CN103499590A - Method and system for detecting and screening end defects in circular parts - Google Patents
Method and system for detecting and screening end defects in circular parts Download PDFInfo
- Publication number
- CN103499590A CN103499590A CN201310486574.XA CN201310486574A CN103499590A CN 103499590 A CN103499590 A CN 103499590A CN 201310486574 A CN201310486574 A CN 201310486574A CN 103499590 A CN103499590 A CN 103499590A
- Authority
- CN
- China
- Prior art keywords
- ring
- work pieces
- shaped work
- image
- circle
- 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
Images
Landscapes
- Image Analysis (AREA)
Abstract
The invention relates to a method and a system for detecting and screening end defects in circular parts. The system comprises an optical amplifier, a control computer, a controller, a pneumatic nozzle device, a step motor and a conveyor belt. The method includes the steps of 1, photographing a circular part to be detected by the optical amplifier to obtain an optically amplifier image of the end of the circular part to be detected; 2, subjecting the optically amplified image to image processing and defect recognition by the control computer, and judging whether the circular part is qualified or not according to defect conditions; 3, allowing the controller to receive a command of controlling the computer, control the pneumatic nozzle device to operate, remove unqualified parts, and control the conveyor belt to convey next part to a detection position. The method and the system have the advantages that end defects in circular parts can be reflected truly, whether an object is qualified or not can be judged accurately, automation level is high, and detection efficiency is improved.
Description
Technical field
The present invention relates to technical field of image processing, particularly a kind ofly can carry out to the small-size annular part method and system of end face defect detection and screening.
Background technology
Be less than the small-size annular part of 5 millimeters for outer ring diameter, in order to guarantee product quality, must micro-damaged (as fine crack, micro-breakage) of its end face be detected.The surface damage of such part detects the main human eye visual detection that relies at present, due to impacts such as examinate person's technology, experience, working environment and asthenopias, be easy to occur flase drop and undetected, and artificial visually examine's efficiency is low, lack accuracy and standardization, and stability and reliability are poor.In order to solve the difficult problem that artificial visually examine's work difficulty is large, efficiency is low, loss is high, need to introduce a kind of Automatic Measurement Technique, not only reduce human cost but also can realize the strict control to product quality.
Computer vision technique is relatively ripe at present, there is the plurality of advantages such as noncontact, speed is fast, precision is high, antijamming capability is strong, if computer vision technique is introduced in small-size annular part end face defect detection, can meet well its requirement to reliability and sensitivity, and easy to maintenance.
Summary of the invention
The object of the invention is to overcome the deficiencies in the prior art, a kind of ring-shaped work pieces end face defect detection and screening technique and system are provided, the method and system not only detection accuracy are high, and automaticity is high, and detection efficiency is provided.
For achieving the above object, technical scheme of the present invention is: a kind of ring-shaped work pieces end face defect detection and screening technique comprise the following steps:
(1) by an optical amplification device, ring-shaped work pieces to be checked is taken, obtained the optical amplifier image of ring-shaped work pieces end face to be checked;
(2) read described optical amplifier image by a control computing machine, described optical amplifier image is carried out to image processing and damaged identification, then judge that according to damaged situation whether ring-shaped work pieces is qualified, and result of determination is sent to the communication port of described control computing machine with command forms;
(3) by a controller, receive the order of the communication port of described control computing machine, if ring-shaped work pieces is defective, described controller is controlled the work of spray nozzle of atmospheric pressure device, by this ring-shaped work pieces travelling belt that blows off, then the control step motor drags travelling belt and next one ring-shaped work pieces to be checked is sent to the detection position of optical amplification device, enters next round and detects and screening process.
Further, in step (1), described optical amplification device employing industrial camera and stereomicroscope are combined, need to obtain the particularly optical amplifier image of large multiple of ring-shaped work pieces different multiples to be checked according to scene.
