n1 representing the ordinate of the outer contour of the glue body,y n2 representing the ordinate of the inner contour of the glue body.
Further, specifically, the coordinates P of the centroidx，y) The calculation formula is as follows:
；
；
wherein ,nfor the amount of line information,ito form the number of triangles according to the number of vertexes, S i To form the area of triangle X i To S as i Is the sum of the abscissa of three vertexes of the area, Y i To S as i Is the sum of the ordinate of the three vertices of the area.
A sealant sealing quality detection device, the detection device comprising:
a visual controller for transmitting a control signal;
the industrial camera shoots a first image before gluing and a second image after gluing according to the control signal;
the algorithm moving end is used for executing the sealant sealing quality detection method;
a display that displays the first image and the second image photographed by the industrial camera;
a computer device, comprising:
a processor;
a memory for storing executable instructions;
the processor is used for reading the executable instructions from the memory and executing the executable instructions to realize the sealant sealing quality detection method.
A computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to implement the sealant sealing quality detection method as described above
The sealing quality detection method for the sealant has the advantages that whether the sealant is coated on the correct position can be rapidly and accurately distinguished, the sealing quality detection efficiency of the sealant is improved, the sealing quality detection accuracy is high, and the applicability is high.
Drawings
The application will be further described with reference to the drawings and examples.
Fig. 1 is a schematic flow chart of a first embodiment of the present application.
Fig. 2 is a schematic view of a glue application area in accordance with a first embodiment of the application.
Fig. 3 is a schematic diagram of a differential image in accordance with a first embodiment of the present application.
FIG. 4 is a schematic illustration of an interrupted and unbroken glue according to an embodiment of the present application.
Fig. 5 is a schematic view of the width of the glue profile on the glue spreading area according to the first embodiment of the present application.
FIG. 6 is a schematic diagram of a neutron region according to an embodiment of the application.
Fig. 7 is a schematic view of a bone line according to an embodiment of the present application.
Fig. 8 is a schematic diagram of a device structure according to a second embodiment of the present application.
Fig. 9 is a schematic diagram of a computer device according to a third embodiment of the present application.
201, a vision controller; 202. an industrial camera; 203. an algorithm moving end; 204. a display;
10. a computer device; 1002. a processor; 1004 a memory; 1006. and a transmission device.
Detailed Description
The application will now be described in further detail with reference to the accompanying drawings. The drawings are simplified schematic representations which merely illustrate the basic structure of the application and therefore show only the structures which are relevant to the application.
In the description of the present application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings are merely for convenience in describing the present application and simplifying the description, and do not indicate or imply that the device or element being referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present application. Furthermore, features defining "first", "second" may include one or more such features, either explicitly or implicitly. In the description of the present application, unless otherwise indicated, the meaning of "a plurality" is two or more.
In the description of the present application, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art.
Embodiment one: the embodiment of the application provides a method for detecting the sealing quality of sealant, as shown in fig. 1, comprising the following steps:
s1, acquiring a first image before gluing and a second image after gluing. Further, an image of the inspected product is acquired by an industrial camera.
S2, preprocessing the first image and the second image to obtain a gluing area. The glue area obtained by taking the detected product as the housing of the vehicle controller is shown in fig. 2.
And S3, judging whether the gluing area is glued or not through the target detection model, and if so, entering the next step.
S4, acquiring a colloid outline of the gluing area, judging whether the gluing area has broken glue according to the colloid outline, and if the gluing area has no broken glue, entering the next step.
S5, calculating the width value of the colloid outlineWComparing with the preset width value, judging whether the glue spreading area has glue overflow, if so, determining that the width value of the glue profileWAnd if the glue overflow is not generated within the range of the preset width value, entering the next step.
S6, calculating skeleton lines of the gluing area, obtaining the ratio of the skeleton lines on the colloid, comparing the ratio with a preset threshold, judging whether the gluing area has less glue, and if the gluing area has less glue, judging that the sealing quality of the sealing glue is qualified.
