CN113643233B - Oily coating detection method, system and equipment, and computer readable storage medium - Google Patents
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- 239000011248 coating agent Substances 0.000 title claims abstract description 145
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- 230000007547 defect Effects 0.000 claims abstract description 154
- 238000006748 scratching Methods 0.000 claims abstract description 46
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- 238000007781 pre-processing Methods 0.000 claims abstract description 10
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- 238000005260 corrosion Methods 0.000 claims description 22
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- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 description 3
- 229910052744 lithium Inorganic materials 0.000 description 3
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Abstract
The application discloses an oily coating detection method, an oily coating detection system, oily coating detection equipment and a computer readable storage medium, and relates to the technical field of image processing, wherein the oily coating detection method comprises the following steps: collecting an initial image; preprocessing the initial image to obtain a coating region to be detected; obtaining a plurality of first connected domain information and a plurality of second connected domain information according to the coating region to be detected; obtaining a scratch characteristic value according to the ratio of the widths of two adjacent first connected domain information; if the scratching characteristic value is smaller than or equal to the scratching threshold value, judging that the scratching defect exists; obtaining a scratch characteristic value according to the width and the height of the same second connected domain information; and if the scratch characteristic value is larger than the scratch threshold value, judging that the scratch is a scratch defect. According to the oily coating detection method, automatic defect detection can be realized, false leakage detection is reduced, and detection efficiency is improved.
Description
Technical Field
The present application relates to the field of image processing technologies, and in particular, to a method, a system, a device, and a computer readable storage medium for detecting an oily coating.
Background
The coating quality of the coating machine directly influences the quality of the lithium battery, when the coating machine is used for coating, various flaw defects can be formed on the oily coating, if the defects cannot be found and treated in time, the quality problem of a finished product can be influenced, and unnecessary waste can be caused. At present, a field worker finds out serious flaws through a visual inspection mode and stops the machine in time, the detection mode has lower detection efficiency, is unfavorable for operation treatment on a production line, and can not avoid accidental misjudgment and missed judgment caused by visual inspection of human eyes.
Disclosure of Invention
The application aims to at least solve one of the technical problems in the prior art, and provides an oily coating detection method, an oily coating detection system, oily coating detection equipment and a computer readable storage medium, which can realize automatic defect detection, reduce false leakage detection and improve detection efficiency.
An oily coating detection method according to an embodiment of the first aspect of the present application includes:
Collecting an initial image;
preprocessing the initial image to obtain a coating region to be detected;
Obtaining a plurality of first connected domain information and a plurality of second connected domain information according to the coating region to be detected;
obtaining a scratch characteristic value according to the ratio of the widths of two adjacent first connected domain information;
If the scratching characteristic value is smaller than or equal to the scratching threshold value, judging that the scratching defect exists;
Obtaining a scratch characteristic value according to the width and the height of the same second connected domain information;
and if the scratch characteristic value is larger than the scratch threshold value, judging that the scratch is a scratch defect.
The oily coating detection method provided by the embodiment of the application has at least the following technical effects: the collected initial image is automatically detected through an image processing visual detection technology without manual operation, so that whether the oily coating coated on the pole piece is defective or not is detected, a link of manual watching is removed, false leakage detection is reduced, detection efficiency is improved, and product quality is improved.
According to some embodiments of the application, the preprocessing the initial image to obtain a coating region to be detected includes:
sequentially carrying out binarization and connected domain processing on the initial image to obtain a processed image;
acquiring a coating width corresponding to the initial image;
And extracting the coating region to be detected from the processed image according to the coating width.
According to some embodiments of the application, the obtaining the first connected domain information and the second connected domain information according to the coating region to be detected includes:
dividing the coating region to be detected according to a first fixed threshold value to obtain a first binary image;
Performing corrosion expansion treatment on the first binary image to obtain a first corrosion expansion diagram;
And carrying out connected domain processing on the first corrosion expansion map to obtain a plurality of pieces of first connected domain information.
According to some embodiments of the application, the obtaining the first connected domain information and the second connected domain information according to the coating area to be detected further includes:
dividing the coating region to be detected according to a second fixed threshold value to obtain a second binary image;
performing corrosion expansion treatment on the second binary image to obtain a second corrosion expansion diagram;
And carrying out connected domain processing on the second corrosion expansion map to obtain a plurality of pieces of second connected domain information.
