CN2932377Y - Flow-type machine visual detector - Google Patents
Flow-type machine visual detector Download PDFInfo
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- CN2932377Y CN2932377Y CN 200620014167 CN200620014167U CN2932377Y CN 2932377 Y CN2932377 Y CN 2932377Y CN 200620014167 CN200620014167 CN 200620014167 CN 200620014167 U CN200620014167 U CN 200620014167U CN 2932377 Y CN2932377 Y CN 2932377Y
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Abstract
A flow-through machine vision detecting instrument comprises an imaging working bench arranged on a chassis, a product delivery mechanism delivering products onto the imaging working bench, an optical imager, a light source and an optical computer, wherein the computer is connected with the optical imager, gathering images from the optical imager analyzing and comparing images of program products and samples in order to distinguishing qualities of program products. The computer is also connected with a motor-driven apparatus of the product delivery mechanism, the control conveyer is actuated with optical imager in phase. The flow-through machine vision detecting instrument is capable of respectively detecting program products on the conveyer automatically, achieving a high and accurate detecting efficiency. By quick-speed orthonormality correlated matching algorism, the utility model quickly positions a location of a key element in the image, by comparing with key element setting in the image instead of the image of the whole product, the instrument is capable of distinguishing the program product if the product is conforming article or non-conforming article, and making it possible for the detected product to rotate and move within a finite range.
Description
Technical field
The utility model relates to the employing movement control technology, and accurately location, optical imagery and image analysis technology come the outward appearance and the profile of product are carried out the Quality Detection technology particularly a kind of continuous-flow type Machine Vision Detection instrument.
Background technology
At present, the outward appearance of known bulk article and the Quality Detection of profile all are to detect by human eye, quantification and execution, human eye are tired easily because the judgement of human eye is difficult for, factor such as work when the people can not grow in being in a bad mood, some high temperature or the poisonous environment easily, cause and now generally judge by accident with false determination ratio all very high to the Quality Detection of product appearance and profile.Some place was once attempted obtaining image with camera and was replaced human eye detection, but all be single product to be placed directly in the detection of taking a picture on the worktable by manual, detected again and taken away, put again one new, so repeat, automaticity is low, detection efficiency is low, and testing staff's working strength is big, and accuracy of detection is poor, can't adapt to the needs of Modern High-Speed automatic production line.
Summary of the invention
The purpose of this utility model is the above-mentioned deficiency that overcomes prior art, a kind of continuous-flow type Machine Vision Detection instrument is provided, it can accurately be transported to the imaging worktable with product to be measured automatically and quickly one by one, obtain the image of product, and analyse and compare, thereby differentiate the outward appearance of product to be measured or the quality of type quality, reach the purpose of fast detecting and raising accuracy rate.
The utility model continuous-flow type Machine Vision Detection instrument comprises the imaging worktable that is installed on the frame, also comprises:
The product conveyor structure, this mechanism is installed on the described frame, it comprises conveying belt, stepper motor or servomotor and motor driver, motor driver drive stepping motor or servomotor running, drive conveying belt and intermittently move, the product to be measured on the conveying belt is accurately delivered to the imaging worktable one by one;
Optical image former, it is installed on imaging worktable top, is used to obtain the image of the product to be measured on the imaging worktable;
Light source, it is installed on imaging worktable front upper place, and when optical image former obtained the image of product to be measured, light source was from this product to be measured of product to be measured front irradiation;
Computing machine, it is connected with optical image former, gathers the image that optical image former obtains, and carries out the analyses and comparison of product image to be measured and sample image, thereby differentiate the quality of product to be measured; Computing machine also is connected with the motor driver of product conveyor structure, control travelling belt and optical image former harmony action.