In this embodiment, the step S2 specifically includes the following steps:
s21, gray processing is carried out on the first image and the second image to obtain a first gray image and a first gray imageA second gray scale image; further, gray processing is performed on the first image and the second image by using a difference method, and the first image is set asf n The second image isf n-1 The first gray-scale image is recorded asf n （x，y) The second gray level image is recorded asf n-1 （x，y）。
S22, subtracting the gray value of the pixel point on the second gray image from the gray value of the pixel point on the first gray image to obtain a difference image D n Acquired differential image D n As shown in fig. 3, further, the differential image D n The calculation formula is as follows:
。
it should be noted that, because the acquired first image and the second image are three-channel color images, in order to ensure that the acquired images have enough light sources during image shooting, the illumination brightness is increased, so that the acquired first image and second image have serious reflection inside, although the reflection can be removed by adopting a traditional vision processing algorithm, the algorithm does not have certain advantages for detecting the sealing quality of the sealant under other illumination conditions, in this embodiment, the differential image D is obtained by the differential processing of the first image without glue and the second image with glue coated n Acquiring a differential image D n， Only the information of the colloid part is reserved, so that the sealing quality detection of the sealant aiming at different illumination conditions is facilitated, and the applicability is wide.
S23, for the differential image D n， Performing brightness self-adaptive adjustment; further, by calculating the difference image D n Is compared with a reference brightness value, and in the image processing, an add function can be used to compare the differential image D n To adjust the brightness of the image by adding and subtracting the pixel values of the image to realize the differential image D n The calculation formula of the brightness compensation and the average gray value is as follows:
wherein a is a differential image D n Is high, b is the differential image D n Is not limited to a wide range.
Brightness compensation for differential image D based on reference brightness value n The compensation is carried out on each pixel in the image, and the calculation method is as follows:
wherein ,kis the reference luminance value.
S24, filtering the difference image with the brightness adjusted by using a filter to obtain a filtered image, wherein a filtering operator of the filter is set as a mean operator, and can be a summation operator or other self-defining operators, and the size and the step length of the filter are set according to detection requirements. Because the light reflected by the acquired image has randomness, partial colloid information is possibly missing in the information of the colloid in the differential image, the gray value index of all pixel points of the differential image after brightness adjustment can be calculated by utilizing the filter on the basis of keeping colloid characteristics, the colloid characteristics are enhanced, the missing information of the colloid is supplemented as much as possible on the premise of not increasing noise, and the measurement accuracy is improved.
S25, dividing the filtered image into a foreground and a background by the Ojin method segmentation to obtain a binary image.
The division calculation formula of the Ojin method is as follows:
wherein ,vandv ’ respectively representing the gray values of pixels before and after binarization of the binary image;
Kas a function of the variance of the values,n c1 andn c2 the number of the two pixel values after binarization,m c1 andm c2 respectively, are the average values of the gray values of the two pixels before binarization.
The filtering image is divided into a foreground and a background by adopting the oxford method, so that a binary image is obtained, and compared with other binary methods, the adaptive threshold mechanism of the oxford method is beneficial to improving the robustness of the algorithm to the integral gray change of the imaging image.
S26, calculating a maximum communication area based on the binary image, wherein the maximum communication area is a gluing area. The difference image after brightness adjustment is filtered through the filter, internal noise can be filtered, but a plurality of external noise exists, and the control circuit board installed in the automobile lamp housing as shown in fig. 3 can carry over noise due to overexposure, the obtained maximum communication area can remove the external noise which is not filtered, the colloid part characteristics are enhanced, and the detection accuracy can be further improved.
In this embodiment, the step S3 specifically includes the following steps:
s31, inputting the gluing area into a target detection model for detection, and obtaining line information and position coordinate information of the gluing area.
S32, calculating the area of the gluing area according to the line information and the position coordinate information.
S33, comparing the area value of the gluing area with a preset threshold value; if the glue is within the preset threshold range, judging that the glue exists, and entering step S4; otherwise, the sealing glue is glue-free, and the sealing quality of the sealing glue is unqualified.
It should be noted that, in this embodiment, whether the glue spreading area has a glue profile or not may also be determined directly according to the obtained line information, whether glue is present or not is determined, if the glue profile is present, the glue spreading area has glue, otherwise, the glue spreading area has no glue.
In this embodiment, the step S4 specifically includes the following steps:
s41, extracting the inner contour and the outer contour of the glue in the glue coating area according to the line information, and forming glue between the inner contour and the outer contour of the glue.
S42, detecting whether the inner contour of the colloid and the outer contour of the colloid are closed; if the sealing is performed, the glue is not broken, as shown in fig. 4 (b), and the step S5 is performed; otherwise, the sealing quality of the sealant is failed, as shown in fig. 4 (a). Further, whether the inner contour of the colloid and the outer contour of the colloid form a seal or not is detected by an Opencv image processing method.