Further, in step (2), described optical amplifier image is carried out to the image processing and damaged identification comprises the following steps:
(2.1) construct linear smoothing filter described optical amplifier image is carried out to filtering, remove the sharpen detail in radio-frequency component and image; Described linear smoothing wave filter adopts the local mean value computing, the weights displacement of all values in its local neighborhood for each grey scale pixel value, and computing formula is:
Wherein, M is the pixel sum in neighborhood N, h[i, j] be the gray-scale value of pixel after filtering [i, j], f[k, l] be the gray-scale value of the neighborhood territory pixel point of filtering preceding pixel point [k, l];
(2.2) adopt the threshold value process of iteration to carry out image binaryzation first to filtered image, combining image morphology operations wiping out background information, obtain the annulus profile of desirable ring-shaped work pieces; Described threshold value process of iteration is as follows:
(2.2.1) select the estimated value T(of an initial approximation threshold value can adopt the gradation of image average as initial value);
(2.2.2) utilize estimated value T that image is divided into to two groups of zone R according to gray-scale value
1and R
2;
(2.2.3) zoning R
1and R
2gray average μ
1and μ
2;
(2.2.4) according to formula T=(μ
1+ μ
2new estimated value T is calculated and selected in)/2;
(2.2.5) repeating step (2.2.2)-(2.2.4), continuous iterative computation estimated value T, until (μ
1+ μ
2the value of)/2 no longer changes;
In order to obtain desirable annulus profile, can select threshold value according to field condition is that (0.5 ~ 1) T is converted into bianry image by image, is partitioned into the doughnut picture;
(2.3) adopt the boundary scan method to obtain the cylindrical border dot information of ring-shaped work pieces, and by central coordinate of circle and the radius of least square fitting cylindrical; Described boundary scan method is as follows:
(2.3.1) any outside the selection circle, as scan start point, by horizontal and vertical scanning, until obtain first point on cylindrical border, judges whether this point is the point on cylindrical simultaneously;
(2.3.2) use this initial point as boundary tracking, according to boundary connected, obtain cylindrical border dot information by the certain orientation pointwise and preserve with matrix form;
Described least square fitting cylindrical is specially:
Read the cylindrical border dot information (circular arc or circle) scanned, by round equation, calculate corresponding parameter, the equation of circle is:
(?x?-?x
c)
2?+?(?y?–?y
c)
2?=?radius
2
Wherein, (x
c, y
c) be the center of circle, radius is radius of a circle, launches to obtain:
x
2+?y
2?+?ax?+?by?+?c?=?0
Wherein, a=-2x
c, b=-2y
c, c=x
c 2+ y
c 2-radius
2, adopt least square method calculating parameter a, b, the c of curve, according to formula:
Calculate data a, b, c, thereby try to achieve round central coordinate of circle (x
c, y
c), radius r adius is:
x
c=?-?a/2；
y
c=?-?b/2；
(2.4) select the center of circle as scan start point, adopt the boundary scan method described in step (2.3) to obtain the inner circle border dot information of ring-shaped work pieces, and pass through radius of a circle in least square fitting;
(2.5) the filtered image of read step (2.1) again, the central coordinate of circle of the ring-shaped work pieces obtained according to step (2.3), (2.4), exradius and interior radius of circle, remove cylindrical border, the inner circle boundary information of background and ring-shaped work pieces, the complete defect that is partitioned into annulus inside;
(2.6) image step (2.5) is partitioned into is processed, adopt the described threshold value process of iteration of step (2.2) to carry out image binaryzation for the second time, after obtaining binary image, for the damaged feature of difference, take suitable structural element to carry out morphology operations, finally defect area is filled and zone marker;
(2.7) calculate the defect area pixel point areas, choose damaged larger several zones and judged, the size of calculating respectively the minimum boundary rectangle of zones of different judges that with the size that calculates zones of different whether ring-shaped work pieces to be checked is qualified.
The present invention also provides a kind of ring-shaped work pieces end face defect detection and screening system, comprise optical amplification device, control computing machine, controller, spray nozzle of atmospheric pressure device, stepper motor and can travelling belt driven by stepper motors, described control computing machine is connected with controller with described optical amplification device respectively, described optical amplification device is placed in directly over travelling belt, and described controller is connected with the air pressure spray nozzle device with described stepper motor respectively.
Further, described optical amplification device comprises industrial camera and stereomicroscope, and described stereomicroscope is equipped with the LED circular lamp.