This continuous-flow type Machine Vision Detection instrument combines movement control technology, optical imagery and image analysis technology come the outward appearance and the profile of product is carried out Quality Detection, can detect one by one the product to be measured on the conveying belt automatically, and the detection efficiency height, accurately.Operating personnel only need product to be measured is put on the belt, this detector can finish automatically product to be measured conveying, take pictures, process such as analysis and judgement, up to the output testing result, automatically enter the detection of next product to be measured then, the take pictures harmony action of travelling belt feeding and optical image former, do not need manual intervention, efficiently solve tradition employing human eye detection with picking and placeing product carries out the defectives that the method detection efficiency is low, False Rate is high such as optical photographing detection by hand.
It is accurately located by importing movement control technology, solved the conveying and the orientation problem of product to be measured effectively, can guarantee the moment of taking pictures product to be measured be what not move, and just be parked in camera under, and be position when clapping sample at first, do not differ 1mm.
It is earlier by quick regular correlation matching algorithm, the quick position of locator key element in image, the key element of setting in the movement images then, to differentiate product to be measured be non-defective unit or go back defective products, but not the image of entire product allows product to be measured to rotate within the specific limits and moves.
Description of drawings
Fig. 1 is the front view of present embodiment continuous-flow type Machine Vision Detection instrument;
Fig. 2 is its side view;
Fig. 3 is its vertical view;
Fig. 4 is the theory diagram of present embodiment continuous-flow type Machine Vision Detection instrument.
Embodiment
The utility model continuous-flow type Machine Vision Detection instrument is the equipment that utilizes machine vision graphical analysis and motion control Positioning Principle that the outward appearance or the type quality of product detected.The technical scheme of detector comprises four bulks: synchronous belt type circulation gear train, accurately positioning motor control, optical imaging system and image analysis system.Promptly by after the sampling of imaging first for the treatment of testing product, the important element that workpiece is differentiated is provided with in the computer image analysis system.In actual production line testing process, by accurate positioning motor the endless apron simple harmonic is accurately located, guarantee that each workpiece fundamental sum sampling is in the same position imaging, image analysis system compares the key element of new pattern and sampling, thereby detects the outward appearance of workpiece or the quality of profile.Further specify below in conjunction with accompanying drawing:
Shown in Fig. 1-4, present embodiment continuous-flow type Machine Vision Detection instrument comprises frame 10, is arranged to the picture worktable on the frame 10, also comprises:
The product conveyor structure, adopt synchronous belt type circulation gear train, be installed on the frame 10, this mechanism comprises conveying belt 7, stepper motor or servomotor 3 and motor driver, motor driver drive stepping motor or servomotor 3 runnings, drive conveying belt 7 and intermittently move, the product to be measured on the conveying belt 7 is accurately delivered to the imaging worktable one by one;
Optical image former 4 adopts optical camera, is installed on imaging worktable top, is used to obtain the image of the product to be measured on the imaging worktable;
The installed software system comprises in the computing machine 1: hardware communication module, kernel module (being image analysis module), subscriber interface module, hardware system diagnostic module, testing result and intermediate data storage, analysis, Reports module.Wherein, the hardware communication module carries out image data acquiring, state reads and order transmission.Image analysis module is extracted the key element that needs differentiation from sample image, be stored in the storer, when checking product to be measured, utilize fast correlation matching algorithm, symbolic construction method shape recognizer, figure center of gravity square recognizer that the key element that the image of product to be measured gets sample image in key element and the storer is compared, thereby differentiate the quality of product to be measured.
Among the figure, 9 is graphoscope, and 10 is frame, and 11 is the position that is used to place product to be measured on the conveying belt 7.Optical image former 4 and light source 5 are installed in the casing 8.
