CN116907360A - RO (reverse osmosis) membrane gel line width detection system and detection method based on machine vision - Google Patents
RO (reverse osmosis) membrane gel line width detection system and detection method based on machine vision Download PDFInfo
- Publication number
- CN116907360A CN116907360A CN202310973564.2A CN202310973564A CN116907360A CN 116907360 A CN116907360 A CN 116907360A CN 202310973564 A CN202310973564 A CN 202310973564A CN 116907360 A CN116907360 A CN 116907360A
- Authority
- CN
- China
- Prior art keywords
- membrane
- line
- glue
- width
- glue line
- 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.)
- Granted
Links
- 239000012528 membrane Substances 0.000 title claims abstract description 100
- 238000001514 detection method Methods 0.000 title claims abstract description 58
- 238000001223 reverse osmosis Methods 0.000 title description 69
- 239000003292 glue Substances 0.000 claims abstract description 104
- 238000005259 measurement Methods 0.000 claims abstract description 21
- 238000000034 method Methods 0.000 claims abstract description 19
- 238000004026 adhesive bonding Methods 0.000 claims abstract description 9
- 238000012545 processing Methods 0.000 claims description 7
- 239000000284 extract Substances 0.000 claims description 4
- 238000007781 pre-processing Methods 0.000 claims description 4
- 238000009826 distribution Methods 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 238000003708 edge detection Methods 0.000 claims description 2
- 230000003287 optical effect Effects 0.000 claims description 2
- 238000010009 beating Methods 0.000 claims 1
- 238000005516 engineering process Methods 0.000 description 4
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000005507 spraying Methods 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000877 morphologic effect Effects 0.000 description 1
- 235000010987 pectin Nutrition 0.000 description 1
- 229920001277 pectin Polymers 0.000 description 1
- 239000001814 pectin Substances 0.000 description 1
- 238000007789 sealing Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
- G01B11/04—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness specially adapted for measuring length or width of objects while moving
- G01B11/046—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness specially adapted for measuring length or width of objects while moving for measuring width
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A20/00—Water conservation; Efficient water supply; Efficient water use
- Y02A20/124—Water desalination
- Y02A20/131—Reverse-osmosis
Abstract
The invention provides a machine vision-based RO membrane gel line width detection system and a detection method, wherein the machine vision-based RO membrane gel line width detection system comprises the following components: a workbench for bearing RO membrane elements; the glue gun is arranged above the RO membrane element and is used for gluing the RO membrane; an industrial camera mounted above the RO membrane element, the industrial camera for capturing images of the RO membrane with the glue line formed; the industrial personal computer is connected with the industrial camera, and is used for receiving the image of the RO membrane acquired by the industrial camera, detecting according to the image and obtaining a detection result; a display for receiving and displaying images of the RO membrane and the measured results; and the driving device is used for driving the RO membrane element to rotate. Compared with the prior art, the invention monitors the width of the glue line by using the industrial camera and processes the data, and feeds back the measurement result in real time, thereby improving the detection efficiency and the detection quality and reducing the difference of the detection results caused by manual operation.
Description
[ field of technology ]
The invention belongs to the field of glue line width detection in the field of glue processing, and particularly relates to a machine vision-based RO (reverse osmosis) membrane glue line width detection system and a detection method.
[ background Art ]
The rapid development of the scientific technology drives the high intellectualization of the industrial production line, and the plastic wire width measurement technology is greatly developed, especially in the industries of electronic products, automobiles, batteries, shoemaking and the like. The usual glue line width measuring means are generally divided into two main categories: contact and non-contact. The contact type measurement is generally carried out by adopting tools such as vernier calipers and the like; the non-contact measurement generally adopts a measurement mode such as wired laser measurement, structured light measurement and the like. In the production process of RO (Reverse Osmosis), the gluing process is extremely important, if the glue line is too narrow, after the Reverse Osmosis membrane element is cut, the phenomenon of water leakage caused by unqualified sealing can be caused, for example, the pectin line is too wide, and the area of the water filtered by the Reverse Osmosis membrane can be reduced, so that the water yield is reduced. When the width of the glue line does not meet the requirement, the glue line needs to be processed in time so as not to influence the subsequent process, and therefore, the detection of the width of the glue line is necessary.
