CN102494643A - Method for automatically detecting flatness of notch of remaining needle bush by machine vision system - Google Patents
Method for automatically detecting flatness of notch of remaining needle bush by machine vision system Download PDFInfo
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- CN102494643A CN102494643A CN2011103590670A CN201110359067A CN102494643A CN 102494643 A CN102494643 A CN 102494643A CN 2011103590670 A CN2011103590670 A CN 2011103590670A CN 201110359067 A CN201110359067 A CN 201110359067A CN 102494643 A CN102494643 A CN 102494643A
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Abstract
The invention provides a method for automatically detecting flatness of a notch of a remaining needle bush by a machine vision system. The method comprises the following steps of: setting the burr height at the notch of the remaining needle bush as a detection parameter; setting different detection precisions and acceptability limits according to user demands; turning on a camera to shoot an image of the notch of the remaining needle bush, which is operated on line, in real time by an external triggering and controlling signal; transmitting the shot image to a computer for detection; processing the image by the computer through an image algorithm; extracting the image of the notch of the remaining needle bush, and calculating the burr height at the notch of the remaining needle bush; judging whether a product belongs to a qualified product or a waste according to the calculated burr height; and removing the wastes from an assigned discharge opening according to the external triggering and controlling signal. According to the method disclosed by the invention, the detection on the flatness of the remaining needle bush is high in precision and fast, so that the product yield 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 remaining needle lining otch smooth method that detects automatically whether in remaining needle lining production scene.
Background technology
Remaining needle be used to infuse, device that blood transfusion and extracorporeal circulation of blood etc. are disposed.Remaining needle remains on the top of remaining needle lining with needle tubing, and the rear end of remaining needle lining connects transfusion with pipe.The medical worker is thrust patient body with said needle tubing with said lining.After this said needle tubing is pulled out, and said lining is kept somewhere in patient body.Said remaining needle lining is connected with infusion set and is used for infusing.
On-the-spot in the remaining needle lining making-up shop of line production, need carry out online detection to remaining needle lining otch is whether smooth.If the out-of-flatness of remaining needle lining otch then can be stabbed patient.In the prior art; Online detection to remaining needle lining incision burr relies on the special-purpose magnifier of artificial use to detect; Establish about 80 people on remaining needle lining production machine side and carry out remaining needle lining otch smooth detection and processing, product is divided into certified products (smooth like otch) and unacceptable product (like the otch out-of-flatness) according to testing result.Unacceptable product 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; The smooth detection of remaining needle lining otch is the detection with very high quantity precision, 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 the remaining needle lining is up to 0.5/s, and throughput rate is had very big restriction.
The content of invention
Smooth online detection relies on manual work to detect to remaining needle lining otch 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 a kind of NI Vision Builder for Automated Inspection to the smooth automatic testing method of remaining needle lining otch, 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 smooth automatic testing method of remaining needle lining otch:
(1) the remaining needle lining 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 remaining needle lining to be detected and remaining needle lining towards, select the focal length of camera lens, shooting angle, enlargement factor, shooting distance, aperture size, the time shutter of camera taken in adjustment, so that obtain photographic images clearly;
(2) burr height with remaining needle lining incision 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) computing machine is obtained camera and synchronous triggering and the control signal of production process, starts the image that said camera is taken on-line operation remaining needle lining otch in real time by external trigger and control signal, and the image of taking is transferred to computing machine confession detection;
(4) computing machine is handled through image algorithm, extracts the image of remaining needle lining otch;
(5) computing machine calculates the burr height of said remaining needle lining otch; This highly is the distance between the apogee distance remaining needle lining otch horizontal line of burr top, and this distance value promptly is the burr height value of said remaining needle lining otch;
(6) judge that through the burr height that calculates this product belongs to certified products, or waste product, rejects waste product through external trigger and control signal from the discharging opening of appointment.
Its further technical scheme is: to said (6) step, specifically carry out smooth judgement of otch and go-on-go by following step:
Whether the burr height of (7) judging remaining needle lining otch is at acceptability limit＜0.01um, as then turned to for (8) step at acceptability limit, if then turned to for (9) step more than or equal to acceptability limit >=0.01um;
(8) sort as certified products;
(9) directly as goods rejection.
And its further technical scheme is: to said (6) step, when detecting product and be waste product, computing machine 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 smooth automatic on-line that carries out of remaining needle lining otch is detected, 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 unacceptable product 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 0.001um, and precision can be adjusted, and is set to 0.001,0.002,0.005, several accuracy classes such as 0.01um, thereby improves product percent of pass greatly and detect quality.
Description of drawings
Fig. 1 is the smooth remaining needle lining image of otch.
Fig. 2 is the irregular remaining needle lining of an otch image.
Fig. 3 is a process sequence diagram of the present invention.
Embodiment
Further specify below in conjunction with the accompanying drawing specific embodiments of the invention.
Fig. 1, Fig. 2 take from remaining needle lining side and real image after treatment.
In photographic images shown in Figure 2,, exaggeration has been carried out in the out-of-flatness of remaining needle lining otch amplified in order better to distinguish figure; In Fig. 1, Fig. 2, blank parts is a remaining needle lining image through the transparent space after the denoising software processes all around, shown in lines be the contour images of remaining needle lining after handling.
Embodiment 1, to the detection of the smooth product of otch:
Remaining needle lining image as shown in Figure 1, wherein top section is the visual pattern of remaining needle lining otch.
Basler ACA640-100GM type industrial camera is fixed on the side of remaining needle lining; Camera is about 20mm apart from the distance of remaining needle lining side, uses to execute and bears 50 times of amplification zooms change times camera lenses, and focal length transfers to 16mm; Aperture is transferred to maximal value, and the time shutter is adjusted to 0.41ms.Protrusion burr accuracy of detection is set to 0.001um, and the setting certified products normally protrude the burr lateral length and are 0.01um 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 remaining needle lining otch 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 computing machine.Adopt the frock bar anchor clamps (faller gill) on the production line to carry out the conveying of remaining needle lining, guarantee that the remaining needle lining by certain direction and speed, stably gets into pick-up unit with belt transmission system.
Computing machine is according to the different 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 remaining needle lining of on-line operation, and, be stored in the computing machine the remaining needle lining otch image that obtains.
Computing machine carries out Flame Image Process to captured image through edge extracting, smoothing denoising, binary conversion treatment, Fourier Tranform scheduling algorithm, makes image more clear, more meets the truth of remaining needle lining otch.The algorithm that is adopted in the above-mentioned image processing process is conventional algorithm of the prior art.
Computing machine calculates remaining needle lining otch burr height.This highly is the distance (height h among Fig. 1) between the burr apogee distance remaining needle lining otch horizontal line, and this distance value promptly is the burr height value of said remaining needle lining otch.
Like detected height value is 0.005um, and then this product is certified products.Computing machine writes down, classifies, adds up warehouse-in to such certified products.
Embodiment 2, to the detection of otch out-of-flatness product:
Remaining needle lining image as shown in Figure 2, wherein top section is the visual pattern of remaining needle lining otch.
Basler ACA640-100GM type industrial camera is fixed on the side of remaining needle lining; Camera is about 20mm apart from the distance of remaining needle lining side, uses to execute and bears 50 times of amplification zooms change times camera lenses, and focal length transfers to 16mm; Aperture is transferred to maximal value, and the time shutter is adjusted to 0.41ms.Protrusion burr accuracy of detection is set to 0.001um, and the setting certified products normally protrude the burr lateral length and are 0.01um 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 remaining needle lining otch 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 computing machine.Adopt the frock bar anchor clamps (faller gill) on the production line to carry out the conveying of remaining needle lining, guarantee that the remaining needle lining by certain direction and speed, stably gets into pick-up unit with belt transmission system.
Computing machine is according to the different 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 remaining needle lining of on-line operation, and, be stored in the computing machine the remaining needle lining otch image that obtains.
Computing machine carries out Flame Image Process to captured image through edge extracting, smoothing denoising, binary conversion treatment, Fourier Tranform scheduling algorithm, makes image more clear, more meets the truth of remaining needle lining otch.The algorithm that is adopted in the above-mentioned image processing process is conventional algorithm of the prior art.
Computing machine calculates remaining needle lining otch burr height.This highly is the distance (height h among Fig. 2) between the burr apogee distance remaining needle lining otch horizontal line, and this distance value promptly is the burr height value of said remaining needle lining otch.
Like detected height value is 0.015um, and then this product is a unacceptable product.Computing machine is pointed out the unacceptable product situation through friendly man-machine interface in image, and gives sound, light alarm, and such unacceptable product is write down, classifies, adds 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. 3.
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 smooth automatic testing method of remaining needle lining otch:
(1) the remaining needle lining 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 remaining needle lining to be detected and remaining needle lining towards, select the focal length of camera lens, shooting angle, enlargement factor, shooting distance, aperture size, the time shutter of camera taken in adjustment, so that obtain photographic images clearly;
(2) burr height with remaining needle lining incision 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) computing machine is obtained camera and synchronous triggering and the control signal of production process, starts the image that said camera is taken on-line operation remaining needle lining otch in real time by external trigger and control signal, and the image of taking is transferred to computing machine confession detection;
(4) computing machine is handled through image algorithm, extracts the image of remaining needle lining otch;
(5) computing machine calculates the burr height of said remaining needle lining otch; This highly is the distance between the apogee distance remaining needle lining otch horizontal line of burr top, and this distance value promptly is the burr height value of said remaining needle lining otch;
(6) judge that through the burr height that calculates this product belongs to certified products, or waste product, rejects waste product through external trigger and control signal from the discharging opening of appointment.
According to the said NI Vision Builder for Automated Inspection of claim 1 to the smooth automatic testing method of remaining needle lining otch, it is characterized in that to said (6) step, specifically carry out smooth judgement of otch and go-on-go by following step:
Whether the burr height of (7) judging remaining needle lining otch is at acceptability limit＜0.01um, as then turned to for (8) step at acceptability limit, if then turned to for (9) step more than or equal to acceptability limit >=0.01um;
(8) sort as certified products;
(9) directly as goods rejection.
According to the said NI Vision Builder for Automated Inspection of claim 1 to the smooth automatic testing method of remaining needle lining otch; It is characterized in that said (6) step; When detecting product and be waste product, computing machine will carry out picture cues through man-machine interface, and start warning device.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103453859A (en) * | 2013-09-04 | 2013-12-18 | 吴江市博众精工科技有限公司 | Mechanism for measuring flatness of small parts |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101033953A (en) * | 2007-02-02 | 2007-09-12 | 西安交通大学 | Measurement method of planeness based on image processing and pattern recognizing |
| JP2009092474A (en) * | 2007-10-05 | 2009-04-30 | Denso Corp | Flash detection method for molded article |
| CN101696877A (en) * | 2009-11-13 | 2010-04-21 | 无锡众望四维科技有限公司 | On-line detection method of machine vision system to spring verticality |
| CN201731837U (en) * | 2010-06-17 | 2011-02-02 | 江苏通达动力科技股份有限公司 | Burr detection device |
| CN201828525U (en) * | 2010-10-11 | 2011-05-11 | 庄鸿 | Automatic detection system for disposable syringe needles |
-
2011
- 2011-11-14 CN CN2011103590670A patent/CN102494643A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101033953A (en) * | 2007-02-02 | 2007-09-12 | 西安交通大学 | Measurement method of planeness based on image processing and pattern recognizing |
| JP2009092474A (en) * | 2007-10-05 | 2009-04-30 | Denso Corp | Flash detection method for molded article |
| CN101696877A (en) * | 2009-11-13 | 2010-04-21 | 无锡众望四维科技有限公司 | On-line detection method of machine vision system to spring verticality |
| CN201731837U (en) * | 2010-06-17 | 2011-02-02 | 江苏通达动力科技股份有限公司 | Burr detection device |
| CN201828525U (en) * | 2010-10-11 | 2011-05-11 | 庄鸿 | Automatic detection system for disposable syringe needles |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103453859A (en) * | 2013-09-04 | 2013-12-18 | 吴江市博众精工科技有限公司 | Mechanism for measuring flatness of small parts |
| CN103453859B (en) * | 2013-09-04 | 2015-12-09 | 吴江市博众精工科技有限公司 | A kind of miniature parts flatness measurement mechanism |
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Application publication date: 20120613 |