CN101696877A - On-line detection method of machine vision system to spring verticality - Google Patents
On-line detection method of machine vision system to spring verticality Download PDFInfo
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- CN101696877A CN101696877A CN200910210888A CN200910210888A CN101696877A CN 101696877 A CN101696877 A CN 101696877A CN 200910210888 A CN200910210888 A CN 200910210888A CN 200910210888 A CN200910210888 A CN 200910210888A CN 101696877 A CN101696877 A CN 101696877A
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Abstract
The invention discloses an on-line detection method of a machine vision system to spring verticality. The spring verticality is set as a detection parameter; the detection precision and the qualified range of the detection parameter are set according to the requirement of a user; a camera is started by outer triggering and control signals for shooting an image of an on-line running spring side in real time; the shot image is transmitted to a computer for detection; the computer is used for carrying out image algorithm processing on the received image; the image on the spring side is extracted; the verticality of the spring side is computed by the computer to judge whether products are qualified products or discarded products by the computed verticality value; and two kinds of products are separated from different discharge holes by the outer triggering and control signals. The method has the advantages of high detection precision and high detection speed of the spring verticality and can effectively ensure the qualified ratio of the products.
Description
Technical field
The present invention relates to utilize Vision Builder for Automated Inspection to carry out the technical field of online detection, relate in particular to, utilize Vision Builder for Automated Inspection that spring verticality is carried out on-line detection method in the spring production scene.
Background technology
At the spring workshop scene of line production, need carry out online detection to the verticality of spring.In the prior art, online detection dependence to spring verticality manually detects, produce the machine side at spring and establish range estimation and the processing that 4～5 people carry out the spring vertical angle, testing result is divided into certified products (is 0～15 ° as vertical angle) and unacceptable product (as 〉=15 °), greater than the spring of acceptable precision directly as waste disposal.
The shortcoming that manual detection exists mainly contains: the on-the-spot dust of workshop is many, noise is big, and workman's testing environment is abominable; 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 detection of band such as spring verticality detection quantity precision, human eye is difficult to judge that accurately error is big that the chance of makeing mistakes is a lot, can't guarantee to detect quality; The professional observes the speed of spring verticality be up to 0.5/s, and throughput rate is had very big restriction.
The content of invention
Online detection dependence to spring verticality manually detects at prior art, the workman is easy to generate visual fatigue, labour intensity is big, can't guarantee product percent of pass and detect quality, problems such as monitoring velocity is low the invention provides the online test method of a kind of Vision Builder for Automated Inspection to spring verticality, and it reduces workman's detection labour intensity greatly, accuracy of detection height, speed are fast, the qualification rate of the product that can effectively guarantee to dispatch from the factory.
Technical scheme of the present invention is as follows:
A kind of Vision Builder for Automated Inspection may further comprise the steps the online test method of spring verticality:
(1) prepares industrial camera, described industrial camera or control online shooting by outer triggering signal;
(2) take aperture size, the time shutter of camera according to the size adjustment of spring product to be detected, so that obtain photographic images clearly;
(3) setting the detection parameter is spring verticality, and the accuracy of detection and the acceptability limit of described detection parameter are set according to customer requirements;
(4) start the image that described camera is taken on-line operation spring side in real time by external trigger and control signal, and the image of taking is transferred to computing machine for detecting;
(5) computing machine extracts the image of spring side to receiving to such an extent that image carries out the image algorithm processing;
(6) calculate computing machine drift angle that perpendicular line is departed from described spring side;
(7) judge that by the angle value that calculates this product is to belong to certified products/waste product, sorts two series products with control signal by external trigger from different discharging openings.
Its further technical scheme is:
To described (7) step, specifically carry out the judgement and the go-on-go of verticality by following step:
(8) whether judge verticality at acceptability limit, as then turn to (8A) step at acceptability limit (＜15 °), if then turn to (8B) step greater than specialized range (〉=15 °):
(8A) sort as certified products;
(8B) directly as goods rejection.
And its further technical scheme is:
To described (7) step, when detecting product and be waste product, computing machine will carry out picture cues by man-machine interface, and start warning device.
Useful technique effect of the present invention is:
The present invention adopts Vision Builder for Automated Inspection that spring verticality is carried out online detection, 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 by 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 Vision Builder for Automated Inspection detection speed can reach about 2/s, and the product detection speed of Vision Builder for Automated Inspection is artificial 4 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 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 neighbourhood noise is big, dust is many, the vision fatiguability is difficult to the Continuous Tracking product quality.Quantize to detect and guarantee that improper defect rate generally about 10～15%, has caused the significant wastage of the resources of production and production cost by artificial being difficult to; The detection of vertical degree precision of Vision Builder for Automated Inspection is up to 0.5 degree, and precision can per 0.5 degree be that a gradient is adjusted, and is set to several accuracy classes such as 0.5,1,1.5,2,2.5 degree, thereby improves product percent of pass greatly and detect quality.