Further, if ring-shaped work pieces is defective, described control computing machine sends product and rejects order, after described controller receives order, controls the spray nozzle of atmospheric pressure device and starts, and by the ring-shaped work pieces travelling belt that blows off, if ring-shaped work pieces is qualified, the spray nozzle of atmospheric pressure device does not start; Then, described controller control step motor operation, be sent to detection position by travelling belt by next one ring-shaped work pieces to be checked, enters next round and detect and screening process.
Compared to prior art, the invention has the beneficial effects as follows: the mode that adopts computer vision and micro-vision technology to combine, end face defect detection and the screening of small-size annular part have been realized, solved small size ring-shape accessory (diameter is less than 5mm) end face defect detection difficulty, and the algorithm calculated amount is large, detection speed waits problem slowly, the end face defect information that can truly reflect ring-shaped work pieces, and can accurately judge that whether detected object is qualified, and data volume is little, detection efficiency is high, has very strong practicality and wide application prospect.
Below in conjunction with drawings and the specific embodiments, the present invention is described in further detail.
The accompanying drawing explanation
Fig. 1 carries out the workflow diagram of image processing and damaged identification to the optical amplifier image in the embodiment of the present invention.
Fig. 2 is the system architecture schematic diagram of the embodiment of the present invention.
Embodiment
The invention provides a kind of ring-shaped work pieces end face defect detection and screening technique, comprise the following steps:
(1) by an optical amplification device, ring-shaped work pieces to be checked is taken, obtained the optical amplifier image of ring-shaped work pieces end face to be checked;
(2) read described optical amplifier image by a control computing machine, described optical amplifier image is carried out to image processing and damaged identification, comprise that image filtering, threshold value iteration, image binaryzation, morphology operations, image are cut apart, damaged identification etc., then judge that according to damaged situation whether ring-shaped work pieces is qualified, and result of determination is sent to the communication port of described control computing machine with command forms;
(3) by a controller, receive the order of the communication port of described control computing machine, if ring-shaped work pieces is defective, described controller is controlled the work of spray nozzle of atmospheric pressure device, by this ring-shaped work pieces travelling belt that blows off, then the control step motor drags travelling belt and next one ring-shaped work pieces to be checked is sent to the detection position of optical amplification device, enters next round and detects and screening process.
In step (1), described optical amplification device employing industrial camera and stereomicroscope are combined, need to obtain the particularly optical amplifier image of large multiple (7 ~ 90 times) of ring-shaped work pieces different multiples to be checked according to scene, can obtain the end face defect information of miniature toroidal part authentic and validly, be convenient to observe and differentiate, greatly improved measuring accuracy.
As shown in Figure 1, in step (2), described optical amplifier image is carried out to the image processing and damaged identification comprises the following steps:
(2.1) construct linear smoothing filter described optical amplifier image is carried out to filtering, remove the sharpen detail in radio-frequency component and image; Described linear smoothing wave filter adopts the local mean value computing, the weights displacement of all values in its local neighborhood for each grey scale pixel value, and computing formula is:
Wherein, M is the pixel sum in neighborhood N, h[i, j] be the gray-scale value of pixel after filtering [i, j], f[k, l] be the gray-scale value of the neighborhood territory pixel point of filtering preceding pixel point [k, l]; For example, at pixel [i, j], locate to get 3 * 3 neighborhoods, obtain:
The linear smoothing wave filter can be removed the sharpen detail in radio-frequency component and image, and the present invention adopts the smoothing filter of 3 * 3 use, and its Weight template is as follows:
(2.2) adopt the threshold value process of iteration to carry out image binaryzation first to filtered image, combining image morphology operations wiping out background information, obtain the annulus profile of desirable ring-shaped work pieces; Described threshold value process of iteration is as follows:
(2.2.1) select the estimated value T(of an initial approximation threshold value can adopt the gradation of image average as initial value);
(2.2.2) utilize estimated value T whether image is greater than to T according to gray-scale value and be divided into two groups of zone R
1and R
2;
(2.2.3) zoning R
1and R
2gray average μ
1and μ
2;
(2.2.4) according to formula T=(μ
1+ μ
2new estimated value T is calculated and selected in)/2;
(2.2.5) repeating step (2.2.2)-(2.2.4), continuous iterative computation estimated value T, until (μ
1+ μ
2the value of)/2 no longer changes;
In order to obtain desirable annulus profile, can select threshold value according to field condition is that (0.5 ~ 1) T is converted into bianry image by image, is partitioned into the doughnut picture;
(2.3) adopt the boundary scan method to obtain the cylindrical border dot information of ring-shaped work pieces, and by central coordinate of circle and the radius of least square fitting cylindrical; Described boundary scan method is as follows:
(2.3.1) any outside the selection circle, as scan start point, by horizontal and vertical scanning, until obtain first point on cylindrical border, judges whether this point is the point on cylindrical simultaneously;
(2.3.2) use this initial point as boundary tracking, according to boundary connected, obtain cylindrical border dot information by the certain orientation pointwise and preserve with matrix form; In this program, it is 8 connected relations that connected relation is set, and the boundary tracking path is 8 paths, for the result that makes to obtain is accurate as far as possible, should utilize as much as possiblely as frontier point, and the number of frontier point can be selected optimum number by experiment;
Described least square fitting cylindrical is specially:
Read the cylindrical border dot information scanned, by round equation, calculate corresponding parameter, the equation of circle is:
(?x?-?x
c)
2?+?(?y?–?y
c)
2?=?radius
2
Wherein, (x
c, y
c) be the center of circle, radius is radius of a circle, launches to obtain:
x
2+?y
2?+?ax?+?by?+?c?=?0
Wherein, a=-2x
c, b=-2y
c, c=x
c 2+ y
c 2-radius
2, adopt least square method calculating parameter a, b, the c of curve, according to formula:
Calculate data a, b, c, thereby try to achieve round central coordinate of circle (x
c, y
c), radius r adius is:
x
c=?-?a/2；
y
c=?-?b/2；
The algorithm of the scanning fitting circle that the present invention adopts is less to the annulus position limitation, only requires the annulus position can complete round matching in the orientation, visual field of micro-vision;
(2.4) select the center of circle as scan start point, adopt the boundary scan method described in step (2.3) to obtain the inner circle border dot information of ring-shaped work pieces, and pass through radius of a circle in least square fitting;
(2.5) the filtered image of read step (2.1) again, the central coordinate of circle of the ring-shaped work pieces obtained according to step (2.3), (2.4), exradius and interior radius of circle, remove cylindrical border, the inner circle boundary information of background (background refers to the zone of other than ring type part) and ring-shaped work pieces, the complete defect that is partitioned into annulus inside, the border of annulus cylindrical and inner circle is also removed, only stayed the part zone between inside and outside circle;
(2.6) image step (2.5) is partitioned into is processed, adopt the described threshold value process of iteration of step (2.2) to carry out image binaryzation for the second time, after obtaining binary image, for the damaged feature of difference, take suitable structural element (as planar rectangular structural element, circular planar disk-like structural element) to carry out morphology operations, finally defect area is filled and zone marker;
(2.7) calculate the defect area pixel point areas, choose damaged larger several zones and judged, the size of calculating respectively the minimum boundary rectangle of zones of different judges that with the size that calculates zones of different whether ring-shaped work pieces to be checked is qualified.
As shown in Figure 2, the present invention also provides a kind of ring-shaped work pieces end face defect detection and screening system, comprise optical amplification device, control computing machine 1, controller 9, spray nozzle of atmospheric pressure device 8, stepper motor 5 and the travelling belt 6 that can be driven by stepper motor 5, described control computing machine 1 is connected with controller 9 with described optical amplification device respectively, described optical amplification device is placed in directly over travelling belt 6 and ring-shaped work pieces 7 to be checked, and described controller 9 is connected with air pressure spray nozzle device 8 with described stepper motor 5 respectively.
In the present embodiment, described optical amplification device comprises industrial camera 2 and stereomicroscope 3, described stereomicroscope 3 is equipped with LED circular lamp 4, the enlargement factor of stereomicroscope is 7 ~ 90 times, utilize this device can effectively obtain the end face defect information of miniature toroidal part, be convenient to observe and differentiate, greatly improved measuring accuracy.