According to some embodiments of the application, the obtaining the scratch characteristic value according to the ratio of the widths of two adjacent first connected domain information includes:
Transversely dividing and cutting each piece of first connected domain information equally to obtain a plurality of first equal-divided regions;
Respectively obtaining the width ratio of two corresponding first equal-dividing areas of two adjacent first connected domain information in each transverse equal-dividing section to obtain a plurality of width ratio values;
Taking a plurality of width ratios as the scratching characteristic values;
Correspondingly, if the scratching characteristic value is smaller than or equal to the scratching threshold value, judging that the scratching defect is generated, including:
comparing each of the width ratios with the scratch threshold value respectively;
And if each width ratio is smaller than or equal to the scratching threshold value, judging that the scratching defect exists.
According to some embodiments of the application, the scratch threshold comprises a ratio threshold, a threshold width value, and a threshold height value; and if the scratch characteristic value is greater than the scratch threshold value, judging that the scratch is defective, wherein the method comprises the following steps:
Comparing the high value of the scratch characteristic value with the threshold high value to obtain a first ratio;
comparing the width of the scratch characteristic value with the threshold width value to obtain a second ratio;
comparing the ratio of the height to the width of the scratch characteristic value with the ratio threshold to obtain a third ratio;
And if the first ratio, the second ratio and the third ratio are not in the corresponding threshold values, judging that the scratch defect exists.
According to some embodiments of the application, after the initial image is acquired, the method further comprises:
Loading a deep learning model;
Acquiring image size information, a first execution degree and a second execution degree;
and inputting the image size information, the first execution degree and the second execution degree into the deep learning model to obtain dry material defect information and bubble defect information.
An oily coating detection system according to an embodiment of the second aspect of the application comprises:
the camera streaming module is used for acquiring an initial image;
The algorithm processing module is used for detecting scratch defects, dry material defects, bubble defects and the like of the coating;
The communication management module is used for controlling the algorithm processing module to detect different defects and stop the system;
And the parameter management module is used for setting judging standards of defects such as coating area information, scratch defects, dry material defects and bubble defects.
An electronic device according to an embodiment of a third aspect of the present application includes:
At least one processor, and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores instructions that are executed by the at least one processor to cause the at least one processor to perform the method of detecting an oil coating as described in the first aspect above when the instructions are executed.
The computer-readable storage medium according to the fourth aspect of the embodiment of the present application stores computer-executable instructions for causing a computer to execute the oil coating detection method according to the first aspect described above.
Additional aspects and advantages of the application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application.
Drawings
The application is further described below with reference to the drawings and examples;
FIG. 1 is a schematic flow chart of an oily coating detection method according to an embodiment of the application;
FIG. 2 is a schematic diagram of an oil coating detection system according to another embodiment of the present application;
fig. 3 is a schematic diagram of an electronic device according to another embodiment of the application.
Detailed Description
Reference will now be made in detail to the present embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein the accompanying drawings are used to supplement the description of the written description so that one can intuitively and intuitively understand each technical feature and overall technical scheme of the present application, but not to limit the scope of the present application.
In the description of the present application, a number means one or more, a number means two or more, and greater than, less than, exceeding, etc. are understood to not include the present number, and above, below, within, etc. are understood to include the present number. The description of the first and second is for the purpose of distinguishing between technical features only and should not be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
The coating quality of the coating machine directly influences the quality of the lithium battery, and various flaw defects, such as bubble defects caused by uneven stirring of the coating, dry material defects caused by particles of the coating, scratch defects caused by serious dry material defects and scratch crack defects caused by serious scratch defects, appear in the oily coating on the coating machine during coating. If defects cannot be found and processed in time, the quality problem of the finished product is affected, and unnecessary waste is caused. At present, a field worker finds out serious flaws through a visual inspection mode and stops the machine in time, the detection mode has lower detection efficiency, is unfavorable for operation treatment on a production line, and can not avoid accidental misjudgment and missed judgment caused by visual inspection of human eyes.
Based on the above, the embodiments of the present application provide a method, a system, a device, and a computer readable storage medium for detecting an oil coating, which can realize automatic defect detection, reduce false detection, and improve detection efficiency. In the lithium battery pole piece oily coating scene, the material characteristics of the oily coating are fully utilized, the manufacturing process of the oily coating and the front cause and the consequence of defect generation are known through on-site observation, the picture acquired by a camera is automatically detected through an image processing visual detection technology, manual operation is not needed, whether the oily coating coated on the pole piece by a coating machine on a production line generates flaws or not is solved, the link of manual observation is removed, the coating flaws can be timely detected and fed back to a system, the shutdown efficiency is improved, the waste generated by the defects is reduced, and the quality of products is improved.
An oily coating detection method according to an embodiment of the present application is described below with reference to the accompanying drawings.
As shown in fig. 1, the method for detecting an oil coating according to the embodiment of the first aspect of the present application at least includes the following steps:
S100: collecting an initial image;
S200: preprocessing an initial image to obtain a coating region to be detected;
s300: obtaining a plurality of first connected domain information and a plurality of second connected domain information according to the coating region to be detected;
s400: obtaining a scratch characteristic value according to the width ratio of the two adjacent first connected domain information;
S500: if the scratching characteristic value is smaller than or equal to the scratching threshold value, judging that the scratching defect is generated;
S600: obtaining scratch characteristic values according to the width and the height of the same second connected domain information;
s700: if the scratch characteristic value is larger than the scratch threshold value, judging that the scratch is a scratch defect.
In some embodiments, step S100: collecting an initial image; specifically, the oily coating is collected by an image collecting unit, and a black-and-white image on the front surface of the coating, namely an initial image, is obtained.
Step S200: preprocessing an initial image to obtain a coating region to be detected; specifically, the initial image, that is, the black-and-white image of the front surface of the coating acquired in step S100, is preprocessed, where preprocessing includes binarization and connected domain detection, and a region of interest, that is, a region of the coating to be detected, is obtained according to information such as a width, that is, a coating width of the coating. Further, in this embodiment, the coating region to be detected includes two regions, each represented by ROI l[x0,x1],ROIr[x2,x3; subscripts l and r represent the to-be-detected coating region of the left region of the coating and the to-be-detected coating region of the right region of the coating, respectively, x 0 and x 1 represent the x-axis coordinates of the left boundary of the to-be-detected coating region on the front black-and-white image of the coating and the x-axis coordinates of the right boundary of the to-be-detected coating region on the front black-and-white image of the coating, respectively, and x 2 and x 3 represent the x-axis coordinates of the left boundary of the to-be-detected coating region on the right side of the coating and the right boundary of the to-be-detected coating region on the front black-and-white image of the coating, respectively.
Step S300: obtaining a plurality of first connected domain information and a plurality of second connected domain information according to the coating region to be detected; specifically, defect detection is performed on the two coating areas to be detected obtained in the step S200, taking one of the coating areas to be detected as an example, according to the characteristics of the scratch defect, a first fixed threshold is set, and according to the first fixed threshold, the coating areas to be detected are subjected to fixed threshold segmentation, corrosion expansion, connected domain processing and the like to obtain a plurality of pieces of first connected domain information, stats 1 (i, x, y, w, h, c) (i=1, 2, 3.) wherein x and y are coordinate positions, w is wide, h is high, and c is a centroid; according to the characteristics of scratch defects, a second fixed threshold value is set, and the coating area to be detected is subjected to fixed threshold value segmentation, corrosion expansion, connected domain treatment and the like according to the second fixed threshold value, so that a plurality of pieces of second connected domain information are obtained, wherein stats 2 (i, x, y, w, h, c) (i=1, 2, 3.) are obtained, x and y are coordinate positions, w is wide, h is high, and c is a centroid.
Step S400: obtaining a scratch characteristic value according to the width ratio of the two adjacent first connected domain information; step S500: if the scratching characteristic value is smaller than or equal to the scratching threshold value, judging that the scratching defect is generated; specifically, in this embodiment, when the scratch feature value is detected, a backlight source is used to obtain an image, when a scratch defect exists, the cross section of the scratch defect is a downward horn mouth, according to the feature, a scratch threshold is set, if the scratch feature value is smaller than or equal to the scratch threshold, the scratch defect is determined, and an alarm is sent out and the coater is controlled to stop; otherwise, scratch defect detection is carried out.
Step S600: obtaining scratch characteristic values according to the width and the height of the same second connected domain information; step S700: if the scratch characteristic value is larger than the scratch threshold value, judging that the scratch is a scratch defect; specifically, a scratch threshold is set according to the characteristics of scratch defects, a scratch characteristic value is obtained according to the ratio of the width to the height of the same second connected domain information, if the scratch characteristic value is larger than the scratch threshold, the scratch defect is judged, and if the scratch defect continuously occurs within 1 meter, an alarm is sent out and the coating machine is controlled to stop; otherwise, dry material detection and bubble detection are carried out.
According to the oily coating detection method provided by the embodiment of the application, the acquired initial image is automatically detected through the image processing visual detection technology, manual operation is not needed, the detection method is used for detecting whether the oily coating coated on the pole piece has flaws or not, a link of manual observation is removed, false detection is reduced, and the detection efficiency is improved, so that the quality of a product is improved.
In some embodiments of the present application, step S100: after the initial image is acquired, the method further comprises the steps of detecting the dry material defect and the bubble defect, wherein the dry material defect and the bubble defect at least comprise the following steps:
Loading a deep learning model;
Acquiring image size information, a first execution degree and a second execution degree;
and inputting the image size information, the first execution degree and the second execution degree into a deep learning model to obtain dry material defect information and bubble defect information.
In some embodiments, after step S700, if both the scratch defect and the scratch defect detection pass, then dry defect and bubble defect detection is performed: a deep learning model, specifically YOLOv, is loaded, wherein the model has been trained in advance with a large number of coating images. Image size information, a first execution degree, and a second execution degree are acquired, specifically, according to the picture size, the length and the width are set to img_size=640, the first execution degree conf_th=0.3, and the second execution degree iou_th=0.6. The image size information, the first execution degree and the second execution degree are input into a deep learning model to obtain dry material defect information and bubble defect information, specifically, the picture size (i.e. the length and the width are img_size=640), the first execution degree conf_th=0.3 and the second execution degree iou_th=0.6 are input into a trained YOLOv model, and coordinate information and size information of the dry material defect and the bubble defect are obtained through the trained YOLOv model, wherein the size information comprises the width and the height. If the defect of the dry material defect or the bubble defect occurs within 1 meter for 3 times, an alarm is sent out and the coater is controlled to stop; otherwise, continuing the defect detection of the next round.
After step S100, according to the collected initial image, the scratch defect, the dry material defect and the bubble defect are sequentially detected, after the current defect detection is passed, the next defect is detected, if the four types of defects are all passed, steps S100 to S700 are repeated, and the steps related to the dry material defect and the bubble defect are repeated, so that the next round of defect detection is performed.
In other embodiments, after step S100, detection of a scratch defect, a dry defect, and a bubble defect may be performed simultaneously, and when any defect does not meet the quality requirement, an alarm is sent and the coater is controlled to stop; if the four defects are detected, continuing to detect the defects of the next round.
In some embodiments of the present application, step S200: preprocessing an initial image to obtain a coating area to be detected, wherein the method at least comprises the following steps:
sequentially carrying out binarization and connected domain processing on the initial image to obtain a processed image;
acquiring a coating width corresponding to an initial image;
And extracting a coating region to be detected from the processed image according to the coating width.
In some embodiments, binarization and connected domain processing are carried out on the acquired initial image, namely, the black-and-white image on the front surface of the coating to obtain a processed image; and extracting coating regions to be detected from the processed image according to the coating width of the actual coating corresponding to the initial image, wherein the two coating regions to be detected are specifically indicated by ROI l[x0,x1],ROIr[x2,x3 respectively. By the method, the coating region to be detected corresponding to the actual coating in the initial image can be extracted more accurately.
In some embodiments of the present application, step S300: according to the coating region to be detected, a plurality of first connected domain information and a plurality of second connected domain information are obtained, and the method at least comprises the following steps:
Dividing a coating region to be detected according to a first fixed threshold value to obtain a first binary image;
performing corrosion expansion treatment on the first binary image to obtain a first corrosion expansion diagram;
and carrying out connected domain processing on the first corrosion expansion map to obtain a plurality of pieces of first connected domain information.
In some embodiments, for scratch defect detection, a first fixed threshold Tscrape 1=200 is set according to an optimal effect of distinguishing foreground and background and image features corresponding to scratch defects; respectively carrying out fixed threshold segmentation on the two coating areas to be detected according to a first fixed threshold Tscrape & lt 1 & gt=200 to obtain first binary images, wherein the first binary images are respectively D1 l[x0,x1 and D1 r[x2,x3; respectively corroding and expanding the two first binary images D1 l[x0,x1 and D1 r[x2,x3 to obtain two first corrosion diagrams DO1 l[x0,x1 and DO1 r[x2,x3; and finally, respectively carrying out connected domain processing to obtain a plurality of first connected domain information stats 1 (i, x, y, w, h, c) (i=1, 2, 3..) wherein x and y are coordinate positions, w is wide, h is high, and c is a centroid.
In some embodiments of the present application, step S300: according to the coating region to be detected, first connected domain information and second connected domain information are obtained, and the method at least further comprises the following steps:
Dividing the coating region to be detected according to a second fixed threshold value to obtain a second binary image;
Performing corrosion expansion treatment on the second binary image to obtain a second corrosion expansion diagram;
and carrying out connected domain processing on the second corrosion expansion map to obtain a plurality of pieces of second connected domain information.
In some embodiments, for scratch defect detection, to eliminate the interference term, a second fixed threshold Tscrape 2=15 is set; respectively carrying out fixed threshold segmentation on the two coating areas to be detected according to a second fixed threshold Tscrape & lt 2 & gt=15 to obtain second binary images, wherein the second binary images are D2 l[x0,x1 and D2 r[x2,x3 respectively; respectively corroding and expanding the two second binary images D2 l[x0,x1 and D2 r[x2,x3 to obtain two second corrosion diagrams DO2 l[x0,x1 and DO2 r[x2,x3; and finally, respectively carrying out connected domain processing to obtain a plurality of first connected domain information stats 2 (i, x, y, w, h, c) (i=1, 2, 3..) wherein x and y are coordinate positions, w is wide, h is high, and c is a centroid.
In some embodiments of the present application, step S400: obtaining a scratch characteristic value according to the wide ratio of two adjacent first connected domain information, wherein the scratch characteristic value at least comprises the following steps:
transversely dividing and cutting each first connected domain information equally to obtain a plurality of first equal regions;
Respectively acquiring the width ratio of two corresponding first equal-dividing areas of two adjacent first connected domain information in each transverse equal-dividing section to obtain a plurality of width ratio values;
Taking a plurality of width ratio values as scratch characteristic values;
Correspondingly, step S500: if the scratch characteristic value is smaller than or equal to the scratch threshold value, judging that the scratch defect is generated, and at least comprising the following steps:
Comparing each width ratio with a scratch threshold;
And if each width ratio is smaller than or equal to the scratching threshold value, judging that the scratching defect is generated.
In some embodiments, each first connected domain information is transversely equally divided and truncated to obtain a plurality of first equal-divided regions; specifically, each first connected domain information stats 1 (i, x, y, w, h, c) (i=1, 2, 3.+ -.) is transversely equally truncated into three parts, resulting in three parts of first equal-divided regions stats 1 (i, x, y, w, h, c, j) (j=0, 1, 2); the transverse bisection cutoff may be one, five, seven or nine, and the more the transverse bisection cutoff is, the more accurate the transverse bisection cutoff is, but the higher the calculation complexity is, and in this embodiment, the three bisections are taken as examples, which are not particularly limited.
Respectively acquiring the width ratio of two corresponding first equal-dividing areas of two adjacent first connected domain information in each transverse equal-dividing section to obtain a plurality of width ratio values; specifically, for each pair of adjacent first connected domain information, performing connected domain processing on three first equal-divided regions stats 1 (i, x, y, w, h, c, j) (j=0, 1, 2) corresponding to each first connected domain information to obtain a wide stats 1 (i, x, y, w, h, c, j) [1,2] of each region, wherein 1 represents a connected domain, and 2 represents the width of the connected domain; and then according to the width ratio of the two corresponding first equal-dividing regions of the two adjacent first connected region information in each transverse equal-dividing region, obtaining three corresponding width ratio Ri1=stats 1(i,x,y,w,h,c,j)[1,2]/stats1 (i+1, x, y, w, h, c, j) [1,2], namely scratch characteristic values.
Correspondingly, each width ratio is compared with a scratch threshold, specifically, each width ratio Ri1 is compared with the scratch threshold, and the scratch threshold th1=0.67 is set according to the scratch defect. If each width ratio is smaller than or equal to the scratching threshold value, judging that the scratching defect exists; specifically, if each width ratio Ri1 meets Ri 1< = th1, detecting and judging that the coating machine is a scratch defect, and sending an alarm by the control system and controlling the coating machine to stop; otherwise, scratch defect detection is entered.
It is easily conceivable that, when comparing with the scratch threshold value, the width ratio corresponding to each pair of adjacent first connected domain information may be compared with the same, or that a set of width ratios corresponding to a plurality of pairs of adjacent first connected domain information may be compared with the same.
By the method, the characteristic value of the scratch defect is fully utilized to extract the characteristic value, and meanwhile, transverse equal division and cutoff are carried out for multiple threshold comparison, so that the detection accuracy is improved.
In some embodiments of the present application, the scratch threshold includes a ratio threshold, a threshold width value, and a threshold height value; step S700: if the scratch characteristic value is larger than the scratch threshold value, judging that the scratch is a scratch defect, and at least comprising the following steps:
comparing the scratch characteristic value with a threshold value to obtain a first ratio;
comparing the width of the scratch characteristic value with a threshold width value to obtain a second ratio;
comparing the ratio of the height to the width of the scratch characteristic value with a ratio threshold to obtain a third ratio;
And if the first ratio, the second ratio and the third ratio are not in the corresponding threshold values, judging that the scratch defect exists.
In some embodiments, prior to step S700, step S600: according to the width and height of the same second connected domain information, scratch characteristic values are obtained, and the method at least comprises the following steps: transversely dividing and cutting each second connected domain information equally to obtain a plurality of second equally divided regions; specifically, each second connected domain information stats 2 i, x, y, w, h, c) (i=1, 2, 3.+ -.) is transversely split into three parts, to obtain three parts of second split regions stats 2 (i, x, y, w, h, c, j) (j=0, 1, 2); carrying out connected domain treatment on three second bisected regions stats 2 (i, x, y, w, h, c, j) (j=0, 1, 2) to obtain wide stats 2 (i, x, y, w, h, c, j) [1,2] and high stats 2 (i, x, y, w, h, c, j) [1,3] of each region, wherein 1 represents the connected domain, 2 represents the width of the connected domain, and 3 represents the height of the connected domain; further, for scratches with break points in the middle, firstly performing a closing operation on the scratches, and then performing a connected domain treatment on the scratches to obtain the width and the height of each region; the width stats 2 (i, x, y, w, h, c, j) [1,2] of each region is taken as the width of the scratch characteristic value, the height stats 2 (i, x, y, w, h, c, j) [1,3] of each region is taken as the height of the scratch characteristic value, and the ratio ri2=stats (i, x, y, w, h, c, j) [1,3]/stats (i, x, y, w, h, c, j) [1,2] of each region of the same second communication region is taken as the ratio of the height to the width of the scratch characteristic value.
The scratch threshold includes a ratio threshold, a threshold width value, and a threshold height value, specifically, the ratio threshold is set to th2=5, the gate width value is set to 50, and the threshold height value is set to 200 according to the characteristics of the scratch defect. In step S700, specifically, if the width stats 2 (i, x, y, w, h, c, j) [1,2] of the scratch characteristic value is smaller than the threshold width value 50, the height stats 2 (i, x, y, w, h, c, j) [1,3] of the scratch characteristic value is larger than the threshold height value 200, the ratio Ri2 of the height to width of the scratch characteristic value is larger than the ratio threshold, i.e., ri2 > th2, all the above three are satisfied, the detection is determined as the scratch defect, and when the scratch defect continuously occurs in 1 meter, the control system sends an alarm and controls the coater to stop; otherwise, dry material detection is carried out.
By the method, the characteristic value of the scratch defect is fully utilized to extract the characteristic value, and meanwhile, transverse equal division and cutoff are carried out for multiple threshold comparison, so that the detection accuracy is improved.
An oily coating detection system according to an embodiment of the second aspect of the application comprises:
the camera streaming module is used for acquiring an initial image;
The algorithm processing module is used for detecting scratch defects, dry material defects, bubble defects and the like of the coating;
the communication management module is used for controlling the algorithm processing module to detect different defects and stop the system;
And the parameter management module is used for setting judging standards of defects such as coating area information, scratch defects, dry material defects and bubble defects.
As shown in fig. 2, in some embodiments, an oily coating detection system is provided for automatically detecting defects in an oily coating, comprising:
The camera flow taking module is used for collecting initial images, specifically, in the normal production process of the coating machine, the camera is used for collecting images and driving the encoder to move according to the running speed of the large roller of the coating machine so as to send pulses to the camera for real-time image collection;
The communication management module is used for controlling the algorithm processing module to detect different defects and stop the system, specifically, the running state of the coating machine is acquired after the system is required to send information, and the running of the algorithm processing module and the stop processing of the coating machine are controlled according to different states;
The algorithm processing module is used for detecting the scratch defects, dry material defects, bubble defects and the like of the coating, specifically, the oily coating detection method of the first aspect is used for detecting the scratch defects, dry material defects and bubble defects of the coating, and the results are fed back to the front end interface, the data storage module and the signal module for processing;
The parameter management module is used for setting coating area information and judging standards of defects such as scraping defects, scratch defects, dry material defects and bubble defects, and particularly, operators can set the positions of the coating areas through the parameter management module and set all defect standards of scraping, scratching, dry material defects and bubble defect judging shutdown;
The log management module stores defect information, system abnormal information and other key information according to the day;
And the data storage module stores defect specific information (including time, defect type, defect coordinate information, defect size and whether to stop or not) according to the day.
In other embodiments, the application also provides an automatic defect detection method of the oil coating, and the system detection algorithm comprises a parameter setting unit, an image acquisition unit, a detection unit and a data storage unit.
The parameter setting unit obtains the defect result required by production by setting different defect sizes and different judging standards, and the on-site problem is timely processed through the defect result.
The image acquisition unit acquires the oily coating image in real time through a high-precision industrial line scanning camera, and provides an original image for subsequent system detection.
The detection unit detects and analyzes the collected original image through a computer vision image processing technology and a deep learning technology, and firstly judges whether the image has defects or not, and judges which type the defects belong to under the defect condition.
The data storage unit stores information (time, result graph, defect information (position, defect size, defect category)) detected as defects to the local through a system storage function for staff to inquire.
According to a third aspect of the embodiment of the present application, an electronic device 700 is provided, which may be any type of intelligent terminal, such as a mobile phone, a tablet computer, a personal computer, etc.
As shown in fig. 3, the electronic device 800 includes: one or more processors 801 and memory 802, one processor 801 being illustrated in fig. 3.
The processor 801 and the memory 802 may be communicatively coupled via a bus or other means, as illustrated in fig. 3.
The memory 802, as a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and units, such as program instructions/units corresponding to the electronic device 800 in embodiments of the present application. The processor 801 executes various functional applications and data processing by running non-transitory software programs, instructions, and units stored in the memory 802, that is, implements the oil coating detection method of the above-described method embodiment.
Memory 802 may include a storage program area that may store an operating system, at least one application program required for functionality, and a storage data area; the storage data area may store data created according to program instructions/units, etc. In addition, memory 802 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 802 may optionally include memory located remotely from processor 801, which may be connected to the electronic device 800 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.
One or more units are stored in memory 802 that, when executed by one or more processors 801, perform the oil coating detection method of any of the method embodiments described above. For example, the above-described method steps S100 to S700 in fig. 1 are performed.
In a third aspect of the embodiment of the present application, there is also provided a computer-readable storage medium storing computer-executable instructions that are executed by one or more processors 801, for example, by one of the processors 801 in fig. 3, which may cause the one or more processors 801 to perform the oil coating detection method in the method embodiment described above, for example, to perform the method steps S100 to S700 in fig. 1 described above.
The apparatus embodiments described above are merely illustrative, wherein elements illustrated as separate elements may or may not be physically separate, and elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
From the above description of embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus a general purpose hardware platform, or may be implemented by hardware. Those skilled in the art will appreciate that all or part of the processes implementing the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, and the program may be stored in a computer readable storage medium, and the program may include processes of the embodiments of the methods described above when executed. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random-access Memory (Random Access Memory, RAM), or the like.
In the description of the present specification, reference to the terms "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and alterations may be made to these embodiments without departing from the spirit and principles of the present application, and it is intended that the application be included within the scope of the application.
Claims (8)
1. An oil coating detection method, characterized by comprising:
Collecting an initial image;
preprocessing the initial image to obtain a coating region to be detected;
Obtaining a plurality of first connected domain information and a plurality of second connected domain information according to the coating region to be detected;
Obtaining a scratching characteristic value according to the ratio of the widths of the two adjacent first connected domain information, wherein the scratching characteristic value is obtained according to the ratio of the widths of the two adjacent first connected domain information, and comprises the following steps: transversely dividing and cutting each piece of first connected domain information equally to obtain a plurality of first equal-divided regions; respectively obtaining the width ratio of two corresponding first equal-dividing areas of two adjacent first connected domain information in each transverse equal-dividing section to obtain a plurality of width ratio values; taking a plurality of width ratios as the scratching characteristic values;
If the scratching characteristic value is less than or equal to the scratching threshold value, judging that the scratching defect exists, wherein, and if the scratching characteristic value is smaller than or equal to the scratching threshold value, judging that the scratching defect is generated, wherein the scratching defect comprises the following steps: comparing each of the width ratios with the scratch threshold value respectively; if each width ratio is smaller than or equal to the scratching threshold value, judging that the scratching defect exists;
Obtaining a scratch characteristic value according to the width and the height of the same second connected domain information;
If the scratch characteristic value is greater than the scratch threshold, determining that the scratch is defective, wherein the scratch threshold comprises a ratio threshold, a threshold width value and a threshold height value, and if the scratch characteristic value is greater than the scratch threshold, determining that the scratch is defective, comprising: comparing the high value of the scratch characteristic value with the threshold high value to obtain a first ratio; comparing the width of the scratch characteristic value with the threshold width value to obtain a second ratio; comparing the ratio of the height to the width of the scratch characteristic value with the ratio threshold to obtain a third ratio; and if the first ratio, the second ratio and the third ratio are not in the corresponding threshold values, judging that the scratch defect exists.
2. The method for detecting an oil coating according to claim 1, wherein the preprocessing the initial image to obtain a coating region to be detected comprises:
sequentially carrying out binarization and connected domain processing on the initial image to obtain a processed image;
acquiring a coating width corresponding to the initial image;
And extracting the coating region to be detected from the processed image according to the coating width.
3. The method for detecting an oil coating according to claim 1, wherein the obtaining a plurality of first connected domain information and a plurality of second connected domain information according to the coating region to be detected includes:
dividing the coating region to be detected according to a first fixed threshold value to obtain a first binary image;
Performing corrosion expansion treatment on the first binary image to obtain a first corrosion expansion diagram;
And carrying out connected domain processing on the first corrosion expansion map to obtain a plurality of pieces of first connected domain information.
4. The method for detecting an oil coating according to claim 3, wherein the obtaining the first connected domain information and the second connected domain information according to the coating region to be detected further comprises:
dividing the coating region to be detected according to a second fixed threshold value to obtain a second binary image;
performing corrosion expansion treatment on the second binary image to obtain a second corrosion expansion diagram;
And carrying out connected domain processing on the second corrosion expansion map to obtain a plurality of pieces of second connected domain information.
5. The method for detecting an oil coating according to claim 1, further comprising, after the initial image is acquired:
Loading a deep learning model;
Acquiring image size information, a first execution degree and a second execution degree;
and inputting the image size information, the first execution degree and the second execution degree into the deep learning model to obtain dry material defect information and bubble defect information.
6. An oil coating detection system, comprising:
the camera streaming module is used for acquiring an initial image;
the algorithm processing module is used for detecting scratch defects, dry material defects and bubble defects of the coating;
The algorithm processing module is also used for preprocessing the initial image to obtain a coating area to be detected; obtaining a plurality of first connected domain information and a plurality of second connected domain information according to the coating region to be detected; obtaining a scratching characteristic value according to the ratio of the widths of the two adjacent first connected domain information, wherein the scratching characteristic value is obtained according to the ratio of the widths of the two adjacent first connected domain information, and comprises the following steps: transversely dividing and cutting each piece of first connected domain information equally to obtain a plurality of first equal-divided regions; respectively obtaining the width ratio of two corresponding first equal-dividing areas of two adjacent first connected domain information in each transverse equal-dividing section to obtain a plurality of width ratio values; taking a plurality of width ratios as the scratching characteristic values; and if the scratching characteristic value is smaller than or equal to the scratching threshold value, judging that the scratching defect is generated, wherein if the scratching characteristic value is smaller than or equal to the scratching threshold value, judging that the scratching defect is generated, and the method comprises the following steps: comparing each of the width ratios with the scratch threshold value respectively; if each width ratio is smaller than or equal to the scratching threshold value, judging that the scratching defect exists; obtaining a scratch characteristic value according to the width and the height of the same second connected domain information; if the scratch characteristic value is greater than the scratch threshold, determining that the scratch is defective, wherein the scratch threshold comprises a ratio threshold, a threshold width value and a threshold height value, and if the scratch characteristic value is greater than the scratch threshold, determining that the scratch is defective, comprising: comparing the high value of the scratch characteristic value with the threshold high value to obtain a first ratio; comparing the width of the scratch characteristic value with the threshold width value to obtain a second ratio; comparing the ratio of the height to the width of the scratch characteristic value with the ratio threshold to obtain a third ratio; if the first ratio, the second ratio and the third ratio are not in the corresponding threshold values, judging that the scratch defect exists;
The communication management module is used for controlling the algorithm processing module to detect different defects and stop the system;
And the parameter management module is used for setting judging standards of defects such as coating area information, scratch defects, dry material defects and bubble defects.
7. An electronic device, comprising:
At least one processor, and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores instructions that are executed by the at least one processor to cause the at least one processor to implement the oil coating detection method of any one of claims 1 to 5 when the instructions are executed.
8. A computer-readable storage medium storing computer-executable instructions for causing a computer to perform the oil coating detection method according to any one of claims 1 to 5.
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