In order to raise the efficiency, at first solve workpiece and move problem, well-known, computer for analysis speed can be by improving the computer configuration and improving algorithm and improve, if workman's place work piece is chronic, be far longer than the time of computer for analysis, the efficient of a then whole equipment is extremely low.In moving, take pictures simultaneously, very easily influence picture effect, so to require at the moment workpiece of taking pictures be not move, workpiece just be parked in camera under, and be position when clapping sample at first, do not differ 1mm, this has just required accurate localization control.The utility model has solved the problem that workpiece moves effectively by the importing with movement control technology.Motion control is meant that by to stepping or watch the accurate positioning control of motor reach motion purpose accurately, this technology is ripe at present.The continuous-flow type conveying belt is meant that driving conveying belt by common drive motor back and forth rotates the target that reaches continuous conveying workpieces, and present known conveying belt all can only reach the effect of speed governing, cannot accomplish that all the optional position stops promptly accurately location.The utility model is that above-mentioned knowledge and technology is combined to form new scheme, to be used for pinpoint stepping and servo motor and be used in the flowing water conveying belt, constitute continuous accurate location, reach and continuous running can accurately locate again, guarantee every width of cloth picture position+/-1mm is with interior deviation, per minute reaches the detection speed of 70 workpiece simultaneously.
Because some inconsistency always place work piece the time, make that workpiece for measurement and exemplar more within the specific limits can some offsets, Workpiece Rotating etc.Both made the picture of same workpiece (certified products) also can some discrepancy.The picture that the image analysis system in past is different with two width of cloth carries out point-to-point comparison, finds out both othernesses, then according to the difference threshold value and then judge the correlativity of two figure.This kind The Application of Technology is attempted at present, all can not accomplish the rotation contrast, and the local correlation system intelligence is than equity.For head it off, the computing method of the x-y-θ skew of quick calculating workpiece on conveying belt have been adopted in this continuous-flow type Machine Vision Detection instrument, specifically describe as follows: specify an element as a feature A in the first half of image, specify an element as a feature B in the latter half of image, the search area SA of specific characteristic A and feature B and SB, and require SA and SB not to allow overlapping areas.In examination criteria, preserve position and size and the view data of feature A and feature B, the position of search area SA and SB and size.During detection, in the search area SA of appointment, search feature A, in search area SB, search feature B, calculate the central point of feature A and feature B, be straight line AB with feature A and feature B central point, calculate the angle with master sample cathetus AB, thereby can determine the θ deviation of keyboard to be detected and standard model, mid point by calculating two straight lines can be determined the X-Y deviation of keyboard to be detected and standard model in the deviation of X, Y direction.Because the feature in this method can be specified arbitrarily,, the adaptability of a general piece of writing is arranged so have dirigibility; The search area of each feature can be arranged on 1/4 range content of image, so search speed is fast; Because a feature is in image the first half, another feature is in image the latter half, and is to use the mid point of the straight line of the central point by two features to calculate X-Y θ deviation, so accurate positioning.Because workpiece is spent in the scope of 5 degree-5 in θ deviation on the travelling belt, so select fast positive naturalization correlation matching algorithm to carry out the search of feature A and feature B.
The method of using above-mentioned continuous-flow type Machine Vision Detection instrument that the outward appearance and the profile of product are carried out quality restriction may further comprise the steps:
A, computing machine extract the key element that needs differentiation by optical image former collected specimens image from sample image, be stored in the storer;
B, product to be measured is spaced on conveying belt;
C, control module control conveying belt intermittently move, and the product to be measured on the conveying belt is delivered to the imaging worktable one by one;
D, optical image former obtain the image of the product to be measured on the imaging worktable, are transferred to computing machine;
E, computing machine compare the key element of sample image in the image of product to be measured and the storer, thereby differentiate the quality of product to be measured;
F, substandard product is made marks or returns preceding working procedure, specification product are transported to subsequent processing.
Among the step a, the method for extracting the key element that needs differentiation from sample image is: maximum between-cluster variance binaryzation, the patch dividing method based on connective principle, symbolic construction method, figure center of gravity square analytic approach.
This continuous-flow type Machine Vision Detection instrument combines outward appearance and type quality to product to detect movement control technology, optical imagery and image analysis technology.Operating personnel only need product to be measured is put on the belt, computer-controlled servo motor and optical image former harmony action are finished the conveying of product to be measured and are taken pictures, it can carry out Quality Detection to spaced product to be measured on the conveying belt automatically one by one, do not need manual intervention, efficiently solve tradition employing human eye detection with picking and placeing product carries out the defectives that the method detection efficiency is low, False Rate is high such as optical photographing detection by hand.
Be that example specifies its application with Quality Detection below to cell phone keyboard:
The keyboard quality problem can be divided into two big classes: the first kind is button misloading (generally being caused by batch mixing), the upside-down mounting on the keyboard; Second class is the surface blemish on the button in the keyboard,, printing position offset, cut, bubble bad, collapse angle etc. as the printing of: character, wherein bad, the printing position offset personnel selection eye of character printing can be found, cut, bubble, collapses the angle and will very carefully could find with human eye.The button misloading mainly contains two kinds of situations: the different key misloading in the same model keyboard, the button misloading between the different model keyboard.Different key misloading in the same model keyboard is generally apparent in view, it is bigger that feature on the button generally all differs, and during button misloading between the different model keyboard, is to cause with batch mixing between a kind of different editions of model keyboard basically, it is very little that feature on the button generally all differs, and is difficult to distinguish.
Detect and require:
Detection accuracy
Detection accuracy can be described with two parameters, " false determination ratio ", " False Rate ".
" misjudgement "--defective products is judged as non-defective unit;
" erroneous judgement "--non-defective unit is judged as defective products;
All and keyboard generate processing and relevant enterprise all requires keyboard that first kind quality problem can not be arranged, i.e. button misloading, upside-down mounting.Require detector should be able to detect the keyboard that all contain first kind quality problem accurately.General require " false determination ratio " is zero; " False Rate " is less than 5/1000ths.
Often require keyboard that the second class quality problem, i.e. keytop flaw can not be arranged to the higher relevant enterprise of keyboard quality requirements.General require " false determination ratio " is less than one of percentage; " False Rate " is less than 5 percent.The judgement critical value of the second class quality problem all requires adjustable.
Requirement to detection speed is basic per minute 30-70.
There are different requirements in different enterprises, and the requirement that has is shunted automatically, and the requirement that has is manually shunted.
Hardware performance requirement to detector
Generally all require and can work in 24 hours, noiselessness during detector work, energy consumption is low, and failure rate is lower than 1 time/100 days, and the detector working environment is keyboard production or processing site, in any case, can not injure operating personnel and peripheral equipment.
It is simple to write the detection formula, and general requirement can be set up the detection formula of a new keyboard in 10 minutes; To detecting the convenient management of formula, for example: on a machine, set up and detect formula, can on many machines, use; Possess testing result analysis and report capability, can be with combining defective products; Software is stable, and is simple to operate, and abundant detector debug function is provided.
Testing process: at first, extract a standard component and make sample, under camera, open light source, adjust the position of sample, make image reach the effect of the most clear, standard.Identify key element then, file;
Start conveying mechanism, product to be measured is placed on the mark position of conveying belt, it is accurate especially not need, and can allow 1mm with interior deviation, near the mark the workpiece spacing that the every operation of conveying belt motor is set is promptly sought;
After product to be measured put in place, the front light-source system was unlocked, and system stability behind the 50ms, camera begin to take pictures;
Take pictures after the imaging, the image that image analysis system in the computing machine will newly obtain is put in order Zhang Xuanzhuan and is cut apart, and the method during according to sampling is extracted relative key element, this key element and the key element that extracts from sample are compared, thereby judge it is non-defective unit or defective products.
Claims (3)
1, a kind of continuous-flow type Machine Vision Detection instrument comprises the imaging worktable that is installed on the frame, it is characterized in that also comprising:
The product conveyor structure, this mechanism is installed on the described frame, it comprises conveying belt, stepper motor or servomotor and motor driver, motor driver drive stepping motor or servomotor running, drive conveying belt and intermittently move, the product to be measured on the conveying belt is accurately delivered to the imaging worktable one by one;
Optical image former, it is installed on imaging worktable top, is used to obtain the image of the product to be measured on the imaging worktable;
Light source, it is installed on imaging worktable front upper place, and when optical image former obtained the image of product to be measured, light source was from this product to be measured of product to be measured front irradiation;
Computing machine, it is connected with optical image former, gathers the image that optical image former obtains, and carries out the analyses and comparison of product image to be measured and sample image, thereby differentiate the quality of product to be measured; Computing machine also is connected with the motor driver of product conveyor structure, control travelling belt and optical image former harmony action.
2, continuous-flow type Machine Vision Detection instrument according to claim 1, it is characterized in that: described light source is made up of the light emitting diode of a plurality of high brightness.
3, continuous-flow type Machine Vision Detection instrument according to claim 1, it is characterized in that: described optical image former is an optical camera.
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| CN 200620014167 CN2932377Y (en) | 2006-06-08 | 2006-06-08 | Flow-type machine visual detector |
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| CN 200620014167 CN2932377Y (en) | 2006-06-08 | 2006-06-08 | Flow-type machine visual detector |
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| CN2932377Y true CN2932377Y (en) | 2007-08-08 |
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Cited By (20)
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| CN101957196A (en) * | 2010-07-15 | 2011-01-26 | 上海大学 | Machine vision based automatic detection device of anastomat |
| CN102156269A (en) * | 2011-03-07 | 2011-08-17 | 中国科学院地质与地球物理研究所 | Automation magnetic susceptibility instrument capable of measuring long core, measurement method and placing support thereof |
| CN102218406A (en) * | 2011-01-04 | 2011-10-19 | 华南理工大学 | Intelligent detection device of defects of mobile phone outer shell based on machine vision |
| CN102494625A (en) * | 2011-11-22 | 2012-06-13 | 吴江市博众精工科技有限公司 | Laser mechanism rotating module |
| CN102494624A (en) * | 2011-11-22 | 2012-06-13 | 吴江市博众精工科技有限公司 | Laser adjustment module |
| CN102636494A (en) * | 2012-03-31 | 2012-08-15 | 苏州千兆自动化科技有限公司 | Vision detection system and detection method |
| CN102841103A (en) * | 2011-06-23 | 2012-12-26 | 神讯电脑(昆山)有限公司 | Keyboard appearance detection apparatus and method thereof |
| CN103033516A (en) * | 2011-10-10 | 2013-04-10 | 靖江市永盛光电科技有限公司 | Automatic conductive adhesive key detection equipment |
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| CN105372250A (en) * | 2015-12-14 | 2016-03-02 | 重庆远创光电科技有限公司 | Ceramic part vision detection system |
| CN105817430A (en) * | 2016-03-29 | 2016-08-03 | 常熟理工学院 | Product detection method based on machine vision |
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| CN106403815A (en) * | 2016-08-31 | 2017-02-15 | 无锡信欧光电科技有限公司 | Optic-mechanical-electric combined equipment |
| CN106501263A (en) * | 2015-09-08 | 2017-03-15 | 深圳市圆融精密电子有限公司 | A kind of online visual inspection machine of remote control finished product and detection method |
| CN108613981A (en) * | 2018-07-15 | 2018-10-02 | 中华人民共和国西安海关 | A kind of quick cotton grade detection device of pipeline system and detection method |
| CN109521025A (en) * | 2018-12-30 | 2019-03-26 | 深圳市杰普特光电股份有限公司 | Laser resistor trimming on-line checking mechanism and detection method |
| CN112499189A (en) * | 2020-11-17 | 2021-03-16 | 安徽信息工程学院 | Machine vision detection device |
| CN112763453A (en) * | 2021-01-11 | 2021-05-07 | 江苏闪码光机电科技有限公司 | Multi-factor real-time online detection device and method for ore bulk cargo in continuous conveying |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101957196A (en) * | 2010-07-15 | 2011-01-26 | 上海大学 | Machine vision based automatic detection device of anastomat |
| CN102218406B (en) * | 2011-01-04 | 2013-06-12 | 华南理工大学 | Intelligent detection device of defects of mobile phone outer shell based on machine vision |
| CN102218406A (en) * | 2011-01-04 | 2011-10-19 | 华南理工大学 | Intelligent detection device of defects of mobile phone outer shell based on machine vision |
| CN102156269A (en) * | 2011-03-07 | 2011-08-17 | 中国科学院地质与地球物理研究所 | Automation magnetic susceptibility instrument capable of measuring long core, measurement method and placing support thereof |
| CN102156269B (en) * | 2011-03-07 | 2013-08-07 | 中国科学院地质与地球物理研究所 | Automation magnetic susceptibility instrument capable of measuring long core, measurement method and placing support thereof |
| CN102841103A (en) * | 2011-06-23 | 2012-12-26 | 神讯电脑(昆山)有限公司 | Keyboard appearance detection apparatus and method thereof |
| CN103033516A (en) * | 2011-10-10 | 2013-04-10 | 靖江市永盛光电科技有限公司 | Automatic conductive adhesive key detection equipment |
| CN102494624A (en) * | 2011-11-22 | 2012-06-13 | 吴江市博众精工科技有限公司 | Laser adjustment module |
| CN102494625B (en) * | 2011-11-22 | 2013-10-02 | 吴江市博众精工科技有限公司 | Laser mechanism rotating module |
| CN102494624B (en) * | 2011-11-22 | 2013-10-02 | 吴江市博众精工科技有限公司 | Laser adjustment module |
| CN102494625A (en) * | 2011-11-22 | 2012-06-13 | 吴江市博众精工科技有限公司 | Laser mechanism rotating module |
| CN102636494A (en) * | 2012-03-31 | 2012-08-15 | 苏州千兆自动化科技有限公司 | Vision detection system and detection method |
| CN103673994B (en) * | 2012-09-18 | 2015-11-25 | 广达电脑股份有限公司 | Dynamic image capturing system |
| CN103673994A (en) * | 2012-09-18 | 2014-03-26 | 广达电脑股份有限公司 | Dynamic image capturing system |
| CN103776840A (en) * | 2012-10-25 | 2014-05-07 | 欧壹科技股份有限公司 | Automatic inspection method and device on production line |
| CN103383240A (en) * | 2013-06-26 | 2013-11-06 | 浙江工业大学 | Machine vision two-dimension detecting platform device |
| CN106290373A (en) * | 2015-05-26 | 2017-01-04 | 深圳市圆融精密电子有限公司 | A kind of silica gel push-button mould preparation visual inspection machine and detection method |
| CN106501263A (en) * | 2015-09-08 | 2017-03-15 | 深圳市圆融精密电子有限公司 | A kind of online visual inspection machine of remote control finished product and detection method |
| CN105372250A (en) * | 2015-12-14 | 2016-03-02 | 重庆远创光电科技有限公司 | Ceramic part vision detection system |
| CN105817430A (en) * | 2016-03-29 | 2016-08-03 | 常熟理工学院 | Product detection method based on machine vision |
| CN106403815A (en) * | 2016-08-31 | 2017-02-15 | 无锡信欧光电科技有限公司 | Optic-mechanical-electric combined equipment |
| CN108613981A (en) * | 2018-07-15 | 2018-10-02 | 中华人民共和国西安海关 | A kind of quick cotton grade detection device of pipeline system and detection method |
| CN109521025A (en) * | 2018-12-30 | 2019-03-26 | 深圳市杰普特光电股份有限公司 | Laser resistor trimming on-line checking mechanism and detection method |
| CN112499189A (en) * | 2020-11-17 | 2021-03-16 | 安徽信息工程学院 | Machine vision detection device |
| CN112763453A (en) * | 2021-01-11 | 2021-05-07 | 江苏闪码光机电科技有限公司 | Multi-factor real-time online detection device and method for ore bulk cargo in continuous conveying |
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