In the present embodiment, step S5 includes the step of measuring the width of the gel profileWThe calculation comprises the following steps:
wherein ,x n1 the abscissa of the outer contour of the glue body is indicated,x n2 the abscissa of the inner contour of the glue is indicated,y n1 the ordinate representing the outer contour of the glue body,y n2 representing the ordinate of the inner contour of the glue.
In order to increase the processing speed, as shown in fig. 5, the width values of all the colloid profiles were calculatedWBy traversing the width values of all colloid profilesW，Obtaining the width value of the maximum colloid outline between the colloid outline and the colloid outlineW1Width value of the maximum colloid profileW1Comparing with the preset threshold, if the width value is larger than the preset threshold, overflowing the glue, and comparing with the width value of each glue profile calculated in the middle of the treatment processWAnd compared with a preset threshold value, the processing speed is improved, and the sealing quality detection efficiency is further improved.
In this embodiment, the step S6 specifically includes the following steps:
s61, obtaining the vertexes of the gluing area and the coordinates of the vertexes, referring to FIG. 6, the vertexes of the gluing area are vertexes H, I, J and L.
S62, calculating the coordinate P of the mass center of the gluing area according to the coordinate of the vertexx，y) The method comprises the steps of carrying out a first treatment on the surface of the Further, the coordinate P of the mass center is%x，y) The calculation formula is as follows:
；
；
wherein ,nfor the amount of line information,ito form the number of triangles according to the number of vertexes, S i To form the area of triangle X i To S as i Is the sum of the abscissa of three vertexes of the area, Y i To S as i Is the sum of the ordinate of the three vertices of the area.
S63, dividing the gluing area according to the vertexes and the barycenter P to form a plurality of subareas, wherein the number of subareas is the same as that of the vertexes, and the subareas shown in FIG. 6 are subareas HPI, subarea IPL, subarea LPJ and subarea JPH respectively.
S64, obtaining pixel points A (x 1 ，y 1 ) And pixel point a (x 1 ，y 1 ) The nearest pixel point a (x 2 ，y 2 ) Calculating the coordinates of the center point between the pixel point A and the pixel point a, wherein the coordinates C of the center point are ((x) 1 +x 2 )/2，(y 1 +y 2 ) 2); and traversing all pixel points of the outer contour of the colloid and the inner contour of the colloid, calculating to obtain coordinates of all center points, wherein a straight line formed by connecting all center points is a skeleton line, and referring to fig. 7.
S65, counting the ratio of the bone lines of each sub-region on the colloid, comparing the ratio with a preset threshold, and judging whether the gluing region has less glue; if no less glue exists, the sealing quality of the sealant is qualified; otherwise, if a few glues, the sealing quality of the sealant is unqualified, and the efficiency of the sealing quality detection of the sealant is further improved.
Further, taking the subarea HPI as an example, the ratio of the subarea HPI skeleton line on the colloid is calculated as the pixel point S of the actual skeleton line on the colloid i Pixel point T on colloid with ideal skeleton line i Is a ratio of (2).
In this embodiment, the determination time of the glue overflow determination is shorter than the determination time of the glue less determination, the glue overflow determination is performed first, and then the glue less determination is performed, and if the glue overflows, the seal quality of the seal glue is directly determined to be unqualified, so that the detection efficiency can be further improved.
In conclusion, the sealing quality detection method of the sealant can rapidly and accurately distinguish whether the sealant is coated on the correct position, improves the sealing quality detection efficiency of the sealant, and has high sealing quality detection accuracy and high applicability.
Example 2: based on the same inventive concept as the method for detecting the sealing quality of the sealant in the foregoing embodiment, as shown in fig. 8, an embodiment of the present application provides a device for detecting the sealing quality of the sealant, where the device includes:
a vision controller 201 for transmitting a control signal;
an industrial camera 202 for photographing a first image before the glue coating and a second image after the glue coating according to the control signal;
the algorithm moving end 203 is configured to execute the sealant sealing quality detection method as described above;
a display 204 displaying a first image and a second image photographed by the industrial camera;
the above-described various modifications and specific examples of the method for detecting the sealing quality of a sealant in the first embodiment of fig. 1 are equally applicable to the device for detecting the sealing quality of a sealant in the present embodiment, and those skilled in the art will be aware of the implementation of the device for detecting the sealing quality of a sealant in the present embodiment through the foregoing detailed description of the method for detecting the sealing quality of a sealant, so that the description will not be repeated here for brevity.
Example 3: the embodiment of the application provides a computer device, which comprises a processor and a memory, wherein at least one instruction or at least one section of program is stored in the memory, and the at least one instruction or the at least one section of program is loaded and executed by the processor to realize the sealant sealing quality detection method provided by the embodiment of the method.
