CN104316033A - Visual inspection system for automobile parts - Google Patents
Visual inspection system for automobile parts Download PDFInfo
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- CN104316033A CN104316033A CN201410613779.4A CN201410613779A CN104316033A CN 104316033 A CN104316033 A CN 104316033A CN 201410613779 A CN201410613779 A CN 201410613779A CN 104316033 A CN104316033 A CN 104316033A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
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Abstract
The invention discloses a visual inspection system for automobile parts. The visual inspection system comprises an optical imaging system, image acquisition equipment, an image processing system, an intelligent decision judgment mechanism and a control execution mechanism in sequence, wherein the image acquisition equipment and the image processing system are simultaneously connected with a communication and monitoring system; the control execution mechanism controls a detected target object; the intelligent decision judgment mechanism controls a light source. According to the visual inspection system for the automobile parts, an image is used as a measure or a carrier for detecting and transmitting information; various required parameters are acquired by processing the detected image; the visual inspection system for the automobile parts has the advantages of high efficiency, high precision and no damage.
Description
Technical field
The present invention relates to a kind of auto parts and components vision detection system.
Background technology
Various unit check, dimensional measurement and Parts Recognition etc. are often related to, as auto-parts size detection and the integrity checking automatically assembled, the detection of electronic assemblies component defects and Quick Response Code identification etc. in modern automobile industry automated production.The basic skills of current auto parts inspection mainly contains: inspect method, gage measuring method, the method for nondestructive inspection, usually these have been come by naked eyes with high reproducibility and necessarily intelligent work, but at some in particular cases, such as to minute sized accurate Quick Measurement, form fit and color-identifying etc., only rely on naked eyes cannot carry out continuously and stably, and the sensor that other physical quantity is correlated with also is difficult to be competent at all.
Machine vision technique, as an important branch of computer science, had swift and violent development in nearly 30 years.Because Vision Builder for Automated Inspection can carry out data processing by quick obtaining bulk information automatically, be easy to same design information and machining control information integerated, therefore, in modern automation production run, Vision Builder for Automated Inspection is widely used in the fields such as operating condition monitoring, product inspection and quality control.
The feature of Vision Builder for Automated Inspection to improve flexibility and the automaticity of production.Be not suitable at some the occasion that the dangerous work environment of manual work or artificial vision be difficult to meet the demands, machine in normal service vision carrys out alternative artificial vision; In addition, in industrial processes in enormous quantities, check the quality of the products by Vision Builder for Automated Inspection obviously fast than manual type speed, precision is high, and can greatly enhance productivity and production automation degree.In addition, Vision Builder for Automated Inspection is convenient to information integerated, is the basic technology realizing modern industry robotization.
Computer Vision Detection System nearly all at present is all only applicable to solve specific Detection task, and the total class of part on automobile is various, if according to its structure and effect, can be divided into five kinds of fundamental types such as housing, axle, gear, bearing, spring.The concrete planform of all kinds of part is different and damaging features and the method for inspection are all different.Therefore how by the detection of machine vision applications in auto parts, how being embedded in the corresponding operation of production line by vision detection system, making detection speed consistent with production line beat, is key one step that vision-based detection goes on practical application.
Summary of the invention
Goal of the invention: in order to solve the problems of the technologies described above, the invention provides a kind of auto parts and components vision detection system.
Technical scheme: auto parts and components vision detection system of the present invention, comprise optical imaging system, image acquisition equipment, image processing system, intelligent decision decision mechanism successively and control topworks, described image acquisition equipment, image processing system be connecting communication and supervisory system simultaneously; By described control actuating mechanism controls measured target object, control light source by described intelligent decision decision mechanism.
Described optical imaging system comprises light source, optical lens and optical imaging apparatus, according to different tasks and object, needs to select Different Light and optical imaging modalities.
Described image acquisition equipment: mainly comprise CCD type video camera and COMS type video camera, image information collecting device; Complete the collection to view data, and it is converted to the output signal of corresponding form.
Described image processing system: for the calculating of realtime image data and analysis, complete the enhancing to image, segmentation, feature extraction and pattern recognition process.
Described communication and supervisory system: comprise fieldbus, various interface and display module, for carrying out real-time control and monitoring to the duty of whole system.
Described intelligent decision decision mechanism: the data result utilizing systematic analysis, makes judgement promptly and accurately in conjunction with application request.
Described control topworks comprises Mechatronic control system, hydraulic control system or atmospheric control.
Described light source is infrared coaxial annular light source or pointolite.
Beneficial effect: the present invention as to detect and the means of transmission of information or carrier are used, is obtained image required various parameters by process by altimetric image, has efficiently, high precision, undamaged detection advantage.
Accompanying drawing explanation
Fig. 1 is system construction drawing of the present invention.
Embodiment:
Auto parts and components vision detection system of the present invention is a complete vision detection system based on digital image processing techniques, as shown in Figure 1, mainly comprises following components:
(1) optical system: comprise the contents such as light source, optical lens, optical imagery, according to different tasks and object, needs to select Different Light and optical imaging modalities.It is the optics input channel of vision detection system that this pastern divides, and counts for much to the image quality of image.
(2) image acquisition equipment: mainly comprise CCD type video camera and COMS type video camera, image information collecting device etc.Mainly complete the collection to view data, and it is converted to the output signal of corresponding form.
(3) image processing system: the core component of vision detection system, for to the calculating of realtime image data and analysis, mainly complete the process such as the enhancing to image, segmentation, feature extraction and pattern-recognition, wherein software systems algorithm process speed and precision produce directly impact to the real-time of whole system.
(4) communication and supervisory system: comprise fieldbus, various interface and display module etc., for carrying out real-time control and monitoring to the duty of whole system.
(5) intelligent decision decision mechanism: the data result utilizing systematic analysis, makes judgement promptly and accurately in conjunction with application request.
(6) topworks is controlled: the action executing center of vision detection system.According to different application requirements and place needs, one in electromechanics, hydraulic pressure, the system such as pneumatic can be divided into by controlling topworks, no matter work in a certain system, we must give to pay attention to the manufacture assembly precision of parts, also will carry out analysis and control to the dynamic perfromance (rapidity and stability) that equipment runs simultaneously.
Concrete, image acquiring device of the present invention, comprises optical imaging apparatus (as ccd video camera) and image pick-up card etc.Described image storage apparatus can be image pick-up card buffer memory, disk or flash memory etc.Described data processor can be PC, DSP or image processor.In addition, also comprise servomechanism installation, function is to make measured target to be in a stable best shooting state, and objective table is the simplest servomechanism installation of one.Also comprise software systems, be responsible for the function such as the extraction of characteristics of image, the analysis and synthesis of data, software systems are keys of whole detection system, and its processing accuracy and speed directly affect precision and the real-time performance of whole detection system.
First according to optical path and the imaging mode of certain setting in advance, convert the target information collected with ccd video camera and other camera heads to data image signal and send special image processing module to, according to characteristics such as pixel grey scale, spatial domain frequency domain energy distributions, various computing is carried out to these signals and extract clarification of objective parameter, and then differentiate that result controls the action of relevant device according to the permission preset and other output with conditions.
Technology crucial in vision inspection process comprises the following aspects: the demarcation of Image Acquisition, image procossing, High Definition Systems, sub-pixel edge location technology etc.
Image Acquisition: the acquisition of image is actually a series of data visual image of testee and internal characteristics being converted to and can be subsequently can by computer, and it forms primarily of three parts: illumination, figure image focu are formed, image is determined and forms camera signal.This project carrys out outstanding tested auto parts and components feature for the light source that specific application choice is suitable, such as, adopt infrared coaxial annular light source detection Quick Response Code, adopt pointolite detection punch rivet to have the integrality projects such as flawless.
Image procossing: in vision system, the treatment technology of visual information depends on image processing method, and it comprises the contents such as image filtering, image enhaucament, edge extracting, refinement, feature extraction, image recognition and understanding.Corresponding different application (Quick Response Code detection, surface defects detection, the linear measure longimetry etc.) gordian technique had on different image processing algorithms needs to solve.
System calibrating: camera calibration is a process determining transformation relation and intrinsic parameters of the camera and external parameter between three-dimensional body space coordinates and camera review two-dimensional coordinate system, and high-precision measuring system needs high-precision calibrating parameters.Because the camera lens in imaging inevitably produces distortion, also there is image error in the hypothesis of aperture projection model, and finding camera marking method that is simple and enough accuracy, is the key factor of videogrammetry system.
Sub-pixel edge location technology: along with the application such as industrial detection improving constantly accuracy requirement, Pixel-level precision can not meet the requirement of actual measurement, therefore needs more high-precision Boundary extracting algorithm, i.e. sub-pixel recognition.Size detection relevant in project needs to utilize such algorithm, and then utilizes software to improve the precision of detection, and have simple, the effective advantage of method, thus the software algorithm of image measurement is more and more subject to people's attention.
Claims (8)
1. an auto parts and components vision detection system, it is characterized in that comprising optical imaging system, image acquisition equipment, image processing system, intelligent decision decision mechanism successively and controlling topworks, described image acquisition equipment, image processing system be connecting communication and supervisory system simultaneously; Described control actuating mechanism controls measured target object, described intelligent decision decision mechanism controls light source.
2. auto parts and components vision detection system as claimed in claim 1, is characterized in that described optical imaging system comprises light source, optical lens and optical imaging apparatus, according to different tasks and object, needs to select Different Light and optical imaging modalities.
3. auto parts and components vision detection system as claimed in claim 1, it is characterized in that described image acquisition equipment comprises image information collecting device and video camera, described video camera is CCD type video camera or COMS type video camera; Complete the collection to view data, and it is converted to the output signal of corresponding form.
4. auto parts and components vision detection system as claimed in claim 1, is characterized in that described image processing system is for the calculating of realtime image data and analysis, completes the enhancing to image, segmentation, feature extraction and pattern recognition process.
5. auto parts and components vision detection system as claimed in claim 1, is characterized in that described communication and supervisory system comprise fieldbus, interface and display module, for carrying out real-time control and monitoring to the duty of whole system.
6. auto parts and components vision detection system as claimed in claim 1, is characterized in that described intelligent decision decision mechanism utilizes the data result of systematic analysis, makes judgement promptly and accurately in conjunction with application request.
7. auto parts and components vision detection system as claimed in claim 1, is characterized in that described control topworks comprises Mechatronic control system, hydraulic control system or atmospheric control.
8. auto parts and components vision detection system as claimed in claim 1, is characterized in that described light source is infrared coaxial annular light source or pointolite.
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| CN201410613779.4A CN104316033A (en) | 2014-11-04 | 2014-11-04 | Visual inspection system for automobile parts |
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| CN201410613779.4A CN104316033A (en) | 2014-11-04 | 2014-11-04 | Visual inspection system for automobile parts |
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105184276A (en) * | 2015-09-28 | 2015-12-23 | 大连楼兰科技股份有限公司 | Method of recognizing parts during maintenance process by intelligent glasses |
| CN106034218A (en) * | 2015-03-12 | 2016-10-19 | 宁夏巨能机器人系统有限公司 | 2D visual identity device and identification method for automatic production line |
| CN106842351A (en) * | 2017-01-17 | 2017-06-13 | 山东飞越钢结构工程有限公司 | A kind of automated production missing nail detecting system |
| CN107917698A (en) * | 2017-11-07 | 2018-04-17 | 东华大学 | A kind of small articles detecting system based on capacitive displacement transducer and image procossing |
| CN108765375A (en) * | 2018-04-28 | 2018-11-06 | 湖北盛时杰精密机电有限公司 | A kind of monitoring method for auto parts and components test equipment |
| CN109596058A (en) * | 2019-02-01 | 2019-04-09 | 东莞中科蓝海智能视觉科技有限公司 | The size detection recognition methods of plastic workpiece |
| CN110108714A (en) * | 2019-04-28 | 2019-08-09 | 浙江博拉自动化科技有限公司 | A kind of auto parts and components appearance detection system and device |
| CN111707692A (en) * | 2020-07-17 | 2020-09-25 | 碳升技术服务(北京)有限公司 | Defect detection method and system for automobile parts and electronic equipment |
| CN111915604A (en) * | 2020-08-20 | 2020-11-10 | 魏小燕 | Internet artificial intelligence electron accessories discernment and detecting system |
| CN116399871A (en) * | 2023-04-19 | 2023-07-07 | 广州市阳普机电工程有限公司 | Automobile part assembly detection system and method based on machine vision |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5329595A (en) * | 1992-06-05 | 1994-07-12 | Trw Inc. | System and method for analyzing optical spectral data of a terrain image |
| JP2005265699A (en) * | 2004-03-19 | 2005-09-29 | Chugoku Electric Power Co Inc:The | System and method for inspecting power transmission line using unmanned flying body |
| CN202547948U (en) * | 2011-12-30 | 2012-11-21 | 上海一成汽车检测设备科技有限公司 | Dual-three-dimensional (3D) automobile detector |
| CN103808720A (en) * | 2012-11-07 | 2014-05-21 | 孙仁 | Machine vision system |
| CN103823454A (en) * | 2014-03-12 | 2014-05-28 | 黄昱俊 | System and method for inquiring and locating books based on machine vision |
| CN203672319U (en) * | 2013-11-08 | 2014-06-25 | 宁波敏实汽车零部件技术研发有限公司 | Automation equipment for visual inspection of large-scale automobile parts |
-
2014
- 2014-11-04 CN CN201410613779.4A patent/CN104316033A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5329595A (en) * | 1992-06-05 | 1994-07-12 | Trw Inc. | System and method for analyzing optical spectral data of a terrain image |
| JP2005265699A (en) * | 2004-03-19 | 2005-09-29 | Chugoku Electric Power Co Inc:The | System and method for inspecting power transmission line using unmanned flying body |
| CN202547948U (en) * | 2011-12-30 | 2012-11-21 | 上海一成汽车检测设备科技有限公司 | Dual-three-dimensional (3D) automobile detector |
| CN103808720A (en) * | 2012-11-07 | 2014-05-21 | 孙仁 | Machine vision system |
| CN203672319U (en) * | 2013-11-08 | 2014-06-25 | 宁波敏实汽车零部件技术研发有限公司 | Automation equipment for visual inspection of large-scale automobile parts |
| CN103823454A (en) * | 2014-03-12 | 2014-05-28 | 黄昱俊 | System and method for inquiring and locating books based on machine vision |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106034218A (en) * | 2015-03-12 | 2016-10-19 | 宁夏巨能机器人系统有限公司 | 2D visual identity device and identification method for automatic production line |
| CN105184276A (en) * | 2015-09-28 | 2015-12-23 | 大连楼兰科技股份有限公司 | Method of recognizing parts during maintenance process by intelligent glasses |
| CN105184276B (en) * | 2015-09-28 | 2018-10-19 | 大连楼兰科技股份有限公司 | Parts Recognition method during intelligent glasses maintenance |
| CN106842351A (en) * | 2017-01-17 | 2017-06-13 | 山东飞越钢结构工程有限公司 | A kind of automated production missing nail detecting system |
| CN107917698A (en) * | 2017-11-07 | 2018-04-17 | 东华大学 | A kind of small articles detecting system based on capacitive displacement transducer and image procossing |
| CN108765375A (en) * | 2018-04-28 | 2018-11-06 | 湖北盛时杰精密机电有限公司 | A kind of monitoring method for auto parts and components test equipment |
| CN109596058A (en) * | 2019-02-01 | 2019-04-09 | 东莞中科蓝海智能视觉科技有限公司 | The size detection recognition methods of plastic workpiece |
| CN110108714A (en) * | 2019-04-28 | 2019-08-09 | 浙江博拉自动化科技有限公司 | A kind of auto parts and components appearance detection system and device |
| CN111707692A (en) * | 2020-07-17 | 2020-09-25 | 碳升技术服务(北京)有限公司 | Defect detection method and system for automobile parts and electronic equipment |
| CN111915604A (en) * | 2020-08-20 | 2020-11-10 | 魏小燕 | Internet artificial intelligence electron accessories discernment and detecting system |
| CN116399871A (en) * | 2023-04-19 | 2023-07-07 | 广州市阳普机电工程有限公司 | Automobile part assembly detection system and method based on machine vision |
| CN116399871B (en) * | 2023-04-19 | 2023-11-14 | 广州市阳普机电工程有限公司 | Automobile part assembly detection system and method based on machine vision |
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