Description of drawings
Fig. 1 is the spring side image of certified products.
Fig. 2 is the spring side image of waste product.
Fig. 3 is a process sequence diagram of the present invention.
Embodiment
Below in conjunction with accompanying drawing the specific embodiment of the present invention is described further.
Fig. 1, the 2nd takes and image after treatment from the spring side.
In the photographic images shown in Fig. 1,2, in order better to distinguish figure, broad-brush parallelogram frame is a spring side photographic images among the figure; The horizontal and vertical lines of band arrow is two dimension (X, Y) coordinate of standard; The angle extended line that row upper left side, equality four limit straight line is done for making things convenient for angle calculation; Whether qualified dotted line be to distinguish spring verticality and the boost line (for the verticality separatrix of certified products and unacceptable product) done for convenience.
Embodiment one, to the detection of specification product:
Spring side image as shown in Figure 1, wherein Y-axis and spring left margin angle are the expression zone of verticality.
With Beijing little 1300UM of looking type industrial camera be fixed on spring detect conveying device directly over, camera is 30cm apart from the distance of spring side, uses 8mm COMPUTAR camera lens, aperture is transferred to maximal value, the time shutter is adjusted to 0.58ms.The differences in angle accuracy of detection is set to 1 °, and setting the normal verticality of certified products is 0 °～15 °.Adopt special red LED-backlit light source, under spring, shine, and use and semiclosedly block the metal framework,, embody the obvious characteristic of spring side so that obtain visual pattern more stablely.The power supply of display light source is a constant pressure and flow, is the stabilized light source that tool does not become frequently or high frequency becomes, so that can photograph distinct image more stablely, and is shown in the screen of computing machine.Adopt high speed spring charging vibrating bunker, guarantee that spring enters pick-up unit by certain mode and speed.
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 described industrial camera and take the image of the spring side of on-line operation, and, be stored in the computing machine the spring side image that obtains.
Computing machine carries out Flame Image Process to captured image by edge extracting, smoothing denoising, binary conversion treatment, Fourier Tranform scheduling algorithm, makes image more clear, more meets the truth of spring.The algorithm that is adopted in the above-mentioned image processing process is conventional algorithm of the prior art.
Computing machine calculates the spring vertical angle.This angle is the number of degrees of described Y-axis and the formed angle of spring left border straight line, and this angle value also is described verticality value.
As detected angle value is 12 °, and then this product is certified products.Computing machine writes down, classifies, adds up warehouse-in to such certified products.
Embodiment two, to the detection of waste product:
Spring side image as shown in Figure 2, wherein Y-axis and spring left margin angle are the expression zone of verticality.
With Beijing little 1300UM of looking type industrial camera be fixed on spring detect conveying device directly over; camera is 30cm apart from the distance of spring side; use 8mm COMPUTAR camera lens; aperture is transferred to 1/3 position; time shutter is adjusted to 1ms, and when the radian accuracy of detection was set to 1 °, setting the normal radian of certified products was 0 °～15 °; in testing process, obtain the spring side image, calculate the verticality value in the spring side image.
It is identical with embodiment 1 to detect remaining operation steps of embodiment.
As detected angle value is 20 °, and then this product is a waste product.Computing machine is pointed out the unacceptable product situation by friendly man-machine interface in image, and gives sound, light alarm, and such waste 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, and concrete step comprises:
(1) prepares industrial camera, described industrial camera or control online shooting by outer triggering signal;
(2) take aperture size, the time shutter of camera according to the size adjustment of spring product to be detected, so that obtain photographic images clearly;
(3) setting the detection parameter is spring verticality, and the accuracy of detection and the acceptability limit of described detection parameter are set according to customer requirements;
(4) start the image that described camera is taken on-line operation spring side in real time by external trigger and control signal, and the image of taking is transferred to computing machine for detecting;
(5) computing machine extracts the image of spring side to receiving to such an extent that image carries out the image algorithm processing;
(6) calculate computing machine drift angle that perpendicular line is departed from described spring side;
(7) judge that by the angle value that calculates this product is to belong to certified products/waste product, sorts two series products with control signal by external trigger from different discharging openings.
To described (7) step, specifically carry out the judgement and the go-on-go of verticality by following step:
(8) whether judge verticality at acceptability limit, as then turn to (8A) step at acceptability limit (＜15 °), if then turn to (8B) step greater than specialized range (〉=15 °):
(8A) sort as certified products;
(8B) directly as goods rejection.
To described (7) step, when detecting product and be waste product, computing machine will carry out picture cues by man-machine interface, and start warning device.
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 Vision Builder for Automated Inspection is characterized in that may further comprise the steps to the online test method of spring verticality:
(1) prepares industrial camera, described industrial camera or control online shooting by outer triggering signal;
(2) take aperture size, the time shutter of camera according to the size adjustment of spring product to be detected;
(3) setting the detection parameter is spring verticality, and the accuracy of detection and the acceptability limit of described detection parameter are set according to customer requirements;
(4) start the image that described camera is taken on-line operation spring side in real time by external trigger and control signal, and the image of taking is transferred to computing machine;
(5) computing machine extracts the image of spring side to receiving to such an extent that image carries out the image algorithm processing;
(6) calculate computing machine drift angle that perpendicular line is departed from described spring side;
(7) judge that by the angle value that calculates this product is to belong to certified products/waste product, sorts two series products with control signal by external trigger from different discharging openings.
2. Vision Builder for Automated Inspection according to claim 1 is characterized in that the online test method of spring verticality, to described (7) step, specifically carries out the judgement and the go-on-go of verticality by following step:
(8) whether judge verticality at acceptability limit, as then turn to (8A) step at acceptability limit (＜15 °), if then turn to (8B) step greater than specialized range (〉=15 °):
(8A) sort as certified products;
(8B) directly as goods rejection.
3. Vision Builder for Automated Inspection according to claim 1 is characterized in that the online test method of spring verticality, and to described (7) step, when detecting product and be waste product, computing machine will carry out picture cues by man-machine interface, and start warning device.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102303021A (en) * | 2011-06-09 | 2012-01-04 | 浙江美力科技股份有限公司 | Equal-wire-diameter varied-stiffness automotive suspension spring flaw detection method |
| CN102305592A (en) * | 2011-04-29 | 2012-01-04 | 无锡众望四维科技有限公司 | Method for automatically detecting back-stitching of steel needle of injector by using mechanical vision system |
| CN102495077A (en) * | 2011-11-14 | 2012-06-13 | 无锡众望四维科技有限公司 | Automatic detecting method of machine vision system for detecting flaws of infusion bottle |
| CN102494643A (en) * | 2011-11-14 | 2012-06-13 | 无锡众望四维科技有限公司 | Method for automatically detecting flatness of notch of remaining needle bush by machine vision system |
| CN103143511A (en) * | 2013-03-14 | 2013-06-12 | 唐景华 | Bent and straight chopsticks separating device |
| CN104976959A (en) * | 2015-07-07 | 2015-10-14 | 齐鲁工业大学 | Machine-vision-based spring size online measurement system and method thereof |
| CN106595530A (en) * | 2016-12-06 | 2017-04-26 | 苏州博众精工科技有限公司 | Device for determining verticality of cylindrical material member |
| CN113514031A (en) * | 2021-04-15 | 2021-10-19 | 石家庄铁道大学 | Building inclination detection device and method based on machine vision |
-
2009
- 2009-11-13 CN CN200910210888A patent/CN101696877A/en active Pending
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102305592A (en) * | 2011-04-29 | 2012-01-04 | 无锡众望四维科技有限公司 | Method for automatically detecting back-stitching of steel needle of injector by using mechanical vision system |
| CN102303021A (en) * | 2011-06-09 | 2012-01-04 | 浙江美力科技股份有限公司 | Equal-wire-diameter varied-stiffness automotive suspension spring flaw detection method |
| CN102495077A (en) * | 2011-11-14 | 2012-06-13 | 无锡众望四维科技有限公司 | Automatic detecting method of machine vision system for detecting flaws of infusion bottle |
| CN102494643A (en) * | 2011-11-14 | 2012-06-13 | 无锡众望四维科技有限公司 | Method for automatically detecting flatness of notch of remaining needle bush by machine vision system |
| CN103143511A (en) * | 2013-03-14 | 2013-06-12 | 唐景华 | Bent and straight chopsticks separating device |
| CN104976959A (en) * | 2015-07-07 | 2015-10-14 | 齐鲁工业大学 | Machine-vision-based spring size online measurement system and method thereof |
| CN104976959B (en) * | 2015-07-07 | 2017-11-03 | 齐鲁工业大学 | A kind of spring sizes on-line measurement system and its method based on machine vision |
| CN106595530A (en) * | 2016-12-06 | 2017-04-26 | 苏州博众精工科技有限公司 | Device for determining verticality of cylindrical material member |
| CN113514031A (en) * | 2021-04-15 | 2021-10-19 | 石家庄铁道大学 | Building inclination detection device and method based on machine vision |
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Application publication date: 20100421 |