CN103018254A - Automatic detection device based on image identification technology - Google Patents
Automatic detection device based on image identification technology Download PDFInfo
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- CN103018254A CN103018254A CN2012105093361A CN201210509336A CN103018254A CN 103018254 A CN103018254 A CN 103018254A CN 2012105093361 A CN2012105093361 A CN 2012105093361A CN 201210509336 A CN201210509336 A CN 201210509336A CN 103018254 A CN103018254 A CN 103018254A
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Abstract
The invention discloses an automatic detection device based on an image identification technology. The quality of a part is detected by the image identification technology; under the condition that the part is not contacted, long-time high-efficiency detection operation can be kept; and particularly, compared with a manual detection device, the automatic detection device can detect small defects on the surface of the part more quickly and efficiently.
Description
Technical field
The present invention relates to a kind of automatic detection device based on image recognition technology, belong to test and field of measuring techniques.
Background technology
In the industrial processes, need to detect product, check omission or repetition that whether it has processing technology, whether have annex that the problems such as omission are installed, to confirm that product meets industrial requirements and standard.At present, product detects and is mostly undertaken by artificial or mechanical hook-up.Manual detection is owing to testing staff's the reasons such as fatigue carelessness can cause undetected.Mechanical hook-up then because Mechanical Contact is arranged, can destroy or damage product.Simultaneously for some tiny flaws on the part to be detected, sand holes for example, the tiny defects such as pin hole.These tiny defectives are not easy to be detected by artificial and mechanical detection.
Summary of the invention
Goal of the invention: the present invention proposes a kind of automatic detection device based on image recognition technology, can detect efficiently various tiny product defectses, and guarantees stable detection quality.
Technical scheme: the technical solution used in the present invention is a kind of automatic detection device based on image recognition technology, and it comprises: worktable, camera, computing machine, communication converter, audible-visual annunciator and input/output module.
Worktable is installed part to be detected, and camera obtains part image and sends to computing machine, and computing machine is connected to input/output module by communication converter, and input/output module is connected to audible-visual annunciator.
As a further improvement on the present invention, described communication converter is realized the mutual conversion between USB and the RS485 interface.Described audible-visual annunciator is comprised of pilot lamp and hummer.
A kind of automatic testing method based on image recognition technology may further comprise the steps:
1) computer booting self check peripherals detects the camera and the communication converter that have connected automatically, the driver that the operating system Automatically invoked carries, and provide api interface for user application;
2) start user application, application program is set up and being connected of camera by DLL (dynamic link library), and the communication interface foundation that carries by operating system is connected with communication converter;
3) computing machine sends order by communication converter, allows the input/output module point give a green light;
4) computing machine enters holding state, and it obtains view data and constantly refreshing by camera, and when part to be detected is put into worktable, camera obtains image and the autostore of part to be detected;
5) part image to be detected of storing in the step 4) carries out image recognition in computing machine, when part to be detected is normal, computing machine sends instruction by communication converter, allow input/output module light blue indicator light, the continuous cycle detection image of simultaneous computer, wait for that complete after testing part to be detected shifts out worktable and closes blue indicator light again, computing machine comes back to holding state;
6) if the part to be detected that detects in the step 5) is unusual, computing machine sends instruction by communication converter, allows input/output module light red led, and input/output module guide sound light crossing-signal sends buzzing warning and continuous flashing indicator light simultaneously;
7) report to the police after, manually remove the part to be detected on the worktable, and manually eliminate the alerting signal of audible-visual annunciator, and be holding state with computer installation.
Beneficial effect: the present invention detects part quality with image recognition technology, can keep the long-time action that detects efficiently in the situation of contact part not.Especially the tiny defect that exists for piece surface, the present invention can more rapidly and efficiently detect with respect to manual detection.
Description of drawings
Fig. 1 is the structural representation that the present invention is based on the automatic detection device of image recognition technology;
Fig. 2 is the workflow diagram that the present invention is based on the automatic detection device of image recognition technology.