If ring-shaped work pieces is defective, described control computing machine sends product and rejects order, after described controller receives order, controls the spray nozzle of atmospheric pressure device and starts, and by the ring-shaped work pieces travelling belt that blows off, if ring-shaped work pieces is qualified, the spray nozzle of atmospheric pressure device does not start; Then, described controller control step motor operation, be sent to detection position by travelling belt by next one ring-shaped work pieces to be checked, enters next round and detect and screening process.
Be more than preferred embodiment of the present invention, all changes of doing according to technical solution of the present invention, when the function produced does not exceed the scope of technical solution of the present invention, all belong to protection scope of the present invention.
Claims (6)
1. a ring-shaped work pieces end face defect detection and screening technique, is characterized in that, comprises the following steps:
(1) by an optical amplification device, ring-shaped work pieces to be checked is taken, obtained the optical amplifier image of ring-shaped work pieces end face to be checked;
(2) read described optical amplifier image by a control computing machine, described optical amplifier image is carried out to image processing and damaged identification, then judge that according to damaged situation whether ring-shaped work pieces is qualified, and result of determination is sent to the communication port of described control computing machine with command forms;
(3) by a controller, receive the order of the communication port of described control computing machine, if ring-shaped work pieces is defective, described controller is controlled the work of spray nozzle of atmospheric pressure device, by this ring-shaped work pieces travelling belt that blows off, then the control step motor drags travelling belt and next one ring-shaped work pieces to be checked is sent to the detection position of optical amplification device, enters next round and detects and screening process.
2. ring-shaped work pieces end face defect detection according to claim 1 and screening technique, it is characterized in that, in step (1), described optical amplification device employing industrial camera and stereomicroscope are combined, need to obtain the particularly optical amplifier image of large multiple of ring-shaped work pieces different multiples to be checked according to scene.
3. ring-shaped work pieces end face defect detection according to claim 1 and screening technique, is characterized in that, in step (2), described optical amplifier image carried out to the image processing and damaged identification comprises the following steps:
(2.1) construct linear smoothing filter described optical amplifier image is carried out to filtering, remove the sharpen detail in radio-frequency component and image; Described linear smoothing wave filter adopts the local mean value computing, the weights displacement of all values in its local neighborhood for each grey scale pixel value, and computing formula is:
Wherein, M is the pixel sum in neighborhood N, h[i, j] be the gray-scale value of pixel after filtering [i, j], f[k, l] be the gray-scale value of the neighborhood territory pixel point of filtering preceding pixel point [k, l];
(2.2) adopt the threshold value process of iteration to carry out image binaryzation first to filtered image, combining image morphology operations wiping out background information, obtain the annulus profile of ring-shaped work pieces accurately; Described threshold value process of iteration is as follows:
(2.2.1) select the estimated value T of an initial approximation threshold value;
(2.2.2) utilize estimated value T whether image is greater than to T according to gray-scale value and be divided into two groups of zone R
1and R
2;
(2.2.3) zoning R
1and R
2gray average μ
1and μ
2;
(2.2.4) according to formula T=(μ
1+ μ
2new estimated value T is calculated and selected in)/2;
(2.2.5) repeating step (2.2.2)-(2.2.4), continuous iterative computation estimated value T, until (μ
1+ μ
2the value of)/2 no longer changes;
In order to obtain annulus profile accurately, select threshold value, for (0.5 ~ 1) T, image is converted into to bianry image, be partitioned into the doughnut picture;
(2.3) adopt the boundary scan method to obtain the cylindrical border dot information of ring-shaped work pieces, and by central coordinate of circle and the radius of least square fitting cylindrical; Described boundary scan method is as follows:
(2.3.1) any outside the selection circle, as scan start point, by horizontal and vertical scanning, until obtain first point on cylindrical border, judges whether this point is the point on cylindrical simultaneously;
(2.3.2) use this initial point as boundary tracking, according to boundary connected, obtain cylindrical border dot information by the certain orientation pointwise and preserve with matrix form;
Described least square fitting cylindrical is specially:
Read the cylindrical border dot information scanned, by round equation, calculate corresponding parameter, the equation of circle is:
(?x?-?x
c)
2?+?(?y?–?y
c)
2?=?radius
2
Wherein, (x
c, y
c) be the center of circle, radius is radius of a circle, launches to obtain:
x
2+?y
2?+?ax?+?by?+?c?=?0
Wherein, a=-2x
c, b=-2y
c, c=x
c 2+ y
c 2-radius
2, adopt least square method calculating parameter a, b, the c of curve, according to formula:
Calculate data a, b, c, thereby try to achieve round central coordinate of circle (x
c, y
c), radius r adius is:
x
c=?-?a/2；
y
c=?-?b/2；
(2.4) select the center of circle as scan start point, adopt the boundary scan method described in step (2.3) to obtain the inner circle border dot information of ring-shaped work pieces, and pass through radius of a circle in least square fitting;
(2.5) the filtered image of read step (2.1) again, the central coordinate of circle of the ring-shaped work pieces obtained according to step (2.3), (2.4), exradius and interior radius of circle, remove cylindrical border, the inner circle boundary information of background and ring-shaped work pieces, the complete defect that is partitioned into annulus inside;
(2.6) image step (2.5) is partitioned into is processed, adopt the described threshold value process of iteration of step (2.2) to carry out image binaryzation for the second time, after obtaining binary image, for the damaged feature of difference, take suitable structural element to carry out morphology operations, finally defect area is filled and zone marker;
(2.7) calculate the defect area pixel point areas, choose damaged larger several zones and judged, the size of calculating respectively the minimum boundary rectangle of zones of different judges that with the size that calculates zones of different whether ring-shaped work pieces to be checked is qualified.
4. one kind adopts ring-shaped work pieces end face defect detection and the screening system of method as claimed in claim 1, it is characterized in that, comprise optical amplification device, control computing machine, controller, spray nozzle of atmospheric pressure device, stepper motor and can travelling belt driven by stepper motors, described control computing machine is connected with controller with described optical amplification device respectively, described optical amplification device is placed in directly over travelling belt, and described controller is connected with the air pressure spray nozzle device with described stepper motor respectively.
5. ring-shaped work pieces end face defect detection according to claim 4 and screening system, is characterized in that, described optical amplification device comprises industrial camera and stereomicroscope, and described stereomicroscope is equipped with the LED circular lamp.
6. ring-shaped work pieces end face defect detection according to claim 4 and screening system, it is characterized in that, if ring-shaped work pieces is defective, described control computing machine sends product and rejects order, after described controller receives order, control the spray nozzle of atmospheric pressure device and start, by the ring-shaped work pieces travelling belt that blows off, if ring-shaped work pieces is qualified, the spray nozzle of atmospheric pressure device does not start; Then, described controller control step motor operation, be sent to detection position by travelling belt by next one ring-shaped work pieces to be checked, enters next round and detect and screening process.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310486574.XA CN103499590B (en) | 2013-10-17 | 2013-10-17 | Ring-shaped work pieces end face defect detection and screening technique and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310486574.XA CN103499590B (en) | 2013-10-17 | 2013-10-17 | Ring-shaped work pieces end face defect detection and screening technique and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103499590A true CN103499590A (en) | 2014-01-08 |
| CN103499590B CN103499590B (en) | 2015-11-18 |
Family
ID=49864819
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310486574.XA Active CN103499590B (en) | 2013-10-17 | 2013-10-17 | Ring-shaped work pieces end face defect detection and screening technique and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103499590B (en) |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104390589A (en) * | 2014-11-20 | 2015-03-04 | 景德镇陶瓷学院 | Anti-dazzle circular daily ceramic device applique out-of-bound detection method |
| CN105092577A (en) * | 2015-05-15 | 2015-11-25 | 浙江工业大学 | Holder positive and negative side distinguishing device |
| CN105548192A (en) * | 2016-02-15 | 2016-05-04 | 无锡速博威迅科技有限公司 | Automatic detection equipment of direct-current shutter |
| CN107315012A (en) * | 2017-06-22 | 2017-11-03 | 福建省万龙新材料科技有限公司 | Composite polycrystal-diamond end face collapses the intelligent detecting method at angle |
| CN107703150A (en) * | 2017-11-01 | 2018-02-16 | 南昌航空大学 | A kind of detection method and detecting system of head portion that defect |
| CN108596909A (en) * | 2018-05-09 | 2018-09-28 | 芜湖哈特机器人产业技术研究院有限公司 | Hollow cylinder Surface Flaw Detection system and method |
| CN109187581A (en) * | 2018-07-12 | 2019-01-11 | 中国科学院自动化研究所 | The bearing finished products plate defects detection method of view-based access control model |
| CN109325930A (en) * | 2018-09-12 | 2019-02-12 | 苏州优纳科技有限公司 | Detection method, device and the detection device of boundary defect |
| CN110989587A (en) * | 2019-11-29 | 2020-04-10 | 龙铁纵横（北京）轨道交通科技股份有限公司 | Intelligent robot fastening control system and method |
| CN111337510A (en) * | 2020-04-20 | 2020-06-26 | 南通大学 | Detection device for lack of fastening buckle of automobile plastic assembly and working method |
| CN114998311A (en) * | 2022-07-11 | 2022-09-02 | 江苏名欧精密机械有限公司 | Part precision detection method based on homomorphic filtering |
| WO2022222467A1 (en) * | 2021-04-22 | 2022-10-27 | 苏州华兴源创科技股份有限公司 | Open circular ring workpiece appearance defect detection method and system, and computer storage medium |
| CN115861315A (en) * | 2023-02-27 | 2023-03-28 | 常州微亿智造科技有限公司 | Defect detection method and device |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH09210656A (en) * | 1995-11-28 | 1997-08-12 | Nikon Corp | Inspection system |
| CN102411007A (en) * | 2011-08-08 | 2012-04-11 | 长春理工大学 | Surface defect detection system for tiny circular or circular ring-shaped parts |
-
2013
- 2013-10-17 CN CN201310486574.XA patent/CN103499590B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH09210656A (en) * | 1995-11-28 | 1997-08-12 | Nikon Corp | Inspection system |
| CN102411007A (en) * | 2011-08-08 | 2012-04-11 | 长春理工大学 | Surface defect detection system for tiny circular or circular ring-shaped parts |
Non-Patent Citations (3)
| Title |
|---|
| 何学科，龙赛琼: "基于计算机视觉技术的小尺寸机械零件的尺寸测量系统研究", 《湘潭师范学院学报》 * |
| 刘科文等: "基于机器视觉的圆环形零件形位尺寸自动测量", 《工业控制计算机》 * |
| 朱晓林等: "机械零件二维几何特征视觉检测系统研究与开发", 《中国工程机械学报》 * |
Cited By (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104390589B (en) * | 2014-11-20 | 2017-02-22 | 景德镇陶瓷大学 | Anti-dazzle circular daily ceramic device applique out-of-bound detection method |
| CN104390589A (en) * | 2014-11-20 | 2015-03-04 | 景德镇陶瓷学院 | Anti-dazzle circular daily ceramic device applique out-of-bound detection method |
| CN105092577A (en) * | 2015-05-15 | 2015-11-25 | 浙江工业大学 | Holder positive and negative side distinguishing device |
| CN105092577B (en) * | 2015-05-15 | 2017-08-01 | 浙江工业大学 | A kind of retainer positive and negative discriminating gear |
| CN105548192A (en) * | 2016-02-15 | 2016-05-04 | 无锡速博威迅科技有限公司 | Automatic detection equipment of direct-current shutter |
| CN105548192B (en) * | 2016-02-15 | 2018-03-06 | 无锡速博威迅科技有限公司 | A kind of automatic detection system of direct current shutter |
| CN107315012B (en) * | 2017-06-22 | 2019-10-18 | 福建省万龙新材料科技有限公司 | Composite polycrystal-diamond end face collapses the intelligent detecting method at angle |
