CN101762589A - On-line monitoring method of machine vision on stationery combined set flaw and equipment thereof - Google Patents
On-line monitoring method of machine vision on stationery combined set flaw and equipment thereof Download PDFInfo
- Publication number
- CN101762589A CN101762589A CN200910155499A CN200910155499A CN101762589A CN 101762589 A CN101762589 A CN 101762589A CN 200910155499 A CN200910155499 A CN 200910155499A CN 200910155499 A CN200910155499 A CN 200910155499A CN 101762589 A CN101762589 A CN 101762589A
- Authority
- CN
- China
- Prior art keywords
- stationery
- combined
- combined set
- cylinder
- stationery combined
- 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
Images
Abstract
The invention discloses an on-line monitoring method of machine vision on stationery combined set flaw, which comprises the following steps: (1) using an industrial video camera and external triggering signals to control the video camera to shoot the on-line operation stationery combined set; (2) selecting the stationery combined set with the correct configuration as a standard image template to be stored into a computer; (3), controlling the video camera by the external triggering signals for shooting the images of the on-line operation stationery combined set in real time, and transmitting the shot images to the computer for detection; and (4) comparing the real-time shooting images obtained in the third step to the standard image template by the computer, carrying out the analysis and judgment, and using the equipment of the monitoring equipment. The invention reduces the work intensity of workers, and ensures higher qualification rate of the products.
Description
Technical field
The present invention relates to on-line monitoring method and the equipment thereof of a kind of machine vision at stationery combined set flaw.Belong to Vision Builder for Automated Inspection and carry out the technical field of on-line monitoring, relate in particular to, utilize Vision Builder for Automated Inspection the flaw of stationery combined set to be carried out the method and the equipment thereof of on-line monitoring at stationery Assembling Production scene.
Background technology
Stationery combined set because generally existing at present the employing manually assembled and packing, so defective often takes place to assemble, need carry out on-line monitoring to assembling flaw.In the prior art, dependence manually detects to the assembling Defect Detection.The shortcoming of its existence is: because product type is a lot, the workman is difficult to effectively remember the situation of all models; The workman works long hours and is easy to generate visual fatigue, can't guarantee to detect quality, therefore can't guarantee the ex factory pass rate of product.
Summary of the invention
In order to address the above problem, the object of the present invention is to provide a kind of machine vision to join the on-line monitoring method and the equipment thereof of flaw at stationery combined set, the present invention has reduced working strength of workers, guarantees the higher qualification rate of product.
For reaching above-mentioned purpose, the present invention adopts following technical scheme,
A kind of machine vision comprises the steps: in the on-line monitoring method of stationery combined flaw
(1) utilize industrial camera and outer triggering signal to control the stationery combined set that described video camera is taken on-line operation;
(2) select the correct stationery combined set of assembling as the standard picture template stores in computing machine;
(3) control described video camera by outer triggering signal, take the image of the stationery combined set of on-line operation in real time, and photographic images is transferred to computing machine for detecting;
(4) image of computing machine real-time shooting that step (3) step is obtained and the image template of standard compare, analyze, judge, when captured image and template do not match, then by the computer starting warning device, alert confirms whether really to have flaw, and handles; When captured image and template matches, then directly pass through.
A kind of machine vision comprises as lower device at the on-line monitoring equipment of stationery assembling flaw, industrial camera, and stationery detects the transmission belt of streamline, first cylinder, second cylinder, the 3rd cylinder, first stationery combined set, second stationery combined set; First stationery combined set wherein, second stationery combined set lays respectively on the transmission belt, industrial camera is installed in the top of the first combined stationery combined complete, make the camera of industrial camera just aim at first suit, and industrial camera is connected with compunication; The side that stationery detects the transmission belt of streamline is separately installed with first cylinder, second cylinder and the 3rd cylinder.
The invention has the beneficial effects as follows: the present invention is directed to prior art big to online personal monitoring's labour intensity of stationery assembling flaw, easily visual fatigue, can't guarantee to detect the problem of quality and ex factory pass rate, the invention provides online test method and the equipment thereof of a kind of Vision Builder for Automated Inspection to stationery combined set assembling flaw, it has reduced working strength of workers, guarantees the higher qualification rate of product.
Description of drawings
Fig. 1 is a process sequence diagram of the present invention;
Fig. 2 detects the streamline synoptic diagram for stationery combined set of the present invention;
Fig. 3 is the pattern of the standard picture template of stationery combined set of the present invention;
Fig. 4 is the flaw pattern of " dislocation " in the stationery combined set image of the present invention;
Fig. 5 is the flaw pattern of " disappearance " in the stationery combined set image of the present invention;
Fig. 6 is the flaw pattern of " stained " in the stationery combined set image of the present invention.
Embodiment
A kind of machine vision as shown in Figure 1 comprises the steps: that in the on-line monitoring method of stationery assembling flaw (1) utilizes industrial camera and outer triggering signal to control the stationery combined set that described video camera is taken on-line operation; And to the setting (2) of camera aperture, exposure time etc. select the correct stationery combined set of assembling as the standard picture template stores in computing machine; (3) control described video camera by outer triggering signal, take the image of the stationery combined set of on-line operation in real time, and photographic images is transferred to computing machine for detecting; (4) image of computing machine real-time shooting that step (3) is obtained and the image template of standard compare, analyze, judge, when captured image and template do not match, then by the computer starting warning device, alert confirms whether really to have flaw, and handles; When captured image and template matches, then directly pass through, detect and finish, carry out the detection of next stationery combined set.Utilize the on-line monitoring equipment of a kind of machine vision of above-mentioned detection method at the stationery combined flaw, comprise as lower device, as shown in Figure 2, the industrial camera (not shown), stationery detects transmission belt 3, the first cylinders 4 of streamline, second cylinder 5, the 3rd cylinder 6, the first stationery combined sets 1, the second stationery combined set 2; First stationery combined set 1 wherein, second stationery combined set 2 lays respectively on the transmission belt 3,1 of Xi'an side's sincere 1300UM type industrial camera is fixed on 1 meter height in top of first stationery combined set 1 of stationery combined set detection streamline as shown in Figure 2, make the camera of industrial camera just aim at first stationery combined set 1, video camera uses 8mmCOMPUTER type camera lens, aperture is transferred to maximal value, time shutter is 0.58ms, yield value is adjusted to 0, adopt the 2.56MHz white light source, directly over the irradiation, so that make the model of stationery combined set and color to the video camera relative insensitivity, and to the flaw sensitivity, the power supply of display light source is a constant pressure and flow, so as can be stable photograph picture clearly.And industrial camera and computing machine (among the figure ont yet) communicate to connect; The side that stationery detects the transmission belt 3 of streamline is separately installed with first cylinder, 4, the second cylinders 5 and the 3rd cylinder 6.
At first to the standard picture collection.First stationery combined set, 1, the second stationery combined set 2 moves on transmission belt 3 as shown in Figure 2.Transmission belt 3 after certain second stationery combined set 2 can also have the 3rd combined complete, the many combined completes to be detected of the 4th combined complete or the like.Begin image template is selected and stored.
A) when first cylinder 4,5 withdrawals of second cylinder, when the 3rd cylinder 6 stretches out, will be blocked by the 3rd cylinder 6, can not advance with the stationery combined set formation headed by first stationery combined set 1.
B) this moment, second cylinder 5 stretched out, it is compacted then to come top first stationery combined set 1, make industrial camera take image first stationery combined set 1 on by the computer starting outer triggering signal this moment, first stationery combined set 1 is to select complete display through operating personnel, and flawless file suit image is stored in the computing machine as standard picture.
C) first cylinder 4 stretches out then, second cylinder 5 and 6 withdrawals of the 3rd cylinder, and first stationery combined set 1 of the image that then has been taken in step b) is pulled away under the motion of transmission belt 3.
Second stationery combined set 2 is sent to the stationery combined set surveyed area under the motion of transmission belt 3 then, detects step then.
1) first cylinder 4,5 withdrawals of second cylinder at this moment when the 3rd cylinder 6 stretches out, will be blocked by cylinder 6 with the stationery combined set formation headed by second stationery combined set 2, can not advance;
2) second cylinder 5 stretches out then, it is compacted then to come top second stationery combined set 2, make industrial camera to second stationery combined set 2 carry out image taking by the computer starting outer triggering signal this moment, then with computing machine in the standard picture of first stationery combined set 1 stored compare; If comparing result is found " dislocation ", " disappearance " and situations such as " stained ", sound and light alarm then, alert is handled.As Fig. 3 is the pattern of the standard picture template of stationery combined set, Fig. 4 is the flaw pattern of " dislocation " in the stationery combined set image, Fig. 5 is the flaw pattern of " disappearance " in the stationery combined set image, and Fig. 6 is the flaw pattern of " stained " in the stationery combined set image; If detect normally then directly pass through, enter detection step to the combined complete of back.
3) detection to the combined complete of back at first is that first cylinder 4 stretches out, and second cylinder 5 and 6 withdrawals of the 3rd cylinder are then in step 2) second stationery combined set 2 of the image that is taken is pulled away under the motion of transmission belt 3.All stationery combined sets in according to above steps in sequence stationery combined set being lined up then detect.
Claims (2)
1. a machine vision is characterized in that: comprise the steps: in the on-line monitoring method of stationery combined flaw
(1) utilize industrial camera and outer triggering signal to control the stationery combined set that described video camera is taken on-line operation;
(2) select the correct stationery combined set of assembling as the standard picture template stores in computing machine;
(3) control described video camera by outer triggering signal, take the image of the stationery combined set of on-line operation in real time, and photographic images is transferred to computing machine for detecting;
(4) image of computing machine real-time shooting that step (3) step is obtained and the image template of standard compare, analyze, judge, when captured image and template do not match, then by the computer starting warning device, alert confirms whether really to have flaw, and handles; When captured image and template matches, then directly pass through.
2. a machine vision as claimed in claim 1 is at the on-line monitoring equipment of stationery combined flaw, it is characterized in that comprising as lower device, industrial camera, the transmission belt (3) of stationery combine detection streamline, first cylinder (4), second cylinder (5), the 3rd cylinder (6), the first combined stationery combined complete (1), the second combined stationery combined complete (2); The first combined stationery combined complete (1) wherein, the second combined stationery combined complete (2) lays respectively on the transmission belt (3), industrial camera is installed in the top of the first combined stationery combined complete (1), make the camera of industrial camera just aim at the first combined stationery combined complete (1), and industrial camera is connected with compunication; One side of the transmission belt (3) of stationery combine detection streamline is separately installed with first cylinder (4), second cylinder (5) and the 3rd cylinder (6).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN200910155499A CN101762589A (en) | 2009-12-17 | 2009-12-17 | On-line monitoring method of machine vision on stationery combined set flaw and equipment thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN200910155499A CN101762589A (en) | 2009-12-17 | 2009-12-17 | On-line monitoring method of machine vision on stationery combined set flaw and equipment thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN101762589A true CN101762589A (en) | 2010-06-30 |
Family
ID=42493880
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN200910155499A Pending CN101762589A (en) | 2009-12-17 | 2009-12-17 | On-line monitoring method of machine vision on stationery combined set flaw and equipment thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101762589A (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102288615A (en) * | 2011-07-12 | 2011-12-21 | 王万年 | Method for detecting middle line adhesive on filter rod |
| CN102305797A (en) * | 2011-04-29 | 2012-01-04 | 无锡众望四维科技有限公司 | Method for automatically detecting foreign matter of medical product package by using machine vision system |
| CN102495077A (en) * | 2011-11-14 | 2012-06-13 | 无锡众望四维科技有限公司 | Automatic detecting method of machine vision system for detecting flaws of infusion bottle |
| CN102495072A (en) * | 2011-11-14 | 2012-06-13 | 无锡众望四维科技有限公司 | Automatic detection method for flaw of transfusion catheter through machine vision system |
| CN102495074A (en) * | 2011-11-14 | 2012-06-13 | 无锡众望四维科技有限公司 | Automatic detecting method of machine vision system for detecting flaws of infusion bag |
| CN102507602A (en) * | 2011-11-14 | 2012-06-20 | 无锡众望四维科技有限公司 | Method for automatically detecting rupture of infusion bottle mouth by using machine vision system |
| CN109508722A (en) * | 2018-11-08 | 2019-03-22 | 中交第二航务工程局有限公司 | Picture comparison method and picture Compare System based on gray value |
| CN110383062A (en) * | 2017-02-23 | 2019-10-25 | 艾达普特有限公司 | For identifying and authenticating the adjustable systems of clothes |
| CN114707904A (en) * | 2022-05-05 | 2022-07-05 | 江苏文友软件有限公司 | Quality detection method and system based on big data |
-
2009
- 2009-12-17 CN CN200910155499A patent/CN101762589A/en active Pending
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102305797A (en) * | 2011-04-29 | 2012-01-04 | 无锡众望四维科技有限公司 | Method for automatically detecting foreign matter of medical product package by using machine vision system |
| CN102288615A (en) * | 2011-07-12 | 2011-12-21 | 王万年 | Method for detecting middle line adhesive on filter rod |
| CN102288615B (en) * | 2011-07-12 | 2015-08-26 | 王万年 | The detection method of middle line adhesive on filter rod |
| CN102495077A (en) * | 2011-11-14 | 2012-06-13 | 无锡众望四维科技有限公司 | Automatic detecting method of machine vision system for detecting flaws of infusion bottle |
| CN102495072A (en) * | 2011-11-14 | 2012-06-13 | 无锡众望四维科技有限公司 | Automatic detection method for flaw of transfusion catheter through machine vision system |
| CN102495074A (en) * | 2011-11-14 | 2012-06-13 | 无锡众望四维科技有限公司 | Automatic detecting method of machine vision system for detecting flaws of infusion bag |
| CN102507602A (en) * | 2011-11-14 | 2012-06-20 | 无锡众望四维科技有限公司 | Method for automatically detecting rupture of infusion bottle mouth by using machine vision system |
| CN110383062A (en) * | 2017-02-23 | 2019-10-25 | 艾达普特有限公司 | For identifying and authenticating the adjustable systems of clothes |
| CN109508722A (en) * | 2018-11-08 | 2019-03-22 | 中交第二航务工程局有限公司 | Picture comparison method and picture Compare System based on gray value |
| CN114707904A (en) * | 2022-05-05 | 2022-07-05 | 江苏文友软件有限公司 | Quality detection method and system based on big data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101762589A (en) | On-line monitoring method of machine vision on stationery combined set flaw and equipment thereof | |
| CN104441526B (en) | Mould in-service monitoring protection system and method based on appearance profile coupling | |
| CN100593716C (en) | On-line detecting method of machine vision system for printed calico flaw | |
| CN102539443B (en) | Bottle body defect automatic detection method based on machine vision | |
| CN104432498B (en) | Cigarette making machine apparent visual detection means based on machine vision | |
| CN108613987A (en) | Cigarette appearance real-time online detects device for eliminating and method | |
| CN105717132B (en) | A kind of the built-in fitting detection system and method for PC component production line | |
| CN111229648A (en) | Solar cell panel flaw detection system and detection method based on machine vision | |
| CN105976365A (en) | Nocturnal fire disaster video detection method | |
| CN102519981A (en) | Online detection system for PVC (polyvinyl chloride) building material surface quality | |
| CN102494773A (en) | Automatic detection method of machine vision system on snap-fastener chromatic aberration | |
| CN106706656A (en) | Machine vision-based zipper detection device and method | |
| CN101169826A (en) | Row roller forming welding tube quality on-line monitoring and controlling system based on machine vision | |
| CN105844282A (en) | Method for detecting defects of fuel injection nozzle O-Ring through line scanning camera | |
| CN202471610U (en) | Automatic bottle body defect detecting device based on machine vision | |
| CN102305597A (en) | Method for automatically detecting abnormal shape of injector part by using mechanical vision system | |
| CN102305603B (en) | Method for automatically detecting inclination of steel needle of injector by machine vision system | |
| CN201569631U (en) | Equipment for online monitoring defects of stationery combination sets by machine vision system | |
| CN102305592A (en) | Method for automatically detecting back-stitching of steel needle of injector by using mechanical vision system | |
| CN102305950A (en) | Method for automatically detecting missed accessory during automatic assembly of injector by using machine visual system | |
| CN202814334U (en) | Bearing ring vehicle process leak process procedure detection device | |
| CN102305797A (en) | Method for automatically detecting foreign matter of medical product package by using machine vision system | |
| CN116253026A (en) | Cigarette appearance detection and discrimination processing system and method for GDX2 packaging equipment | |
| CN208155893U (en) | binocular vision scratch detection system based on high speed camera | |
| CN102507602A (en) | Method for automatically detecting rupture of infusion bottle mouth by using machine vision system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C12 | Rejection of a patent application after its publication | ||
| RJ01 | Rejection of invention patent application after publication |
Open date: 20100630 |