At present, the common means for measuring the width of the glue line is contact type measurement, a vernier caliper is generally used as a measuring tool, and the manual detection has subjectivity and standard inconsistency, so that the problems of high cost, high labor intensity, difficult guarantee of measuring precision and the like exist. Although the precision of structured light measurement, laser sensor etc. is high, but the price is high and all belong to local measurement, because the whole orbit needs to be measured to the glued line, and the platform exists the vibration, will cause measurement error to be bigger, can't satisfy the requirement of glued line width detection.
Accordingly, there is a need for an improved solution to the above-mentioned problems.
[ invention ]
The invention aims to provide a machine vision-based RO membrane gel line width detection system and a detection method, which can improve detection efficiency and detection quality and reduce difference of detection results caused by manual operation.
According to one aspect of the present invention, there is provided a machine vision-based RO membrane gel line width detection system comprising: a workbench for bearing an RO membrane element, wherein the RO membrane element comprises a rod core and an RO membrane wound on the rod core; the glue gun is arranged above the RO membrane element and is used for gluing the RO membrane so as to form glue lines on the RO membrane; an industrial camera mounted above the RO membrane element for capturing images of the RO membrane with the glue lines formed; the industrial personal computer is connected with the industrial camera and is used for receiving the image of the RO membrane acquired by the industrial camera and detecting according to the image so as to determine whether the width of the glue line on the RO membrane meets the standard requirement or not and obtain a detection result; the display is connected with the industrial personal computer and is used for receiving and displaying the image of the RO film with the glue line and the detection result; and the driving device is used for driving the RO membrane element to rotate.
According to another aspect of the present invention, the present invention provides a method for detecting a RO membrane gel line width detection system based on machine vision, which is characterized in that the method comprises: placing the RO membrane element on the table; the driving device drives the RO membrane element to rotate; the glue gun is used for gluing on the RO membrane in the RO membrane element so as to form a glue line on the RO membrane; the industrial camera collects images of the RO membrane with the glue line formed; the industrial personal computer extracts the edge of the outline of the glue line from the image of the RO membrane; the industrial personal computer measures the width of the glue line based on the edge of the extracted glue line outline; the industrial personal computer determines whether the width of the gel line on the RO membrane meets the standard requirement or not based on the measured width of the gel line so as to obtain a detection result; the display receives and displays the image of the RO membrane and the detection result.
Compared with the prior art, the invention monitors the width of the glue line by using the industrial camera and processes the data, and feeds back the measurement result in real time, thereby improving the detection efficiency and the detection quality and reducing the difference of the detection results caused by manual operation.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:
FIG. 1 is a schematic diagram of the overall structure of a machine vision-based RO membrane gel line width detection system in one embodiment of the present invention;
FIG. 2 is a flow chart of a method of detecting a RO membrane gel line width detection system based on machine vision according to one embodiment of the invention, such as shown in FIG. 1.
[ detailed description ] of the invention
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic may be included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Unless specifically stated otherwise, the terms coupled, connected, or connected, as used herein, mean either direct or indirect connection, such as a and B, and include both direct electrical connection of a and B, and connection of a to B through electrical components or circuitry.
In the description of the present invention, it should be understood that the terms "upper", "lower", "front", "rear", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element in question must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present invention.
Referring to fig. 1, a schematic diagram of an overall structure of a machine vision-based RO membrane gel line width detection system according to an embodiment of the present invention is shown. The machine vision-based RO membrane gel line width detection system shown in FIG. 1 comprises a workbench 110, a gel gun 120, an industrial camera 130, an industrial personal computer 140, a display 150 and a driving device 160.
The workbench 110 is used for bearing an RO membrane element 170, and the RO membrane element 170 comprises a rod core (not labeled) and an RO membrane (not labeled) wound on the rod core, wherein the RO membrane (i.e. a rubberized membrane sheet) is a background of a target glue line and is an important component of the RO membrane element 170. A glue gun 120 is mounted above the RO membrane element 170, the glue gun 120 being used to glue the RO membrane to form glue lines on the RO membrane. An industrial camera 130 is mounted above the RO membrane element 170, the industrial camera 130 being used to capture images of the RO membrane on which the glue lines are formed. The industrial personal computer 140 is connected with the industrial camera 130, and the industrial personal computer 140 is used for receiving the image of the RO membrane acquired by the industrial camera 130, and detecting according to the image to determine whether the width of the glue line on the RO membrane meets the standard requirement or not, so as to obtain a detection result. The display 150 is connected to the industrial personal computer 140, and the display 150 is used for receiving and displaying the image and the detection result of the RO film with the glue line. The driving device 160 is used to drive the RO membrane element 170 to rotate (or spin).
In the specific embodiment shown in fig. 1, the industrial camera 130 is turned on in the industrial personal computer 140 to collect images, and the track image of the glue line after each glue is applied is photographed and recorded; in order to ensure measurement accuracy, it is required that the optical axis of the lens 132 of the industrial camera 130 is perpendicular to the table 110.
Referring to fig. 2, a flow chart of a method for detecting the RO membrane gel line width detection system based on machine vision as shown in fig. 1 in an embodiment of the present invention is shown. The detection method of the RO membrane gel line width detection system based on machine vision shown in fig. 2 comprises the following steps.
Step 210, placing the RO membrane element 170 on the table 110.
Step 220, the driving device 160 drives the RO membrane element 170 to rotate.
Step 230, glue gun 120 glues the RO membrane (not identified) in RO membrane element 170 to form glue lines on the RO membrane.
Step 240, the industrial camera 130 captures an image of the RO membrane with the glue line formed.
Step 250, the industrial personal computer 140 extracts the edge of the contour of the glue line from the image of the RO membrane.
In step 260, the industrial personal computer 140 measures the width of the glue line based on the edge of the extracted glue line profile.
Step 270, the industrial personal computer 140 determines whether the width of the glue line on the RO membrane meets the standard requirement (i.e. determines the quality of the glue line) based on the measured width of the glue line, so as to obtain a detection result.
Step 280, the display 150 receives and displays the image of the RO membrane collected by the industrial personal computer 140 and the detection result obtained by the industrial personal computer 140.
In a preferred embodiment, a polynomial interpolation based subpixel edge detection algorithm is used to extract the edges of the glue line profile from the image of the RO membrane. The improved Canny algorithm can finely extract the edge of the glue line outline.
In a specific embodiment of the present invention, step 260 (i.e., measuring the glue line width based on the edges of the extracted glue line profile) includes: dividing the edge of the extracted glue line outline into a plurality of small sections in sequence, and measuring the width of each small section of glue line to obtain the width pixel value of each small section of glue line; based on the width pixel value of each small section of glue line and the pixel equivalent of the industrial camera 130, a width measurement value of each small section of glue line is obtained. Correspondingly, determining whether the width of the gel line of the RO membrane meets the standard requirement or not based on the measured width measurement value of each small section of gel line. Wherein the pixel equivalent is obtained by the industrial camera 130 when performing camera calibration.
And (3) calibrating an industrial camera: because the invention adopts the industrial camera 130 to collect the image, the obtained size is the pixel size, the industrial camera 130 needs to be calibrated, the lens 132 of the industrial camera 130 is subjected to distortion correction, the pixel equivalent is obtained, and the pixel size is converted into the actual size (or the measured size). In a preferred embodiment, the industrial camera 130 is calibrated using a calibration plate to find its pixel equivalent.
In a specific embodiment of the present invention, "measuring the width of each small section of the glue line to obtain the width pixel value of each small section of the glue line" includes: performing straight line fitting on the contour of one side of each small section of glue line by adopting a least square algorithm to obtain a fitting straight line of the contour of one side of the small section of glue line; and selecting a plurality of points on the outline on the other side of the small section of glue line, and calculating the average distance between the plurality of points and the fitting straight line, wherein the average distance is used as the width pixel value of the small section of glue line. For example, firstly, a fitting straight line equation ax+by+c=0 of a contour on one side of a small section of glue line is obtained, secondly, the first and last points and the middle point of the contour on the other side of the small section of glue line are selected, the distance d1 from the fitting straight line is obtained respectively, and finally, the average distance d from the points to the fitting straight line is obtained. In order to improve the detection accuracy of the edges of the sub-pixels, a least square algorithm is adopted to conduct straight line fitting on the outline of each small section of glue line.
In a specific embodiment of the invention, a measuring rectangle with a proper size is selected according to a gluing line, the edge of the extracted glue line outline is sequentially divided into a plurality of small sections, for example, 273 measuring rectangles are set in total and numbered sequentially for the whole glue track, and the glue line widths with certain intervals are sequentially measured from the lower left corner to the lower right corner of the measuring rectangle along the gluing line; correspondingly, the display 150 also displays the measured rectangular distribution as well as the width measurement.
In a specific embodiment of the present invention, the detection method of the RO membrane gel line width detection system based on machine vision shown in fig. 2 further comprises: before extracting the edge of the contour of the glue line from the image of the RO membrane, the industrial control computer 140 performs image preprocessing on the image of the RO membrane. The image preprocessing includes: firstly, extracting an ROI (region of interest, namely an interested region) in an image of an RO membrane, wherein the ROI region is a region covered by a gel line track, and marking the ROI region related to the gel line track can remove part of interference regions; then, gray morphology processing is carried out on the extracted ROI area, and reflection on the glue line can be removed; and finally, conducting guide filtering processing on the ROI area subjected to morphological processing to remove noise interference, namely denoising the image by adopting a guide filtering algorithm which can keep more edge details and has shorter time.
In summary, the invention aims to solve the problems that the quality is unqualified and the AB glue is prevented from being wasted due to missed detection caused by too wide and too narrow glue lines in the glue spraying process, adopts a machine vision technology to carry out non-contact detection, calculates the error between the standard size and the measured size, judges whether the standard size and the measured size meet the requirements, monitors the glue spraying process and the glue line quality, can improve the current situation that the detection of the existing glue line is mainly finished by manpower, improves the detection efficiency and the detection quality, and reduces the difference of detection results caused by manual operation.
Compared with the prior art, the invention has the beneficial effects that:
(1) The operation is simple and convenient, and the width detection of the glue line can be carried out by starting the industrial personal computer to run the upper computer software;
(2) The visual, upper computer interface is simple and clear, and can directly observe the parameters such as the video stream of the gluing track, the rectangular distribution of the glue line width measurement, the measured value and the like;
(3) The compatibility is good, the expansibility is strong, and the system can directly run in Windows, linux and other different operating systems;
(4) The precision is high, the measuring range is wide, and the measuring precision of the invention is within +/-0.2 mm;
(5) The real-time performance is strong, 30 frames of images are acquired every second, and unqualified glue lines can be processed in time.
It should be noted that any modifications to the specific embodiments of the invention may be made by those skilled in the art without departing from the scope of the invention as defined in the appended claims. Accordingly, the scope of the claims of the present invention is not limited to the foregoing detailed description.
Claims (10)
1. RO membrane line of glue width detecting system based on machine vision, its characterized in that includes:
a workbench for bearing an RO membrane element, wherein the RO membrane element comprises a rod core and an RO membrane wound on the rod core;
the glue gun is arranged above the RO membrane element and is used for gluing the RO membrane so as to form glue lines on the RO membrane;
an industrial camera mounted above the RO membrane element for capturing images of the RO membrane with the glue lines formed;
the industrial personal computer is connected with the industrial camera and is used for receiving the image of the RO membrane acquired by the industrial camera and detecting according to the image so as to determine whether the width of the glue line on the RO membrane meets the standard requirement or not and obtain a detection result;
the display is connected with the industrial personal computer and is used for receiving and displaying the image of the RO film with the glue line and the detection result;
and the driving device is used for driving the RO membrane element to rotate.
2. The machine vision-based RO membrane gel line width detection system of claim 1, wherein,
starting the industrial camera in the industrial personal computer to acquire images;
the optical axis of the lens of the industrial camera is perpendicular to the workbench.
3. A method of detecting a machine vision-based RO membrane gel line width detection system according to claim 1 or 2, comprising:
placing the RO membrane element on the table;
the driving device drives the RO membrane element to rotate;
the glue gun is used for gluing on the RO membrane in the RO membrane element so as to form a glue line on the RO membrane;
the industrial camera collects images of the RO membrane with the glue line formed;
the industrial personal computer extracts the edge of the outline of the glue line from the image of the RO membrane;
the industrial personal computer measures the width of the glue line based on the edge of the extracted glue line outline;
the industrial personal computer determines whether the width of the gel line on the RO membrane meets the standard requirement or not based on the measured width of the gel line so as to obtain a detection result;
the display receives and displays the image of the RO membrane and the detection result.
4. The method according to claim 3, wherein,
and extracting the edge of the glue line outline from the image of the RO film by adopting a sub-pixel edge detection algorithm based on polynomial interpolation.
5. The method according to claim 3, wherein,
the "edge measurement glue line width based on the extracted glue line profile" includes: sequentially dividing the edge of the extracted glue line outline into a plurality of small sections, and measuring the width of each small section of glue line to obtain the width pixel value of each small section of glue line; based on the width pixel value of each small section of glue line and the pixel equivalent of the industrial camera, obtaining a width measurement value of each small section of glue line,
correspondingly, determining whether the width of the gel line of the RO membrane meets the standard requirement or not based on the measured width measurement value of each small section of gel line.
6. The method according to claim 5, wherein,
the step of measuring the width of each small section of the glue line to obtain the width pixel value of each small section of the glue line includes:
performing straight line fitting on the contour of one side of each small section of glue line by adopting a least square algorithm to obtain a fitting straight line of the contour of one side of the small section of glue line;
selecting a plurality of points on the outline of the other side of the small section of glue line;
the average distance from the points to the fitting straight line is calculated and is taken as the width pixel value of the small section of glue line.
7. The method according to claim 5, wherein,
and selecting a measuring rectangle with a proper size according to the glue-beating line, and dividing the edge of the extracted glue line outline into a plurality of small sections in sequence.
8. The method according to claim 7, wherein,
the display also displays the measured rectangular distribution and the width measurement.
9. The method according to claim 3, wherein,
the method also comprises the step that before the edge of the outline of the gel line is extracted from the image of the RO membrane, the industrial personal computer carries out image preprocessing on the image of the RO membrane,
the image preprocessing includes:
extracting an interested region in the image of the RO membrane, wherein the interested region is a region covered by a gel line track;
carrying out gray morphology processing on the extracted region of interest to remove reflection on a glue line;
and carrying out guided filtering processing on the region of interest after gray morphology processing so as to remove noise interference.
10. The method according to claim 6, wherein,
the pixel equivalent is obtained by the industrial camera when the camera calibration is carried out;
and calibrating the industrial camera by using a calibration plate to obtain the pixel equivalent. .