| CN107315012A (en) * | 2017-06-22 | 2017-11-03 | 福建省万龙新材料科技有限公司 | Composite polycrystal-diamond end face collapses the intelligent detecting method at angle |
| CN107703150A (en) * | 2017-11-01 | 2018-02-16 | 南昌航空大学 | A kind of detection method and detecting system of head portion that defect |
| CN108596909A (en) * | 2018-05-09 | 2018-09-28 | 芜湖哈特机器人产业技术研究院有限公司 | Hollow cylinder Surface Flaw Detection system and method |
| CN109187581A (en) * | 2018-07-12 | 2019-01-11 | 中国科学院自动化研究所 | The bearing finished products plate defects detection method of view-based access control model |
| CN109325930A (en) * | 2018-09-12 | 2019-02-12 | 苏州优纳科技有限公司 | Detection method, device and the detection device of boundary defect |
| CN110989587A (en) * | 2019-11-29 | 2020-04-10 | 龙铁纵横（北京）轨道交通科技股份有限公司 | Intelligent robot fastening control system and method |
| CN110989587B (en) * | 2019-11-29 | 2023-11-17 | 龙铁纵横（北京）轨道交通科技股份有限公司 | Intelligent fastening control system and method for robot |
| CN111337510A (en) * | 2020-04-20 | 2020-06-26 | 南通大学 | Detection device for lack of fastening buckle of automobile plastic assembly and working method |
| WO2022222467A1 (en) * | 2021-04-22 | 2022-10-27 | 苏州华兴源创科技股份有限公司 | Open circular ring workpiece appearance defect detection method and system, and computer storage medium |
| CN114998311A (en) * | 2022-07-11 | 2022-09-02 | 江苏名欧精密机械有限公司 | Part precision detection method based on homomorphic filtering |
| CN115861315A (en) * | 2023-02-27 | 2023-03-28 | 常州微亿智造科技有限公司 | Defect detection method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103499590B (en) | 2015-11-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103499590A (en) | Method and system for detecting and screening end defects in circular parts | |
| CN109357630B (en) | A kind of polymorphic type batch workpiece vision measurement system and method | |
| CN103604808B (en) | A kind of bottle cap defective vision detection method | |
| CN109900711A (en) | Workpiece, defect detection method based on machine vision | |
| CN105046697B (en) | A kind of beer bottleneck localization method assessed based on multiple random loop truss and degree of fitting | |
| CN103913468B (en) | Many defects of vision checkout equipment and the method for large-scale LCD glass substrate on production line | |
| CN102636490B (en) | Method for detecting surface defects of dustproof cover of bearing based on machine vision | |
| CN108230324B (en) | Visual detection method for microdefect on surface of magnetic shoe | |
| CN101995223B (en) | Chip appearance detection method and system | |
| CN102095733B (en) | Machine vision-based intelligent detection method for surface defect of bottle cap | |
| CN104297255B (en) | A kind of dixie cup defective vision detection method and system and device | |
| CN101858734B (en) | Method for detecting PET bottleneck quality | |
| CN105388162B (en) | Raw material silicon chip surface scratch detection method based on machine vision | |
| CN111982921B (en) | Method and device for detecting hole defects, conveying platform and storage medium | |
| CN106780473B (en) | A kind of magnet ring defect multi-vision visual detection method and system | |
| CN102496161B (en) | Method for extracting contour of image of printed circuit board (PCB) | |
| CN107255641A (en) | A kind of method that Machine Vision Detection is carried out for GRIN Lens surface defect | |
| CN101105459A (en) | Empty bottle mouth defect inspection method and device | |
| CN106643549A (en) | Machine vision-based tile size detection method | |
| CN105783723A (en) | Machine vision-based precise die surface processing precision detection device and method | |
| CN107101598B (en) | Automatic detection method and device for concentricity quality of piezoelectric ceramic silver sheet | |
| CN103645573A (en) | Liquid crystal display (LCD) detection method and system based on machine vision | |
| CN108844961A (en) | A kind of temperature controller case vision detection system and method | |
| CN105954301A (en) | Bottleneck quality detection method based on machine vision | |
| CN112001917A (en) | Machine vision-based geometric tolerance detection method for circular perforated part |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |