CN102303017B - Method for automatically detecting bending of injector steel needles by using machine vision system - Google Patents
Method for automatically detecting bending of injector steel needles by using machine vision system Download PDFInfo
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- CN102303017B CN102303017B CN 201110109619 CN201110109619A CN102303017B CN 102303017 B CN102303017 B CN 102303017B CN 201110109619 CN201110109619 CN 201110109619 CN 201110109619 A CN201110109619 A CN 201110109619A CN 102303017 B CN102303017 B CN 102303017B
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- 238000001514 detection method Methods 0.000 claims abstract description 34
- 239000002699 waste material Substances 0.000 claims abstract description 9
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- 238000004519 manufacturing process Methods 0.000 claims description 15
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- 239000011521 glass Substances 0.000 description 2
- 238000009499 grossing Methods 0.000 description 2
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Abstract
The invention provides a method for automatically detecting the bending of injector steel needles by using a machine vision system. The method comprises the following steps of: setting transverse bending values of needle points of the steel needles to be detection parameters; setting detection accuracy and qualified ranges of different detection parameters according to requirements of users; starting a camera by using external trigger and control signals to shoot pictures of the steel needles operated on line in real time, and transmitting the shot pictures to a computer for detection; processing the pictures by using the computer by a picture algorithm; extracting the pictures in which the steel needles are bent, and computing the transverse bending values of two bending needles; and judging whether a product is a qualified product or a waste product through the computed transverse bending values, and eliminating the waste product from a specified material outlet through the external trigger and control signals. By the method, the injector steel needles can be detected at high accuracy and high speed, and the yield of the product can be effectively ensured.
Description
Technical field
The present invention relates to utilize NI Vision Builder for Automated Inspection to carry out the technical field of online detection, relate in particular to, utilize NI Vision Builder for Automated Inspection the syringe draw point method whether looper detects automatically in syringe draw point production scene.
Background technology
Syringe draw point assembly shop in continuous productive process is on-the-spot, need carry out online detection to draw point looper (being whether the draw point needle point exists bending).In the prior art; Online detection to the draw point looper relies on the special-purpose magnifying glass of artificial use to detect; Produce the machine side at draw point and establish detection and the processing that about 80 people carry out the draw point looper; According to testing result with product be divided into certified products (like transverse curvature value＜0.05mm, the interior curved transverse curvature value＜0.05mm of excurvation or do not have looper) and defective work (like the transverse curvature value >=0.05mm of excurvation, or interior curved transverse curvature value >=0.05mm).Defective work is directly as goods rejection.
The shortcoming that manual detection exists mainly contains: the on-the-spot ventilation of workshop is poor, and workman's testing environment is abominable, can't directly use range estimation (needing use special-purpose hand magnifying glass), and labour intensity is big; The normal eye promptly can dim eyesight, eye discomfort such as expand about uninterrupted observation moving object 30min, and testing staff's non-stop run for a long time can't guarantee the product export qualification rate; It is the detection with very high quantity precision that the draw point looper detects, and human eye can't judge accurately that error is big, and the chance of makeing mistakes is a lot, can't guarantee to detect quality; The speed that the professional detects draw point is up to 0.5/s, and throughput rate is had very big restriction.
The content of invention
Online detection dependence manual work to syringe draw point looper detects to prior art, and the workman is easy to generate visual fatigue, and labour intensity is big; Can't guarantee product percent of pass and detect quality; Problems such as monitoring velocity is low, the present invention provides the automatic testing method of a kind of NI Vision Builder for Automated Inspection to syringe draw point looper, and it reduces workman's detection labour intensity greatly; Accuracy of detection is high, speed is fast, the qualification rate of the product that can effectively guarantee to dispatch from the factory.
Technical scheme of the present invention is following:
A kind of NI Vision Builder for Automated Inspection may further comprise the steps the automatic testing method of syringe draw point looper:
(1) draw point is fixed on the frock bar anchor clamps, makes frock bar anchor clamps on-line operation, taking frock bar anchor clamps one side of camera fixing at on-line operation; According to the size of draw point to be detected and draw point towards, select the focal length of camera lens, shooting angle, multiplication factor, shooting distance, aperture size, the time for exposure of camera taken in adjustment, so that obtain photographic images clearly;
(2) the transverse curvature value with the draw point needle point is made as the detection parameter, and according to customer requirements the accuracy of detection and the acceptability limit of said detection parameter is set;
(3) computer is obtained camera and synchronous triggering and the control signal of production process, starts the image that said camera is taken on-line operation draw point needle point in real time by external trigger and control signal, and the image of taking is transferred to computer confession detection;
(4) computer is handled through image algorithm, extracts the image of draw point needle point; Find not have the transverse curvature value as if handling, think that then there is not bending in this draw point, belong to certified products, sort out from certified products letter sorting mouth through image algorithm;
(5) computer calculates the transverse curvature value of said draw point needle point; For the needle point excurvation, calculate the maximum distance of the said needle point outside and draw point needle body back side vertical line, this distance value promptly is the transverse curvature value of said excurvation draw point needle point; For curved in the needle point, calculate the maximum distance of said needle point inboard and draw point needle body back side vertical line, this distance value promptly is the transverse curvature value of said interior curved draw point needle point;
(6) judge that through the draw point needle point transverse curvature value that calculates this product belongs to certified products or waste product, waste product is rejected from the discharging opening of appointment through external trigger and control signal.
Its further technical scheme is: to said (6) step, specifically carry out the judgement and the go-on-go of draw point by following step:
(7) judge that the draw point needle point is an excurvation or interior curved, if excurvation then turned to for (8) step, if interior curved (9) step that then turned to;
Whether the transverse curvature value of (8) judging excurvation draw point needle point image is at acceptability limit＜0.05mm, as then turned to for (10) step at acceptability limit, if then turned to for (11) step more than or equal to acceptability limit >=0.05mm;
Whether the transverse curvature value of (9) judging interior curved draw point needle point image is at acceptability limit＜0.05mm, as then turned to for (10) step at acceptability limit, if then turned to for (11) step more than or equal to acceptability limit >=0.05mm;
(10) sort as certified products;
(11) directly as goods rejection.
And its further technical scheme is: to said (6) step, when detecting product and be waste product, computer will carry out picture cues through man-machine interface, and start warning device.
Useful technique effect of the present invention is:
The present invention adopts NI Vision Builder for Automated Inspection that the draw point looper is carried out automatic on-line and detects, and replaces manual detection, and the user can carry out the adjusting of accuracy of detection automatically.Have the record, classification, statistics, storage, the query function that product are detected certified products, this two series products of waste product.And in image, point out the defective work situation through friendly man-machine interface, and give sound, light alarm, reduce workman's detection labour intensity greatly.
Manual detection speed is generally 0.5/s, and the NI Vision Builder for Automated Inspection detection speed can reach 3 ~ 4/s, and the product detection speed of NI Vision Builder for Automated Inspection is artificial 6 ~ 8 times, has greatly improved production efficiency.
Manual detection can't uninterruptedly be carried out product quality in 24 hours and detect owing to environment and physiological reason, adopted NI Vision Builder for Automated Inspection to detect and then made it become possibility.The production time of equipment can prolong to greatest extent, has improved usage ratio of equipment.
The artificial detection because poor, the vision fatiguability that ventilates is difficult to the Continuous Tracking product quality.Quantizing to detect leans on artificial being difficult to guarantee that improper defect rate generally about 8 ~ 10%, has caused the significant wastage of the resources of production and production cost; The detection dimensional accuracy of NI Vision Builder for Automated Inspection is up to 0.01mm, and precision can every 0.01mm be that a gradient is adjusted, and is set to 0.01,0.02,0.03,0.04, several accuracy classes such as 0.05mm, thereby improves product percent of pass greatly and detect quality.
Description of drawings
Fig. 1 is normal draw point image.
Fig. 2 is the draw point image of needle point excurvation.
Fig. 3 is a draw point image curved in the needle point.
Fig. 4 is a process sequence diagram of the present invention.
The specific embodiment
Further specify below in conjunction with the accompanying drawing specific embodiments of the invention.
Fig. 1, Fig. 2, Fig. 3 take from the draw point side and real image after treatment.
In Fig. 1, Fig. 2, photographic images shown in Figure 3, in order better to distinguish figure, looper partly adopts exaggeration to handle among the figure, and generally there is not the bending of intensity like this in the draw point needle point in actual conditions; All around blank parts for the draw point image through the transparent space after the denoising software processes, shown in lines be the contour images after draw point is handled.
Embodiment 1, to the detection of needle point excurvation product:
Needle point excurvation image as shown in Figure 2, wherein the bent out portion of needle point upper right quarter is divided into the visual pattern of excurvation needle point.
Basler ACA640-100GM type industrial camera is fixed on the side of draw point, and camera is about 20mm apart from the distance of draw point side, uses to execute and bears 50 times and amplify zooms and become times camera lenses, and focal length transfers to 16mm, and aperture is transferred to maximum, and the time for exposure is adjusted to 0.41ms.Needle point excurvation accuracy of detection is set to 0.01mm, sets the normal transverse curvature value of certified products and is 0.05mm to the maximum.Adopt special-purpose white fiber optic point source, shine (backlight), and use and semiclosedly block the influence that the metal framework shields extraneous veiling glare,, embody the obvious characteristic of draw point looper so that obtain visual pattern more stablely from the heteropleural side of camera.The optical fiber source of this project uses the machine vision special light source (also can use the optical fiber source of other companies) of CCS company, so that can photograph distinct image more stablely, and is shown in the screen of computer.Adopt the frock bar anchor clamps (faller gill) on the production line to carry out the conveying of syringe draw point, guarantee that draw point by certain direction and speed, stably gets into checkout gear with belt transmission system.