Embodiment
Below in conjunction with the drawings and specific embodiments, further illustrate the present invention, should understand these embodiment only is used for explanation the present invention and is not used in and limits the scope of the invention, after having read the present invention, those skilled in the art all fall within the application's claims limited range to the modification of the various equivalent form of values of the present invention.
Can place part to be detected on the table top of worktable of the present invention.Camera is installed in table top top 20 to 80 centimeters of worktable, to obtain part image and to send to computing machine by USB interface.Computing machine is connected to input/output module by communication converter.Communication converter is realized the mutual conversion of signal between the RS485 interface of the USB interface of computing machine and input/output module.Input/output module is an intelligent object that contains multi-way switching values control, and its inside is that a group relay is used for to audible-visual annunciator output control signal.Audible-visual annunciator is connected with input/output module, receives the control signal that it sends.Audible-visual annunciator includes green, blueness, red led and hummer.
As shown in Figure 1, automatically search camera and communication converter behind the computer booting, the driver that the operating system Automatically invoked carries, and provide api interface for user application.The usb communication interface foundation of computing machine by WINDOWS is connected with camera with communication converter and is connected, and the table surface Image Saving of not placing part to be detected that camera is captured is in computing machine.After above-mentioned preliminary work was finished, computing machine sent instruction to input/output module by communication converter, allows input/output module light the green indicating lamp of audible-visual annunciator, represents that whole device enters holding state.
As shown in Figure 2, computing machine can obtain the image of table surface by camera every ten seconds when standby, and carries out image recognition, if image is the image that comprises the table surface of part to be detected, then automatically preserves.Otherwise continue to obtain image.After part to be detected was put on the worktable, whole device entered detected state.Computing machine carries out image recognition according to the image that obtains to each machining area of part to be detected.Image recognition is that the image of part to be detected and the image that is stored in the normal part in the computing machine are compared, if part is normal, computing machine sends instruction by communication controler to input/output module, allows input/output module light the blue indicator light of audible-visual annunciator and closes green indicating lamp.Computing machine continues to obtain by camera every ten seconds the image of table surface, and carry out image recognition, to judge whether normal part to be detected has shifted out worktable, forbid simultaneously other operations, after shifting out worktable, it sends again the blue indicator light that audible-visual annunciator is closed in instruction.If unusual through image recognition part to be detected, computing machine sends instruction by communication controler to input/output module, allow input/output module light the red led of audible-visual annunciator and send the buzzing chimes of doom, this moment, whole device entered alarm condition, need to operate manually computing machine and could eliminate alarm condition, get back to holding state.
Claims (4)
1. the automatic detection device based on image recognition technology is characterized in that, comprising: worktable, camera, computing machine, communication converter, audible-visual annunciator and input/output module;
Worktable is installed part to be detected, and camera obtains part image and sends to computing machine, and computing machine is connected to input/output module by communication converter, and input/output module is connected to audible-visual annunciator.
2. the automatic detection device based on image recognition technology according to claim 1 is characterized in that: the mutual conversion between described communication converter realization USB and the RS485 interface.
3. the automatic detection device based on image recognition technology according to claim 1, it is characterized in that: described audible-visual annunciator is comprised of pilot lamp and hummer.
4. the automatic testing method based on image recognition technology is characterized in that, may further comprise the steps:
1) computer booting self check peripherals detects the camera and the communication converter that have connected automatically, the driver that the operating system Automatically invoked carries, and provide api interface for user application;
2) start user application, application program is set up and being connected of camera by DLL (dynamic link library), and the communication interface foundation that carries by operating system is connected with communication converter;
3) computing machine sends order by communication converter, allows the input/output module point give a green light;
4) computing machine enters holding state, and it obtains view data and constantly refreshing by camera, determines that by pattern recognition part to be detected puts into worktable, and camera obtains image and the autostore of part to be detected;
5) part image to be detected of storing in the step 4) carries out image recognition in computing machine, when part to be detected is normal, computing machine sends instruction by communication converter, allow input/output module light blue indicator light, the continuous cycle detection image of simultaneous computer, wait for that complete after testing part to be detected shifts out worktable and closes blue indicator light again, computing machine comes back to holding state;
6) if the part to be detected that detects in the step 5) is unusual, computing machine sends instruction by communication converter, allows input/output module light red led, and input/output module guide sound light crossing-signal sends buzzing warning and continuous flashing indicator light simultaneously;
7) report to the police after, manually remove the part to be detected on the worktable, and manually eliminate the alerting signal of audible-visual annunciator, and be holding state with computer installation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN2012105093361A CN103018254A (en) | 2012-12-04 | 2012-12-04 | Automatic detection device based on image identification technology |
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| CN2012105093361A CN103018254A (en) | 2012-12-04 | 2012-12-04 | Automatic detection device based on image identification technology |
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| CN103018254A true CN103018254A (en) | 2013-04-03 |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107367513A (en) * | 2017-08-03 | 2017-11-21 | 朱林清 | Workpiece, defect on-line analysis device |
| CN107437248A (en) * | 2017-08-04 | 2017-12-05 | 陈思 | A kind of method of smart fields detection textile product quality |
| CN107525809A (en) * | 2017-08-03 | 2017-12-29 | 朱林清 | A kind of method using the on-line automatic analysis workpiece, defect of wireless communication technology |
| CN108053399A (en) * | 2017-08-08 | 2018-05-18 | 卜风雷 | Real-time pattern identifying system |
| CN109521015A (en) * | 2018-10-31 | 2019-03-26 | 上海沪工汽车电器有限公司 | Automobile fuse box visual identity detection system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102175701A (en) * | 2011-02-11 | 2011-09-07 | 王慧斌 | System and method for online flaw detection of industrial X-ray machine |
| CN202119720U (en) * | 2011-05-30 | 2012-01-18 | 上海福耀客车玻璃有限公司 | Automatic detecting system for automobile glass trademarks in moulds |
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2012
- 2012-12-04 CN CN2012105093361A patent/CN103018254A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102175701A (en) * | 2011-02-11 | 2011-09-07 | 王慧斌 | System and method for online flaw detection of industrial X-ray machine |
| CN202119720U (en) * | 2011-05-30 | 2012-01-18 | 上海福耀客车玻璃有限公司 | Automatic detecting system for automobile glass trademarks in moulds |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107367513A (en) * | 2017-08-03 | 2017-11-21 | 朱林清 | Workpiece, defect on-line analysis device |
| CN107525809A (en) * | 2017-08-03 | 2017-12-29 | 朱林清 | A kind of method using the on-line automatic analysis workpiece, defect of wireless communication technology |
| CN108072663A (en) * | 2017-08-03 | 2018-05-25 | 朱林清 | Workpiece, defect on-line analysis device |
| CN107437248A (en) * | 2017-08-04 | 2017-12-05 | 陈思 | A kind of method of smart fields detection textile product quality |
| CN107437248B (en) * | 2017-08-04 | 2018-04-10 | 胡侠 | A kind of method of smart fields detection textile product quality |
| CN108053399A (en) * | 2017-08-08 | 2018-05-18 | 卜风雷 | Real-time pattern identifying system |
| CN108053399B (en) * | 2017-08-08 | 2020-02-11 | 宿州市徽腾知识产权咨询有限公司 | Real-time pattern recognition system |
| CN109521015A (en) * | 2018-10-31 | 2019-03-26 | 上海沪工汽车电器有限公司 | Automobile fuse box visual identity detection system |
| CN109521015B (en) * | 2018-10-31 | 2021-12-14 | 上海沪工汽车电器有限公司 | Visual identification and detection system for automobile fuse box |
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Application publication date: 20130403 |