CN113325001A - Automatic distinguishing and detecting equipment and method for surface appearance flaws of copper foil - Google Patents
Automatic distinguishing and detecting equipment and method for surface appearance flaws of copper foil Download PDFInfo
- Publication number
- CN113325001A CN113325001A CN202110390208.9A CN202110390208A CN113325001A CN 113325001 A CN113325001 A CN 113325001A CN 202110390208 A CN202110390208 A CN 202110390208A CN 113325001 A CN113325001 A CN 113325001A
- Authority
- CN
- China
- Prior art keywords
- copper foil
- image
- grade
- detected
- value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 title claims abstract description 112
- 239000011889 copper foil Substances 0.000 title claims abstract description 109
- 238000000034 method Methods 0.000 title claims abstract description 21
- 230000007547 defect Effects 0.000 claims abstract description 50
- 238000001514 detection method Methods 0.000 claims abstract description 47
- 238000012545 processing Methods 0.000 claims abstract description 20
- 239000000126 substance Substances 0.000 claims abstract description 14
- 230000000007 visual effect Effects 0.000 claims abstract description 9
- 238000012937 correction Methods 0.000 claims description 6
- 238000011179 visual inspection Methods 0.000 claims description 6
- 238000007689 inspection Methods 0.000 claims description 5
- 238000005520 cutting process Methods 0.000 claims description 4
- 238000013461 design Methods 0.000 claims description 3
- 238000003708 edge detection Methods 0.000 claims description 3
- 238000009432 framing Methods 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims description 3
- 230000005855 radiation Effects 0.000 claims description 3
- 238000012360 testing method Methods 0.000 claims 1
- 238000004519 manufacturing process Methods 0.000 abstract description 8
- 229910052802 copper Inorganic materials 0.000 description 3
- 239000010949 copper Substances 0.000 description 3
- 238000007373 indentation Methods 0.000 description 3
- 230000007774 longterm Effects 0.000 description 3
- 239000000758 substrate Substances 0.000 description 3
- 230000000694 effects Effects 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 229910001416 lithium ion Inorganic materials 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8854—Grading and classifying of flaws
Abstract
The invention belongs to the technical field of copper foil surface detection, and particularly relates to automatic distinguishing and detecting equipment and a detecting method for surface appearance flaws of a copper foil, wherein the automatic distinguishing and detecting equipment is erected between a copper foil processing end and a slitting end, comprises a CCD linear array camera which is erected above and below a copper foil production line and is used for synchronously scanning the front side and the back side of the copper foil in real time, a visual detection image processing system which is used for analyzing and judging the surface image characteristics of the copper foil, a light source generating device and a grading and judging module which is used for grading according to the flaw size of the copper foil, the number of the flaws in a specified unit length and the defect density degree, and the visual detection image processing system is used for identifying whether the top surface and the bottom surface of the copper foil have the phenomena of pinholes, spots, chemical marks and craters. The automatic distinguishing and detecting equipment and the detecting method for the surface appearance flaws of the copper foil disclosed by the invention are simple to operate, so that the damage of the appearance of the copper foil detected by eyes for a long time to a human body is reduced, and the accuracy and the stability of the appearance quality detection of the copper foil are improved.
Description
Technical Field
The invention relates to automatic distinguishing and detecting equipment and method for surface appearance flaws of a copper foil. Belongs to the technical field of copper foil surface detection.
Background
The copper foil is an important material for manufacturing copper clad laminates, printed circuit boards and lithium ion batteries. With the rapid development of the electronic information industry, the demand of copper foil is increasing, especially high-quality copper foil, therefore, the quality of copper foil is important to improve, especially the appearance quality seriously affects the service life and performance of related products.
At present, most of the detection of the appearance defects of the copper foil at home and abroad depends on manual detection, and the copper foil has large area, more defect types and less obvious characteristics, so the detection result lacks objectivity, has low efficiency and has high labor intensity; and the traditional machine vision technology is difficult to meet the requirements due to the complexity of copper foil defects and small difference between the defects.
The fast and accurate detection of the defects of the copper foil substrate is an important research content in industrial production. In the production and manufacturing process of the copper foil substrate, appearance defects are difficult to avoid, which causes great negative effects on the performance and quality of the copper foil substrate, and in order to avoid the effects caused by the defects, the existing management and control needs to manually add strips or marks on the copper foil, and calculate whether the roll of copper foil is degraded or not after the roll is rolled down. There are many human factors that cause defect management not to be strictly performed. The detection method has the limitations and the execution process is time-consuming and labor-consuming, and the precision and the speed are difficult to meet the requirements.
Disclosure of Invention
The invention provides the automatic distinguishing detection equipment and the detection method for the surface appearance flaws of the copper foil, which are simple to operate, reduce the damage of the appearance of the copper foil to a human body by long-term eye detection, and improve the accuracy and stability of the appearance quality detection of the copper foil, so that the problems in the prior art are solved.
In order to solve the technical problems, the technical scheme of the invention is as follows:
the automatic distinguishing and detecting equipment for the surface appearance defects of the copper foil is erected between a copper foil processing end and a slitting end and comprises a CCD (charge coupled device) linear array camera which is erected above and below a copper foil production line and is used for synchronously scanning the front side and the back side of the copper foil in real time, a visual detection image processing system which is used for analyzing and judging the surface image characteristics of the copper foil, a light source generating device which is matched with the CCD linear array camera and a grading module which is used for grading according to the defect size of the copper foil, the number of the defects of the copper foil with specified unit length and the defect density, wherein the visual detection image processing system is used for identifying whether the top surface and the bottom surface of the copper foil have the phenomena of pinholes, spots, chemical marks and craters or the like, and the grading module is used for giving a copper foil grading result according to the defect size, the number of the defects per kilometer and the defect density.
A detection method of automatic distinguishing detection equipment for surface appearance flaws of a copper foil comprises the following steps:
the method comprises the following steps: carrying out surface detection on the processed copper foil through a CCD linear array camera and a visual detection image processing system; detecting whether surface defects including pinholes, spots, chemical marks and pressure pits exist on the surface; if the surface defects exceeding the set control standard value are detected, carrying out marking grade processing on the copper foil with the specified unit length through a grading judging module, wherein the marking grade comprises a first grade, a second grade and a third grade;
step two: recording the specified unit length of copper foil continuously having surface defects exceeding a set control standard value as N; if the numerical value of N is larger than a preset value stored in the surface detection system; the alarm device is started; wherein the surface detection comprises upper and lower surface detection of the copper foil;
step three: and cutting the copper foil with qualified surface detection.
Preferably, the method for identifying whether pinholes, spots, chemical marks and craters exist on the top surface and the bottom surface of the copper foil by the visual inspection image processing system comprises the following steps:
s1: numbering the obtained copper foil top surface image and the obtained copper foil bottom surface image to form a first image to be detected and a second image to be detected;
s2: extracting a first image to be detected, and preprocessing the image, including geometric correction, radiation correction and denoising; denoising refers to correcting unclear images in a shot image.
S3: determining the boundary contour of the copper foil in the first image to be detected through Canny operator edge detection, and extracting an image in the boundary contour;
s4: converting the image acquired in step S3 into a first to-be-detected grayscale image;
s5: acquiring a reference point pixel gray value of the first to-be-detected gray image in the step S4, and radiating outwards in a circumferential manner by taking the central point as a circle center; comparing the difference value between the gray value of the pixel of the adjacent point and the gray value of the central point to obtain a difference value T1; and recording the comparison quantity as S1; if T1 is less than or equal to 20; recording the gray value of the adjacent point; if T1 is more than 20, discarding the gray value of the adjacent point; and so on, when the value of S1 is greater than 50% of the image pixel points, the recorded gray values of all the adjacent points are averaged to obtain a standard gray value; forming a standard gray image, wherein the gray value of each pixel point of the standard gray image is a standard gray value, and the pixel of the standard gray image is the same as the first to-be-detected gray image; if the quantity of the S1 is not 50% of the image pixel point, it indicates that the selected reference point pixel is possibly a pinhole or a spot or a chemical mark or a pit; then, searching the reference point again, and based on the reference point, until obtaining the standard gray value;
s6: performing AND operation on the standard gray image and the first to-be-detected gray image to obtain pixel points which are different from the standard gray image in the first to-be-detected gray image, and framing the positions of the different pixel points to make marks; the positions of the pixels are selected and distinguished in a square frame, so that the detection content can be conveniently collected in the later period.
S7: judging whether the difference value T2 between the gray value of the distinguishing pixel point and the standard gray value is larger than 80, if T2 is larger than 80, the position of the distinguishing pixel point is a pinhole;
s8: if the value is more than or equal to 80 and more than or equal to T2 and more than 30, distinguishing the position of the pixel point as a pit;
s9: if T2 is less than or equal to 30, judging the shape of the position of the distinguishing pixel point, and if the shape of the position of the distinguishing pixel point is linearly arranged, judging the distinguishing pixel point is a mark; if the shape of the position of the distinguishing pixel point is arranged in a different shape, the distinguishing pixel point is judged to be a spot;
s10: and extracting a second image to be detected, and judging whether pinholes, spots, chemical marks and pits exist on the bottom surface of the copper foil according to the steps S1-S9.
The unit length copper foil specified in the step one is specified according to design requirements, the unit length copper foil can be 500m or 1000 m, one grade in the marking grade is an excellent grade, the second grade in the marking grade is a qualified grade, and the third grade in the marking grade is an unqualified grade.
The invention relates to an automatic distinguishing and detecting device and a detecting method for surface appearance flaws of copper foil, which select the required defect types, automatically calculate the number and the density of each kilometer, and give out a grading result, and once a parking prompt is given out after exceeding the standard, the next step is carried out after the parking prompt is confirmed to be received. The advantages are that: the work load of personnel is reduced, the probability of personnel making mistakes is reduced, the efficiency can be increased, the influence of human factors is reduced, real-time synchronous scanning is carried out through a CCD linear array camera erected on a production line, CCD transmits acquired image data to visual inspection image processing software, the surface image characteristics of the copper foil are analyzed and judged through the software, and therefore the defects of various pinholes, spots, residual copper, indentation and the like are detected, classified and processed in real time, the damage of the appearance of the copper foil to a human body through long-term eye inspection is reduced, and the accuracy and the stability of the appearance quality detection of the copper foil are improved.
The control standard of the detected copper foil defects can be roughly as follows: the size, the number per kilometer, the density and the like are classified, the number of allowed flaws in the copper foil with the specified unit length is specified, and the flaws are classified into three grades, for example, 1-5 flaws of 1 kilometer are excellent grades, 5-10 flaws of 1 kilometer are qualified grades, and more than 10 flaws of 1 kilometer are unqualified grades. The allowable flaw density in the copper foil with the specified unit length is specified and divided into two grades, wherein the qualified grade is that less than 2 flaws appear every 100 meters in 1 kilometer, and the unqualified grade is that more than 2 flaws appear every 100 meters in 1 kilometer.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a detection diagram of the automatic distinguishing detection device and the detection method for the surface appearance defects of the copper foil.
Detailed Description
The following further describes embodiments of the present invention with reference to the drawings. It should be noted that the description of the embodiments is provided to help understanding of the present invention, but the present invention is not limited thereto. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The automatic distinguishing and detecting equipment for the surface appearance defects of the copper foil is erected between a copper foil processing end and a slitting end and comprises a CCD (charge coupled device) linear array camera which is erected above and below a copper foil production line and is used for synchronously scanning the front side and the back side of the copper foil in real time, a visual detection image processing system which is used for analyzing and judging the surface image characteristics of the copper foil, a light source generating device which is matched with the CCD linear array camera and a grading module which is used for grading according to the defect size of the copper foil, the number of the defects of the copper foil with specified unit length and the defect density, wherein the visual detection image processing system is used for identifying whether the top surface and the bottom surface of the copper foil have the phenomena of pinholes, spots, chemical marks and craters or the like, and the grading module is used for giving a copper foil grading result according to the defect size, the number of the defects per kilometer and the defect density.
A detection method of automatic distinguishing detection equipment for surface appearance flaws of a copper foil comprises the following steps:
the method comprises the following steps: carrying out surface detection on the processed copper foil through a CCD linear array camera and a visual detection image processing system; detecting whether surface defects including pinholes, spots, chemical marks and pressure pits exist on the surface; if the surface defects exceeding the set control standard value are detected, carrying out marking grade processing on the copper foil with the specified unit length through a grading judging module, wherein the marking grade comprises a first grade, a second grade and a third grade;
the control standard of the detected copper foil defects can be classified by size, number per kilometer, density and the like, the number of defects allowed to appear in the copper foil with a specified unit length is specified, and the defects are classified into three grades, for example, 1-5 defects of 1 kilometer are excellent grades, 5-10 defects of 1 kilometer are qualified grades, and more than 10 defects of 1 kilometer are unqualified grades. The allowable flaw density in the copper foil with the specified unit length is specified and divided into two grades, wherein the qualified grade is that less than 2 flaws appear every 100 meters in 1 kilometer, and the unqualified grade is that more than 2 flaws appear every 100 meters in 1 kilometer.
Step two: recording the specified unit length of copper foil continuously having surface defects exceeding a set control standard value as N; if the numerical value of N is larger than a preset value stored in the surface detection system; the alarm device is started; wherein the surface detection comprises upper and lower surface detection of the copper foil;
step three: and cutting the copper foil with qualified surface detection.
Preferably, the method for identifying whether pinholes, spots, chemical marks and craters exist on the top surface and the bottom surface of the copper foil by the visual inspection image processing system comprises the following steps:
s1: numbering the obtained copper foil top surface image and the obtained copper foil bottom surface image to form a first image to be detected and a second image to be detected;
s2: extracting a first image to be detected, and preprocessing the image, including geometric correction, radiation correction and denoising; denoising refers to correcting unclear images in a shot image.
S3: determining the boundary contour of the copper foil in the first image to be detected through Canny operator edge detection, and extracting an image in the boundary contour;
s4: converting the image acquired in step S3 into a first to-be-detected grayscale image;
referring to fig. 1, S5: acquiring a reference point pixel gray value of the first to-be-detected gray image in the step S4, and radiating outwards in a circumferential manner by taking the central point as a circle center; comparing the difference value between the gray value of the pixel of the adjacent point and the gray value of the central point to obtain a difference value T1; and recording the comparison quantity as S1; if T1 is less than or equal to 20; recording the gray value of the adjacent point; if T1 is more than 20, discarding the gray value of the adjacent point; and so on, when the value of S1 is greater than 50% of the image pixel points, the recorded gray values of all the adjacent points are averaged to obtain a standard gray value; forming a standard gray image, wherein the gray value of each pixel point of the standard gray image is a standard gray value, and the pixel of the standard gray image is the same as the first to-be-detected gray image; if the quantity of the S1 is not 50% of the image pixel point, it indicates that the selected reference point pixel is possibly a crack or a position of a gap; then, searching the reference point again, and based on the reference point, until obtaining the standard gray value;
when the reference point pixel is obtained for the first time, preferably selecting the position of the central point of the first to-be-detected gray level image;
s6: performing AND operation on the standard gray image and the first to-be-detected gray image to obtain pixel points which are different from the standard gray image in the first to-be-detected gray image, and framing the positions of the different pixel points to make marks; the positions of the pixels are selected and distinguished in a square frame, so that the detection content can be conveniently collected in the later period.
S7: judging whether the difference value T2 between the gray value of the distinguishing pixel point and the standard gray value is larger than 80, if T2 is larger than 80, the position of the distinguishing pixel point is a pinhole;
according to a large amount of experimental data, if the position of the distinguishing pixel point is a pinhole, a brightness exposure state occurs at the position, and the gray value of the pinhole position and the standard gray value are definitely greater than 80.
S8: if the value is more than or equal to 80 and more than or equal to T2 and more than 30, distinguishing the position of the pixel point as a pit; according to a large amount of experimental data, if the position of the distinguishing pixel point is the indentation, an obvious black state can appear at the position.
S9: if T2 is less than or equal to 30, judging the shape of the position of the distinguishing pixel point, and if the shape of the position of the distinguishing pixel point is linearly arranged, judging the distinguishing pixel point is a mark; if the shape of the position of the distinguishing pixel point is arranged in a different shape, the distinguishing pixel point is judged to be a spot;
s10: and extracting a second image to be detected, and judging whether pinholes, spots, chemical marks and pits exist on the bottom surface of the copper foil according to the steps S1-S9.
The unit length copper foil specified in the step one is specified according to design requirements, the unit length copper foil can be 500m or 1000 m, one grade in the marking grade is an excellent grade, the second grade in the marking grade is a qualified grade, and the third grade in the marking grade is an unqualified grade.
The invention relates to an automatic distinguishing and detecting device and a detecting method for surface appearance flaws of copper foil, which select the required defect types, automatically calculate the number and the density of each kilometer, and give out a grading result, and once a parking prompt is given out after exceeding the standard, the next step is carried out after the parking prompt is confirmed to be received. The advantages are that: the work load of personnel is reduced, the probability of personnel making mistakes is reduced, the efficiency can be increased, the influence of human factors is reduced, real-time synchronous scanning is carried out through a CCD linear array camera erected on a production line, CCD transmits acquired image data to visual inspection image processing software, the surface image characteristics of the copper foil are analyzed and judged through the software, and therefore the defects of various pinholes, spots, residual copper, indentation and the like are detected, classified and processed in real time, the damage of the appearance of the copper foil to a human body through long-term eye inspection is reduced, and the accuracy and the stability of the appearance quality detection of the copper foil are improved.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. It will be apparent to those skilled in the art that various changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, and the scope of protection is still within the scope of the invention.
Claims (4)
1. The utility model provides a copper foil surface appearance flaw automatic discrimination check out test set erects between copper foil processing end and the end of cutting, its characterized in that: the visual inspection image processing system identifies whether pinholes, spots, chemical marks and craters exist on the top surface and the bottom surface of the copper foil, and the grading judging module gives a copper foil grade result according to the size of the copper foil defects, the number of defects per kilometer and the defect concentration degree.
2. The inspection method of the inspection apparatus for automatically distinguishing the surface appearance defects of the copper foil according to claim 1, wherein the inspection method comprises the following steps: the method comprises the following steps:
the method comprises the following steps: carrying out surface detection on the processed copper foil through a CCD linear array camera and a visual detection image processing system; detecting whether surface defects including pinholes, spots, chemical marks and pressure pits exist on the surface; if the surface defects exceeding the set control standard value are detected, carrying out marking grade processing on the copper foil with the specified unit length through a grading judging module, wherein the marking grade comprises a first grade, a second grade and a third grade;
step two: recording the specified unit length of copper foil continuously having surface defects exceeding a set control standard value as N; if the numerical value of N is larger than a preset value stored in the surface detection system; the alarm device is started; wherein the surface detection comprises upper and lower surface detection of the copper foil;
step three: and cutting the copper foil with qualified surface detection.
3. The method for automatically distinguishing the surface appearance defects of the copper foil according to claim 2, wherein the method comprises the following steps: the method for identifying whether pinholes, spots, chemical marks and craters exist on the top surface and the bottom surface of the copper foil by the visual inspection image processing system comprises the following steps:
s1: numbering the obtained copper foil top surface image and the obtained copper foil bottom surface image to form a first image to be detected and a second image to be detected;
s2: extracting a first image to be detected, and preprocessing the image, including geometric correction, radiation correction and denoising;
s3: determining the boundary contour of the copper foil in the first image to be detected through Canny operator edge detection, and extracting an image in the boundary contour;
s4: converting the image acquired in step S3 into a first to-be-detected grayscale image;
s5: acquiring a reference point pixel gray value of the first to-be-detected gray image in the step S4, and radiating outwards in a circumferential manner by taking the central point as a circle center; comparing the difference value between the gray value of the pixel of the adjacent point and the gray value of the central point to obtain a difference value T1; and recording the comparison quantity as S1; if T1 is less than or equal to 20; recording the gray value of the adjacent point; if T1 is more than 20, discarding the gray value of the adjacent point; and so on, when the value of S1 is greater than 50% of the image pixel points, the recorded gray values of all the adjacent points are averaged to obtain a standard gray value; forming a standard gray image, wherein the gray value of each pixel point of the standard gray image is a standard gray value, and the pixel of the standard gray image is the same as the first to-be-detected gray image; if the quantity of S1 can not reach 50% of the image pixel points, re-searching the reference points, and obtaining the standard gray value based on the reference points;
s6: performing AND operation on the standard gray image and the first to-be-detected gray image to obtain pixel points which are different from the standard gray image in the first to-be-detected gray image, and framing the positions of the different pixel points to make marks;
s7: judging whether the difference value T2 between the gray value of the distinguishing pixel point and the standard gray value is larger than 80, if T2 is larger than 80, the position of the distinguishing pixel point is a pinhole;
s8: if the value is more than or equal to 80 and more than or equal to T2 and more than 30, distinguishing the position of the pixel point as a pit;
s9: if T2 is less than or equal to 30, judging the shape of the position of the distinguishing pixel point, and if the shape of the position of the distinguishing pixel point is linearly arranged, judging the distinguishing pixel point is a mark; if the shape of the position of the distinguishing pixel point is arranged in a different shape, the distinguishing pixel point is judged to be a spot;
s10: and extracting a second image to be detected, and judging whether pinholes, spots, chemical marks and pits exist on the bottom surface of the copper foil according to the steps S1-S9.
4. The method for automatically distinguishing the surface appearance defects of the copper foil according to claim 2, wherein the method comprises the following steps: the unit length copper foil specified in the step one is specified according to design requirements, the unit length copper foil can be 500m or 1000 m, one grade in the marking grade is an excellent grade, the second grade in the marking grade is a qualified grade, and the third grade in the marking grade is an unqualified grade.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110390208.9A CN113325001A (en) | 2021-04-12 | 2021-04-12 | Automatic distinguishing and detecting equipment and method for surface appearance flaws of copper foil |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110390208.9A CN113325001A (en) | 2021-04-12 | 2021-04-12 | Automatic distinguishing and detecting equipment and method for surface appearance flaws of copper foil |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113325001A true CN113325001A (en) | 2021-08-31 |
Family
ID=77414708
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110390208.9A Pending CN113325001A (en) | 2021-04-12 | 2021-04-12 | Automatic distinguishing and detecting equipment and method for surface appearance flaws of copper foil |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113325001A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114147421A (en) * | 2021-10-13 | 2022-03-08 | 浙江南龙工贸有限公司 | Preparation method of anti-overflow multi-layer micro-pressure cooker capable of being stewed in classified time-sharing manner |
| CN114529510A (en) * | 2022-01-11 | 2022-05-24 | 三门三友科技股份有限公司 | Cathode copper online quality automatic detection and classification method |
| CN115049644A (en) * | 2022-08-12 | 2022-09-13 | 山东三微新材料有限公司 | Temperature control method and system based on aluminum pipe surface flaw identification |
| CN116148268A (en) * | 2023-04-21 | 2023-05-23 | 创新奇智(青岛)科技有限公司 | Method, device, electronic equipment and computer readable storage medium for flaw detection |
| CN116500086A (en) * | 2023-06-28 | 2023-07-28 | 深圳市鑫典金光电科技有限公司 | Deep learning-based copper complex aluminum heat dissipation bottom plate production evaluation method and system |
| WO2024011674A1 (en) * | 2022-07-14 | 2024-01-18 | 淮南师范学院 | Multifunctional automatic inspection platform based on machine vision technology |
| CN117607164A (en) * | 2024-01-22 | 2024-02-27 | 钛玛科（北京）工业科技有限公司 | Copper foil defect detection method and device based on time-sharing polishing and virtual stations |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012229928A (en) * | 2011-04-25 | 2012-11-22 | Jfe Steel Corp | Surface flaw detection method and surface flaw detection device |
| CN107300559A (en) * | 2017-08-25 | 2017-10-27 | 山东众鑫电子材料有限公司 | A kind of Kapton defect detection system and method |
| CN107389701A (en) * | 2017-08-22 | 2017-11-24 | 西北工业大学 | A kind of PCB visual defects automatic checkout system and method based on image |
| CN111612737A (en) * | 2020-04-15 | 2020-09-01 | 枞阳立太智能装备有限公司 | Artificial board surface flaw detection device and detection method |
| CN112415013A (en) * | 2020-11-09 | 2021-02-26 | 上海圣之尧智能科技有限公司 | Copper foil defect detection system |
-
2021
- 2021-04-12 CN CN202110390208.9A patent/CN113325001A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012229928A (en) * | 2011-04-25 | 2012-11-22 | Jfe Steel Corp | Surface flaw detection method and surface flaw detection device |
| CN107389701A (en) * | 2017-08-22 | 2017-11-24 | 西北工业大学 | A kind of PCB visual defects automatic checkout system and method based on image |
| CN107300559A (en) * | 2017-08-25 | 2017-10-27 | 山东众鑫电子材料有限公司 | A kind of Kapton defect detection system and method |
| CN111612737A (en) * | 2020-04-15 | 2020-09-01 | 枞阳立太智能装备有限公司 | Artificial board surface flaw detection device and detection method |
| CN112415013A (en) * | 2020-11-09 | 2021-02-26 | 上海圣之尧智能科技有限公司 | Copper foil defect detection system |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114147421A (en) * | 2021-10-13 | 2022-03-08 | 浙江南龙工贸有限公司 | Preparation method of anti-overflow multi-layer micro-pressure cooker capable of being stewed in classified time-sharing manner |
| CN114529510A (en) * | 2022-01-11 | 2022-05-24 | 三门三友科技股份有限公司 | Cathode copper online quality automatic detection and classification method |
| WO2024011674A1 (en) * | 2022-07-14 | 2024-01-18 | 淮南师范学院 | Multifunctional automatic inspection platform based on machine vision technology |
| CN115049644A (en) * | 2022-08-12 | 2022-09-13 | 山东三微新材料有限公司 | Temperature control method and system based on aluminum pipe surface flaw identification |
| CN115049644B (en) * | 2022-08-12 | 2022-11-01 | 山东三微新材料有限公司 | Temperature control method and system based on aluminum pipe surface flaw identification |
| CN116148268A (en) * | 2023-04-21 | 2023-05-23 | 创新奇智(青岛)科技有限公司 | Method, device, electronic equipment and computer readable storage medium for flaw detection |
| CN116500086A (en) * | 2023-06-28 | 2023-07-28 | 深圳市鑫典金光电科技有限公司 | Deep learning-based copper complex aluminum heat dissipation bottom plate production evaluation method and system |
| CN116500086B (en) * | 2023-06-28 | 2023-09-05 | 深圳市鑫典金光电科技有限公司 | Deep learning-based copper complex aluminum heat dissipation bottom plate production evaluation method and system |
| CN117607164A (en) * | 2024-01-22 | 2024-02-27 | 钛玛科（北京）工业科技有限公司 | Copper foil defect detection method and device based on time-sharing polishing and virtual stations |
| CN117607164B (en) * | 2024-01-22 | 2024-04-16 | 钛玛科（北京）工业科技有限公司 | Copper foil defect detection method and device based on time-sharing polishing and virtual stations |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113325001A (en) | Automatic distinguishing and detecting equipment and method for surface appearance flaws of copper foil | |
| CN109141232B (en) | Online detection method for disc castings based on machine vision | |
| CN102175700B (en) | Method for detecting welding seam segmentation and defects of digital X-ray images | |
| CN1869667B (en) | Profile analyzing method for investigating defect of printed circuit board | |
| CN109900711A (en) | Workpiece, defect detection method based on machine vision | |
| CN109752392B (en) | PCB defect type detection system and method | |
| CN112053318A (en) | Two-dimensional PCB defect real-time automatic detection and classification device based on deep learning | |
| CN109785294A (en) | A kind of pcb board defective locations detection system and method | |
| CN112819844B (en) | Image edge detection method and device | |
| CN115601359A (en) | Welding seam detection method and device | |
| CN110426395B (en) | Method and device for detecting surface of solar EL battery silicon wafer | |
| CN116539620A (en) | On-machine detection method for surface defects of cutter | |
| CN115601369A (en) | Quality evaluation method for power transformation equipment support for power transmission and transformation engineering | |
| CN111353986A (en) | Die-cutting product quality detection method | |
| CN113781458A (en) | Artificial intelligence based identification method | |
| CN113962929A (en) | Photovoltaic cell assembly defect detection method and system and photovoltaic cell assembly production line | |
| CN112837287B (en) | Method and device for extracting defect area of board surface | |
| CN107797517B (en) | Method and system for realizing steel belt punching processing detection by adopting machine vision | |
| CN114820439A (en) | PCB bare board defect detection system and method based on AOI | |
| CN111598851B (en) | Solar cell broken piece detection method based on morphological image processing | |
| CN102735689A (en) | Paper defect detection system based on image pattern recognition | |
| CN113808104A (en) | Block-based metal surface defect detection method and system | |
| CN112183593A (en) | Road damage detection method based on DSSD algorithm | |
| CN114943704A (en) | Method, device and equipment for detecting defects of battery electrode die-cut piece | |
| CN116091506A (en) | Machine vision defect quality inspection method based on YOLOV5 |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information |
Address after: 322121 Huayuan village, Nanma Town, Dongyang City, Jinhua City, Zhejiang Province Applicant after: Zhejiang Huayuan new energy Co.,Ltd. Address before: 322100 Huayuan village, Nanma Town, Dongyang City, Jinhua City, Zhejiang Province Applicant before: ZHEJIANG HUAYUAN NEW ENERGY Co.,Ltd. |
|
| CB02 | Change of applicant information |