Computer is according to the difference control system of institute of different production firm production equipment; Obtain synchronous triggering of camera and production process and control signal; Start said industrial camera and take the image of the draw point of on-line operation, and, be stored in the computer the draw point needle point image that obtains.
Computer carries out image to captured image through edge extracting, smoothing denoising, binary conversion treatment, Fourier Tranform scheduling algorithm to be handled, and makes image more clear, more meets the truth of draw point needle point.The algorithm that is adopted in the above-mentioned image processing process is conventional algorithm of the prior art.
Computer calculates the transverse curvature value of draw point needle point.This length is the needle point outside and (Fig. 2 middle distance a), this distance value promptly is the transverse curvature value of said excurvation draw point needle point to the maximum distance of draw point needle body back side vertical line.
Like detected transverse curvature value is 0.04mm, and then this product is certified products; Like detected transverse curvature value is 0.06mm, and then this product is a defective work.Computer is pointed out the defective work situation through friendly man-machine interface in image, and gives sound, light alarm, and certified products are write down, classify, add up warehouse-in.
Embodiment 2, to bending the detection of product in the needle point:
Needle point excurvation image as shown in Figure 3, wherein the bent out portion of needle point upper right quarter is divided into the visual pattern of excurvation needle point.
Basler ACA640-100GM type industrial camera is fixed on the side of draw point, and camera is about 20mm apart from the distance of draw point side, uses to execute and bears 50 times and amplify zooms and become times camera lenses, and focal length transfers to 16mm, and aperture is transferred to maximum, and the time for exposure is adjusted to 0.41ms.Draw point looper accuracy of detection is set to 0.01mm, sets the normal transverse curvature value of certified products and is 0.05mm to the maximum.Adopt special-purpose white fiber optic point source, shine (backlight), and use and semiclosedly block the influence that the metal framework shields extraneous veiling glare,, embody the obvious characteristic of draw point looper so that obtain visual pattern more stablely from the heteropleural side of camera.The optical fiber source of this project uses the machine vision special light source (also can use the optical fiber source of other companies) of CCS company, so that can photograph distinct image more stablely, and is shown in the screen of computer.Adopt the frock bar anchor clamps (faller gill) on the production line to carry out the conveying of syringe draw point, guarantee that draw point by certain direction and speed, stably gets into checkout gear with belt transmission system.
Computer is according to the difference control system of institute of different production firm production equipment; Obtain synchronous triggering of camera and production process and control signal; Start said industrial camera and take the image of the draw point of on-line operation, and, be stored in the computer the draw point needle point image that obtains.
Computer carries out image to captured image through edge extracting, smoothing denoising, binary conversion treatment, Fourier Tranform scheduling algorithm to be handled, and makes image more clear, more meets the truth of draw point needle point.The algorithm that is adopted in the above-mentioned image processing process is conventional algorithm of the prior art.
Computer calculates the transverse curvature value of draw point needle point.This length be needle point inboard with draw point needle body back side vertical line maximum distance (Fig. 3 middle distance a), this distance value promptly be said in the transverse curvature value of curved draw point needle point.
Like detected transverse curvature value is 0.04mm, and then this product is certified products; Like detected transverse curvature value is 0.06mm, and then this product is a defective work.Computer is pointed out the defective work situation through friendly man-machine interface in image, and gives sound, light alarm, and certified products are write down, classify, add up warehouse-in.
More than the control system (hardware and software) of the image capture device (camera, radiation source, power supply, image pick-up card etc.) that uses among all embodiment and storage device (hard disk, CD, floppy disk etc.), image processing equipment (hardware of image processor and software), image display (hardware and software), warning device and each part mentioned above all adopt prior art to design and produce or directly adopt relevant commercially available prod.
Above-described processing step of the present invention is shown in Fig. 4.
It should be noted that above-described at last only is preferred implementation of the present invention, the invention is not restricted to above embodiment.Be appreciated that other improvement and variation that those skilled in the art directly derive or associate under the prerequisite that does not break away from spirit of the present invention and design, all should think to be included within protection scope of the present invention.
Claims (3)
1. a NI Vision Builder for Automated Inspection is characterized in that may further comprise the steps to the automatic testing method of syringe draw point looper:
(1) draw point is fixed on the frock bar anchor clamps, makes frock bar anchor clamps on-line operation, taking frock bar anchor clamps one side of camera fixing at on-line operation; According to the size of draw point to be detected and draw point towards, select the focal length of camera lens, shooting angle, multiplication factor, shooting distance, aperture size, the time for exposure of camera taken in adjustment, so that obtain photographic images clearly;
(2) the transverse curvature value with the draw point needle point is made as the detection parameter, and according to customer requirements the accuracy of detection and the acceptability limit of said detection parameter is set;
(3) computer is obtained camera and synchronous triggering and the control signal of production process, starts the image that said camera is taken on-line operation draw point needle point in real time by external trigger and control signal, and the image of taking is transferred to computer confession detection;
(4) computer is handled through image algorithm, extracts the image of draw point needle point; Find not have the transverse curvature value as if handling, think that then there is not bending in this draw point, belong to certified products, sort out from certified products letter sorting mouth through image algorithm;
(5) computer calculates the transverse curvature value of said draw point needle point; For the needle point excurvation, calculate the maximum distance of the said needle point outside and draw point needle body back side vertical line, this distance value promptly is the transverse curvature value of said excurvation draw point needle point; For curved in the needle point, calculate the maximum distance of said needle point inboard and draw point needle body back side vertical line, this distance value promptly is the transverse curvature value of said interior curved draw point needle point;
(6) judge that through the draw point needle point transverse curvature value that calculates this product belongs to certified products or waste product, waste product is rejected from the discharging opening of appointment through external trigger and control signal.
2. according to the automatic testing method of the said NI Vision Builder for Automated Inspection of claim 1, it is characterized in that said (6) step is specifically carried out the judgement and the go-on-go of draw point by following step to syringe draw point looper:
(7) judge that the draw point needle point is an excurvation or interior curved, if excurvation then turned to for (8) step, if interior curved (9) step that then turned to;
Whether the transverse curvature value of (8) judging excurvation draw point needle point image at acceptability limit＜0.05mm, as then turning to for (10) step at acceptability limit, if >=0.05mm then turned to for (11) step;
(9) judge in the transverse curvature value of curved draw point needle point image whether at acceptability limit＜0.05mm, as then turning to for (10) step at acceptability limit, if >=0.05mm then turned to for (11) step;
(10) sort as certified products;
(11) directly as goods rejection.
3. according to the automatic testing method of the said NI Vision Builder for Automated Inspection of claim 1, it is characterized in that to said (6) step when detecting product and be waste product, computer will carry out picture cues through man-machine interface, and start warning device to syringe draw point looper.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104483321B (en) * | 2014-10-31 | 2017-07-28 | 苏州捷碧医疗科技有限公司 | A kind of injection needle automatic checkout system and detection method based on machine vision |
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| CN104076039B (en) * | 2014-03-28 | 2017-05-31 | 合波光电通信科技有限公司 | Optical filter open defect automatic testing method |
| CN104528082B (en) | 2014-12-24 | 2016-11-30 | 苏州捷碧医疗科技有限公司 | The pen-type injector syringe needle of a kind of simple packaging and using method thereof |
| CN105158260A (en) * | 2015-08-27 | 2015-12-16 | 孔华 | Textile needle treatment method based on double detection |
| CN106491358B (en) * | 2016-10-31 | 2019-10-11 | 成都杰仕德科技有限公司 | A kind of positioning device and method for automated dispensing system |
| CN109211937B (en) * | 2018-08-28 | 2021-02-19 | 西安工程大学 | Detection system and detection method for bending defect of elastic braid of underwear |
| CN111189844A (en) * | 2020-02-25 | 2020-05-22 | 威海远航科技发展股份有限公司 | Automatic detection system for packaging quality of venous blood taking needle |
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| CN113588662A (en) * | 2021-07-28 | 2021-11-02 | 扬州美德莱医疗用品有限公司 | Accurate image detection method and system for processing of injection needle |
| CN114813746B (en) * | 2022-04-08 | 2024-01-09 | 苏州浪潮智能科技有限公司 | Method, system, storage medium and equipment for curved needle detection based on machine vision |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| JPH02203269A (en) * | 1989-01-31 | 1990-08-13 | Shimadzu Corp | Method for detecting needle bending of automatic sample injection device |
| CN2619236Y (en) * | 2002-03-21 | 2004-06-02 | 阮积祥 | Bend needle detector of sewing machine |
| CN201503261U (en) * | 2009-08-04 | 2010-06-09 | 梁启明 | Automatic detecting device for infusion needles |
| CN201516418U (en) * | 2009-10-16 | 2010-06-30 | 南京师范大学 | Automatic detecting and sorting machine for metal buttons |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104483321B (en) * | 2014-10-31 | 2017-07-28 | 苏州捷碧医疗科技有限公司 | A kind of injection needle automatic checkout system and detection method based on machine vision |
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