Fig. 9 shows a schematic hardware structure of a device for implementing a sealant sealing quality detection method provided by an embodiment of the present application, where the device may participate in forming or including an apparatus or a system provided by an embodiment of the present application. As shown in fig. 9, the computer device 10 may include one or more processors 1002 (the processors may include, but are not limited to, processing means such as a microprocessor MCU or a programmable logic device FPGA), a memory 1004 for storing data, and a transmission means 1006 for communication functions. In addition, the method may further include: display devices, input/output interfaces (I/O interfaces), universal Serial Bus (USB) ports (which may be included as one of the ports of the I/O interfaces), network interfaces, power supplies, and/or cameras. It will be appreciated by those skilled in the art that the configuration shown in fig. 9 is merely illustrative and is not intended to limit the configuration of the electronic device. For example, computer device 10 may also include more or fewer components than shown in FIG. 9, or have a different configuration than shown in FIG. 9.
It should be noted that the one or more processors and/or other data processing circuits described above may be referred to herein generally as "data processing circuits. The data processing circuit may be embodied in whole or in part in software, hardware, firmware, or any other combination. Furthermore, the data processing circuitry may be a single stand-alone processing module, or incorporated in whole or in part into any of the other elements in the computer device 10 (or mobile device). As referred to in embodiments of the application, the data processing circuit acts as a processor control (e.g., selection of the path of the variable resistor termination connected to the interface).
The memory 1004 may be used to store software programs and modules of application software, such as a program instruction/data storage device corresponding to a sealant sealing quality detection method in the embodiment of the present application, and the processor executes the software programs and modules stored in the memory 1004, thereby executing various functional applications and data processing, that is, implementing a method as described above. Memory 1004 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 1004 may further include memory located remotely from the processor, which may be connected to computer device 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission means 1006 is for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communications provider of the computer device 10. In one example, the transmission means 1006 includes a network adapter (Network Interface Controller, NIC) that can be connected to other network devices via a base station to communicate with the internet. In one example, the transmission device 1006 may be a Radio Frequency (RF) module for communicating with the internet wirelessly.
The display device may be, for example, a touch screen type Liquid Crystal Display (LCD) that may enable a user to interact with a user interface of the computer device 10 (or mobile device).
Example 4: the embodiment of the application also provides a computer readable storage medium, which can be arranged in a server to store at least one instruction or at least one section of program related to the sealant sealing quality detection method in the method embodiment, wherein the at least one instruction or the at least one section of program is loaded and executed by the processor to realize the sealant sealing quality detection method provided by the method embodiment.
Alternatively, in this embodiment, the storage medium may be located in at least one network server among a plurality of network servers of the computer network. Alternatively, in the present embodiment, the storage medium may include, but is not limited to: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Example 5: embodiments of the present application also provide a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs a sealant sealing quality detection method provided in the above-described various alternative embodiments.
It should be noted that: the sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And the foregoing description has been directed to specific embodiments of this application. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The embodiments of the present application are described in a progressive manner, and the same and similar parts of the embodiments are all referred to each other, and each embodiment is mainly described in the differences from the other embodiments. In particular, for apparatus, devices and storage medium embodiments, the description is relatively simple as it is substantially similar to method embodiments, with reference to the description of method embodiments in part.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program for instructing relevant hardware, where the program may be stored in a computer readable storage medium, and the storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
With the above-described preferred embodiments according to the present application as an illustration, the above-described descriptions can be used by persons skilled in the relevant art to make various changes and modifications without departing from the scope of the technical idea of the present application. The technical scope of the present application is not limited to the description, but must be determined according to the scope of claims.
Claims (9)
1. The sealing quality detection method of the sealant is characterized by comprising the following steps of:
s1, acquiring a first image before gluing and a second image after gluing;
s2, preprocessing the first image and the second image to obtain a gluing area;
s3, judging whether the glue coating area is coated with glue or not through a target detection model, and if so, entering the next step;
s4, acquiring a colloid outline of the gluing area, judging whether the gluing area has broken glue according to the colloid outline, and if the gluing area has no broken glue, entering the next step;
s5, calculating the width value of the colloid outlineWComparing with a preset width value, judging whether the glue spreading area has glue overflow or not, if so, determining that the width value of the glue profileWIf the glue overflow is not generated within the range of the preset width value, entering the next step;
s6, calculating skeleton lines of the gluing area, obtaining the ratio of the skeleton lines on the colloid, comparing the ratio with a preset threshold, judging whether the gluing area has less glue, and if the gluing area has less glue, judging that the sealing quality of the sealing glue is qualified;
the step S6 specifically includes the following steps:
s61, obtaining the vertex of the gluing area and the coordinates of the vertex;
s62, calculating the coordinate P of the mass center of the gluing area according to the coordinate of the vertexx，y）；
S63, dividing the gluing area according to the vertexes and the centroids to form a plurality of subareas, wherein the number of the subareas is the same as that of the vertexes;
s64, calculating a bone line of the gluing area, wherein the calculation of the bone line of the gluing area comprises the following steps: the colloid outline comprises an colloid outer outline and an colloid inner outline, and pixel points A (x 1 ，y 1 ) And the pixel point a (x 1 ，y 1 ) The nearest pixel point a (x 2 ，y 2 ) Calculating the pixelTraversing all pixel points of the outer contour of the colloid and the inner contour of the colloid by the coordinates of the central point between the point A and the pixel point a, and calculating to obtain the coordinates of all the central points, wherein the straight line formed by connecting all the central points is the skeleton line;
s65, counting the ratio of the bone lines of each sub-region on the colloid, comparing the ratio with a preset threshold, and judging whether the gluing region has less glue;
if no less glue exists, the sealing quality of the sealant is qualified;
otherwise, if the glue is few, the sealing quality of the sealant is unqualified.
2. The method for detecting the sealing quality of the sealant according to claim 1, wherein the step S2 specifically includes the steps of:
s21, gray processing is carried out on the first image and the second image, and a first gray image and a second gray image are obtained;
s22, subtracting the gray value of the pixel point on the second gray level image from the gray value of the pixel point on the first gray level image to obtain a differential image;
s23, performing brightness self-adaptive adjustment on the differential image;
s24, filtering the difference image with the brightness adjusted by using a filter to obtain a filtered image;
s25, dividing the filtered image into a foreground and a background by the Ojin method segmentation to obtain a binary image;
s26, calculating a maximum communication area based on the binary image, wherein the maximum communication area is a gluing area.
3. The method for detecting the sealing quality of the sealant according to claim 1, wherein the step S3 specifically includes the steps of:
s31, inputting the gluing area into the target detection model for detection to obtain line information and position coordinate information of the gluing area;
s32, calculating the area of the gluing area according to the line information and the position coordinate information;
s33, comparing the area value of the gluing area with a preset threshold value;
if the glue is within the preset threshold range, judging that the glue exists, and entering step S4;
otherwise, the sealing glue is glue-free, and the sealing quality of the sealing glue is unqualified.
4. The method for detecting the sealing quality of the sealant according to claim 3, wherein the step S4 specifically comprises the steps of:
s41, extracting an inner contour and an outer contour of the glue in the glue spreading area according to the line information, wherein the glue is formed between the inner contour and the outer contour of the glue;
s42, detecting whether the inner colloid outline and the outer colloid outline are closed or not;
if the sealing is closed, the glue is not broken, and the step S5 is carried out;
otherwise, the sealing glue is broken, and the sealing quality of the sealing glue is unqualified.
5. The method for detecting the quality of a sealant according to claim 4, wherein the width of the gel profile is as followsWThe calculation comprises the following steps:
wherein ,x n1 the abscissa representing the outer contour of the glue body,x n2 the abscissa representing the inner contour of the glue body,y n1 representing the ordinate of the outer contour of the glue body,y n2 representing the ordinate of the inner contour of the glue body.
6. The method for detecting the sealing quality of a sealant according to claim 1, wherein the coordinate P of the centroid is #x，y) The calculation formula is as follows:
；
；
wherein ,nfor the amount of line information,ito form the number of triangles according to the number of vertexes, S i To form the area of triangle X i To S as i Is the sum of the abscissa of three vertexes of the area, Y i To S as i Is the sum of the ordinate of the three vertices of the area.
7. A sealant sealing quality detection device, characterized in that the detection device comprises:
a vision controller (201) for transmitting control signals;
an industrial camera (202) for shooting a first image before gluing and a second image after gluing according to the control signal;
an algorithmic mobile terminal (203) for performing the sealant sealing quality detection method according to any one of claims 1 to 6;
a display (204) displays the first image and the second image captured by the industrial camera.
8. A computer device, comprising:
a processor;
a memory for storing executable instructions;
wherein the processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the sealant sealing quality detection method of any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, which when executed by a processor, causes the processor to implement the sealant sealing quality detection method according to any one of claims 1 to 6.
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