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310973564.2A CN116907360B (en) | 2023-08-03 | 2023-08-03 | RO (reverse osmosis) membrane gel line width detection system and detection method based on machine vision |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310973564.2A CN116907360B (en) | 2023-08-03 | 2023-08-03 | RO (reverse osmosis) membrane gel line width detection system and detection method based on machine vision |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116907360A true CN116907360A (en) | 2023-10-20 |
| CN116907360B CN116907360B (en) | 2024-03-12 |
Family
ID=88364817
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310973564.2A Active CN116907360B (en) | 2023-08-03 | 2023-08-03 | RO (reverse osmosis) membrane gel line width detection system and detection method based on machine vision |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116907360B (en) |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106064753A (en) * | 2016-07-22 | 2016-11-02 | 珠海格力电器股份有限公司 | A kind of wound membrane Apparatus and method for |
| CN106093057A (en) * | 2016-06-14 | 2016-11-09 | 上海贝特威自动化科技有限公司 | A kind of online gluing detection method |
| CN108507472A (en) * | 2018-03-19 | 2018-09-07 | 江南大学 | A kind of safe automobile air bag strip of paper used for sealing size non-contact vision detection method |
| CN108838027A (en) * | 2018-05-08 | 2018-11-20 | 河南汇丰水处理设备有限公司 | A kind of RO automation wound membrane equipment and RO wound membrane preparation method |
| CN109590134A (en) * | 2018-12-26 | 2019-04-09 | 上海福赛特机器人有限公司 | A kind of device and method in the folding line position of folded membrane progress glue spraying |
| CN109840902A (en) * | 2019-01-21 | 2019-06-04 | 无锡埃姆维工业控制设备有限公司 | A kind of gluing detection method, device and storage medium |
| CN111097664A (en) * | 2019-12-20 | 2020-05-05 | 广西柳州联耕科技有限公司 | Real-time deviation rectifying method based on robot gluing |
| CN112819845A (en) * | 2021-02-26 | 2021-05-18 | 华南理工大学 | Flexible packaging substrate contour, line width and line distance defect detection method, medium and equipment |
| CN113340909A (en) * | 2021-08-05 | 2021-09-03 | 常州铭赛机器人科技股份有限公司 | Glue line defect detection method based on machine vision |
| CN113763323A (en) * | 2021-07-30 | 2021-12-07 | 广东省威汇智能科技有限公司 | Vehicle-mounted camera dispensing detection method based on machine vision |
| CN115127479A (en) * | 2022-09-02 | 2022-09-30 | 西安西动智能科技有限公司 | Machine vision-based rubber roller thread online detection and correction method |
| CN115365088A (en) * | 2022-09-05 | 2022-11-22 | 苏州光宝科技股份有限公司 | Dispensing method and device based on visual guidance |
| CN115682943A (en) * | 2021-07-21 | 2023-02-03 | 苏州希盟科技股份有限公司 | Method for detecting glue line |
| CN115880205A (en) * | 2021-09-26 | 2023-03-31 | 北京小米移动软件有限公司 | Detection method and detection equipment for shell gluing line |
-
2023
- 2023-08-03 CN CN202310973564.2A patent/CN116907360B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106093057A (en) * | 2016-06-14 | 2016-11-09 | 上海贝特威自动化科技有限公司 | A kind of online gluing detection method |
| CN106064753A (en) * | 2016-07-22 | 2016-11-02 | 珠海格力电器股份有限公司 | A kind of wound membrane Apparatus and method for |
| CN108507472A (en) * | 2018-03-19 | 2018-09-07 | 江南大学 | A kind of safe automobile air bag strip of paper used for sealing size non-contact vision detection method |
| CN108838027A (en) * | 2018-05-08 | 2018-11-20 | 河南汇丰水处理设备有限公司 | A kind of RO automation wound membrane equipment and RO wound membrane preparation method |
| CN109590134A (en) * | 2018-12-26 | 2019-04-09 | 上海福赛特机器人有限公司 | A kind of device and method in the folding line position of folded membrane progress glue spraying |
| CN109840902A (en) * | 2019-01-21 | 2019-06-04 | 无锡埃姆维工业控制设备有限公司 | A kind of gluing detection method, device and storage medium |
| CN111097664A (en) * | 2019-12-20 | 2020-05-05 | 广西柳州联耕科技有限公司 | Real-time deviation rectifying method based on robot gluing |
| CN112819845A (en) * | 2021-02-26 | 2021-05-18 | 华南理工大学 | Flexible packaging substrate contour, line width and line distance defect detection method, medium and equipment |
| CN115682943A (en) * | 2021-07-21 | 2023-02-03 | 苏州希盟科技股份有限公司 | Method for detecting glue line |
| CN113763323A (en) * | 2021-07-30 | 2021-12-07 | 广东省威汇智能科技有限公司 | Vehicle-mounted camera dispensing detection method based on machine vision |
| CN113340909A (en) * | 2021-08-05 | 2021-09-03 | 常州铭赛机器人科技股份有限公司 | Glue line defect detection method based on machine vision |
| CN115880205A (en) * | 2021-09-26 | 2023-03-31 | 北京小米移动软件有限公司 | Detection method and detection equipment for shell gluing line |
| CN115127479A (en) * | 2022-09-02 | 2022-09-30 | 西安西动智能科技有限公司 | Machine vision-based rubber roller thread online detection and correction method |
| CN115365088A (en) * | 2022-09-05 | 2022-11-22 | 苏州光宝科技股份有限公司 | Dispensing method and device based on visual guidance |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116907360B (en) | 2024-03-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110017773B (en) | Package volume measuring method based on machine vision | |
| CN109489566B (en) | Lithium battery diaphragm material slitting width detection method, detection system and device | |
| CN108876744B (en) | Large-scale point cloud noise denoising method based on region segmentation | |
| CN102175700A (en) | Method for detecting welding seam segmentation and defects of digital X-ray images | |
| CN107703513B (en) | Non-contact net relative position detection method based on image processing | |
| CN110966956A (en) | Binocular vision-based three-dimensional detection device and method | |
| CN113340909B (en) | Glue line defect detection method based on machine vision | |
| CN114881915A (en) | Symmetry-based mobile phone glass cover plate window area defect detection method | |
| CN113325001A (en) | Automatic distinguishing and detecting equipment and method for surface appearance flaws of copper foil | |
| CN111879264A (en) | Flatness measurement and evaluation system based on line structured light | |
| CN111624203A (en) | Relay contact alignment non-contact measurement method based on machine vision | |
| CN109187561A (en) | A kind of vehicle door interior trim defective vision detection system | |
| CN115575416A (en) | Flexible circuit board pad detection method and system | |
| CN110470247B (en) | Device and method for detecting coaxiality of inner and outer circular surfaces of part | |
| CN110570412A (en) | part error vision judgment system | |
| CN116907360B (en) | RO (reverse osmosis) membrane gel line width detection system and detection method based on machine vision | |
| CN117058411A (en) | Method, device, medium and equipment for identifying edge appearance flaws of battery | |
| WO2023123003A1 (en) | Machine vision detection method, detection apparatus and detection system thereof | |
| CN113240629B (en) | Edge-based image matching narrow-gap weld initial point positioning device and method | |
| CN110111317A (en) | A kind of dispensing visual detection method for quality based on intelligent robot end | |
| CN111435075A (en) | Computer vision measurement system | |
| CN109579720B (en) | Extensometer dynamic measurement method for measuring edge distance | |
| CN114219758A (en) | Defect detection method, system, electronic device and computer readable storage medium | |
| CN110021027B (en) | Edge cutting point calculation method based on binocular vision | |
| CN113869407A (en) | Monocular vision-based vehicle length measuring method and device |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |