CN1313821C - Automatic detection meethod and system for smooth surface flaw - Google Patents

Automatic detection meethod and system for smooth surface flaw Download PDF

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CN1313821C
CN1313821C CNB2004100176289A CN200410017628A CN1313821C CN 1313821 C CN1313821 C CN 1313821C CN B2004100176289 A CNB2004100176289 A CN B2004100176289A CN 200410017628 A CN200410017628 A CN 200410017628A CN 1313821 C CN1313821 C CN 1313821C
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CN1563957A (en
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杨甬英
卓永模
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Zhejiang University ZJU
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Abstract

The present invention discloses a method and a system for automatically detecting smooth surface blemishes. A novel digital detection device which is suitable for large caliber sub-aperture scan scattering imaging and is aided by a computer is established according to blemish standards and the light scattering characteristics of the blemishes; a cold light source with multi-optical fibers and multi-azimuth layouts, which has Kohler illumination, is adopted, and the reflection type imaging of the scattering light of the detected surface blemishes is realized; the scattering light of the surface blemishes is collected and imaged on a CCD by an optical micro zooming system; when the detected surface has a large caliber, the computer controls an X and Y movable worktable table to scan a plurality of sub-apertures of the surface; a mathematic model which is recognized by a pattern and is based on mathematical morphology for blemish images and a software system calibrated by blemish dimensions are established. By adopting an objective digital evaluation system by the present invention, the accuracy of blemish detection is higher than the accuracy of visual subjective observation; by adopting automatic scan and a data processing method, detected work efficiency is greatly increased when a detected part has a large caliber. The present invention can be used for the identification, the classification, the calibration and the evaluation of a plurality of surface blemishes whose dimensions are more than a micrometer.

Description

The automated detection method of smooth surface defect and system thereof
Technical field
The present invention relates to a kind of automated detection method and system thereof of smooth surface defect.
Background technology
Optical engineering, large scale integrated circuit is made, related industry and national defence high-tech areas such as precision optical machinery, to some high-precision optics, the defect on the surface of materials such as metal has strict requirement, especially some defects that are used for the high-precision optical element surface of optical system are had more strict control, must carry out defect to the smooth surface of optical element according to defect engineering specification both domestic and external detects, because the scattering of defect will consume luminous energy greatly and reduce the laser damage threshold of optical element, cause the new damage of optical element, destroy rete, have a strong impact on the normal operation of optical system.At present in China, it all is to adopt visual method that defect is detected, incandescent lamp is gathered in tested element surface, human eye utilizes transmission and the method for reflection scattered light picture that produced by beauty defects of the observation of zonule one by one, finally make an artificial subjective roughly quantitative conclusion, judge whether it is specification product, artificial like this visualization assessment causes the accuracy that detects low because subjective factor is got involved; Simultaneously heavy-calibre element is detected, visualization efficient is low.The closely-related standard of defect international standard and tested surface has: 5/N * A; LN " * A "; EA , wherein N * A characterizes the number of defective and the square root of area; LN " * A " represent the cut symbol, allow length and width; EA  represents the ductility of edge damage and edge chips.Since the yardstick of defect can from several microns as pit to tens micron as the cut width etc., must carry out amplification detection by optical microscope system, the visual field of microscopic system can not be very big, and the bore of the detection of present tested element often can be a hundreds of millimeter even bigger.
Smooth surface defect detection to precision both at home and abroad has many methods, and be according to defect the different scattering properties of light to be differentiated mostly: the most basic and commonly used is visual method, observes by visual or magnifier, and defect is bright and resembles or secretly resemble by distinct methods; Also have the high-pass filtering imaging method, promptly adopt the special light hurdle, make defect scattered light imaging, can observe bright elephant the on the dark background with high frequency composition; It is various that (Total Integral Scatter, TIS) scanning scattering microscope utilizes small-bore laser beam and hemisphere to collect scattered light and detects the surface, and digitizing based on full integral scattering technology TIS.Except that the light scattering imaging, utilize laser diffraction spectrogram identification the carrying out scanning imagery of defect in addition; The contourgraph of laser interference imaging etc.These methods have the reference part, but at the digitizing evaluation system that solves the heavy caliber beauty defects many deficiencies are arranged all: the uncertainty of visualization, poor efficiency; The disunity of pick-up unit light source and system and international standard; Too little detection bore; Defect can't precise calibration or the like.Therefore how according to the defect engineering specification of international ISO10110-7 heavy-calibre element being carried out accurate, quantitative, the efficient objectively detection and the digitizing evaluation of robotization, is the problem of a required urgent solution of related industry really.
List of references
1)Jukka?Livarinen,“Surface?defect?detection?with?histogram-based?texturefeatures”,SPIE?vol.4197,P140-145,(2000)
2)Jrg?Steinert,Stefan?Gliech,“Advanced?methods?for?Surface?and?subsurfacedefect?characterization?of?optical?components”,SPIE?vol.4099,P290-298,(2000)
3)J.M.Elson,H.E.Bennett,and?J.M.Bennett,“Scattering?from?optical?surface”,inApplied?Optics?and?Optical?Engineering,vol.VII,P191-244,Chapter?7.R.R.Shannonand?J.C.Wyant,e?d.Academic?Press,New?York(1979)
Summary of the invention
The automated detection method and the system thereof that the purpose of this invention is to provide a kind of smooth surface defect.
The automated detection method of smooth surface defect: adopted the cold light source with cola illumination of many optical fiber position angle layout, realized the reflective imaging of the scattered light of defect; The scattered light that the beauty defects edge brings out is collected and is imaged on the CCD through optical microphotograph zoom amplification system; When tested surface was heavy caliber, X, Y table translation that computer control can be carried out sub-aperture scanning obtained surperficial a plurality of sub-aperture scannings, obtain unified defect view data; Set up the defect image based on the mathematical model of the pattern-recognition of mathematical morphology and the software architecture of defect calibration.
The automated detection system of smooth surface defect has the optical microphotograph zoom system, pancreatic system successively, light source, scanning workbench and image acquisition and data handling system, the optical microphotograph zoom system, pancreatic system has CCD successively, varifocal micro-amplification system, light source has incandescent light source successively, the optical fiber that angles of azimuth is arranged, the cola illumination head, fiber angle is adjustable, scanning workbench has the X of sub-aperture scanning successively, Y worktable driving circuit, X, the motor of Y scanning direction, X, the Y scanning workbench, the bottom that is plane was seized in scanning workbench is provided with dark background, and image acquisition and data handling system have watch-dog, image capturing system, computing machine, computer digital mode treatment system.
Advantage of the present invention: the present invention is according to the defect engineering specification of smooth surface, the digitizing detection method and the system that are suitable for the reflective imaging of heavy caliber sub-aperture scanning scattered light have been set up: adopted many optical fiber cold light source cola lighting system, be not heated in the tested element testing undeformed, imaging is clear can effectively accept the beauty defects scattered light, obtains the desirable defect image that view data is handled that is easy to; But method and the software architecture of assessing precise calibration defect yardstick at the mathematical model and the classification based on the mathematical morphology pattern-recognition of defect dispersion image have been developed; Adopted objective digitizing evaluation system, the accuracy that defect is detected is higher than visual subjective observation far away; Adopt automatic scanning and data processing method, when measured piece is heavy caliber, improved the work efficiency that detects greatly.The present invention is a brand-new system that can carry out the detection and the digitizing evaluation of accurate, quantitative, an efficient objectively robotization to the surface of different bore elements.
Description of drawings
Fig. 1 is the automated detection system block diagram of smooth surface defect;
Fig. 2 is the image that utilizes the reflective imaging of scattered light of the smooth surface defect that Fig. 1 device obtains;
Fig. 3 is pattern-recognition and the process flow figure that the image digitazation of smooth surface defect detects;
X, Y direction sub-aperture scanning synoptic diagram when Fig. 4 is the heavy caliber detection.
Embodiment
The automated detection system of smooth surface defect has the optical microphotograph zoom system, pancreatic system successively, light source, scanning workbench and image acquisition and data handling system, the optical microphotograph zoom system, pancreatic system has CCD 1 successively, varifocal micro-amplification system 2, light source has incandescent light source 8 successively, the optical fiber 9 that angles of azimuth is arranged, cola illumination head 5, fiber angle is adjustable 3, scanning workbench has the X of sub-aperture scanning successively, Y worktable driving circuit 14,15, X, the motor 16 of Y scanning direction, 17, X, Y scanning workbench 18, be provided with dark background 7 in scanning workbench, image acquisition and data handling system have watch-dog 11, image capturing system 10, computing machine 12, computer digital mode treatment system 13.
Incandescent light source 8 is for Halogen lamp LED and adopt the cola illumination.Computer digital mode treatment system 13 as accompanying drawing 3 is: image imports, utilizes medium filtering to suppress random impulsive noise; Utilize gray scale linear transformation efficiently effectively to extract the target signature image; Realize image segmentation and binaryzation; Remove redundant information; Adopt the erosion operation of morphology refinement to make the lines refinement be convenient to subsequently line tracking; Set up the defect java standard library; Sort out and estimate and calibration.The optical fiber 9 that angles of azimuth is arranged is: the array of angles of azimuth cold light source is arranged.
The optical measurement principle of the automated detection system of smooth surface defect
The prerequisite that the present invention all should adopt scattered light to detect according to the engineering specification defect is set up suitable heavy caliber and aperture scanning is scattering into the system that picture detects.Be the system layout of pick-up unit as shown in Figure 1, computing machine is described in the lower part to the mode identification method and the process of defect.Detected element 6 is placed on an X that heavy caliber can be divided into some sub-aperture scannings, the Y worktable 18, is dark background 7 in the detected element bottom, and scanning can be controlled by computing machine 12.Adjustable 3 of optical fiber source 9 usefulness are with the specific tested element of angular illumination, incident light is through being positioned at lower surface on the optical system object plane or upper surface reflection back from other end outgoing, and 4 one-tenth α corner reflections of the scattered light that this beauty defects edge brings out are after varifocal micro-amplification system 2 collections and imaging on the CCD 1.Monitoring when image one tunnel supplies to detect through watch-dog 11, computer patterns disposal system 13 is sent the view data that collects into through image capturing system 10 in another road.By optical scattering photoimaging theory as can be known, constitute the reflective image of bright defect scattered light on the dark background thus, because character such as this α angle and the defect marginal ditch angle of the v-groove have substantial connection, so adopt the layout of many optical fiber angles of azimuth, become angle α to incide plane was seized with optical axis, can guarantee so all can obtain the reflection of light of the surface scattering clearly image of defect no matter how the marginal ditch angle of the v-groove of defect changes.Realize the digitizing evaluation of computing machine to the defect Flame Image Process, very crucial a bit is exactly acquisition can be suitable for the defect image that computer patterns is discerned, and accompanying drawing 2 is the digital picture that the defect of cut and pit is contained on surface that the present invention collects with accompanying drawing 1 described device, the gray-scale value contrast of background and defect target obviously is very suitable for the image and the data processing of computing machine.When tested surface is heavy caliber, computing machine 12 controls can be carried out the X of sub-aperture scanning, the driving circuit 14,15 of Y worktable, make X, Y motor 16,17 drive worktable 18 and carry out a plurality of sub-aperture scannings of X, Y direction, thereby can obtain unified defect view data.
Identification of defect image model and feature extraction mathematical model
The present invention has set up mathematical model and the process software of defect image based on the pattern-recognition of mathematical morphology, has set up the evaluation system of a complete digitizing standard.It has mainly finished identification processing and feature extraction to the defect image information; The classification assessment and the calibration of defect.
(1) realizes defect image model identification mathematical model and feature extracting method
The defect image model model of cognition of setting up among the present invention is the key link that digitizing is estimated.As from the defect image of accompanying drawing 2, extracting the information relevant with the defective cut, to utilize digital morphological to learn and carry out image segmentation, feature (as defect shape, size, length, area etc.) is extracted, multiple Flame Image Process work such as line tracking.Utilize the disposal route of mathematical morphology, binary image is carried out optimization process, finish the identification of defect, accompanying drawing 3 is realizes defect image model identification mathematical model and feature extracting method process flow diagram.
Medium filtering
The defect image because the impulsive noise that each link produces in some systems at random in order to remove the noise that some do not belong to defect, is utilized medium filtering or other filtering method, effectively suppresses noise as shown in Figure 2.
The gray scale linear transformation
Defect feature and background separation be come, it must utilize image segmentation.Adopt one efficiently disposal route be the gray scale linear transformation.Output and input gray level satisfy:
G Go out=a iG Go intoI=1,2 ..., n (1)
A in the formula iBe transformed value, a i>1 is grey level stretching, and contrast strengthens.The gray scale linear transformation can be carried out in segmentation, and the gray scale of defect feature and background is drawn back greatly, has effectively extracted the target signature image.
Image segmentation and binaryzation
Image segmentation is a very important image analysis technology.After grey level stretching, both separate substantially at gray scale, and histogram must be " L " type, and promptly the gray-scale value probability of background is much larger than the gray-scale value of defect target.Optimal threshold search method in utilization and the shape Region Segmentation Algorithm.This data model is according to known image probability density function expression-form, when the probability density of background and defect target is respectively p b, p o, can solve and make target cut apart the optimal threshold T of total error probability minimum:
T = ( μ b + μ 0 ) 2 + σ 2 μ b + μ 0 ln ( p 0 / p b ) - - - ( 2 )
μ in the formula b, μ 0Be respectively the average optical density of background and target; σ is the standard deviation of noise, as the separatrix of cutting apart background and target, to this method of imagery exploitation, makes background and target optimal segmentation with T.
Binaryzation is based on the basis of image segmentation, is the boundary with background and target according to being worth most threshold value T, respectively background and target are made as 0 and 1 (help like this accelerate in the morphology processing speed), binaryzation can make the realization of algorithm greatly simple, and to following removal redundant information, applied morphology carries out feature extraction to image and provides the foundation.
Remove redundant information
Heavy caliber scanning detects, and has hundreds and thousands of sub-apertures.Whether there is defect information in each sub-aperture, screened and carry out next step computing.Defective is stochastic distribution in the aperture, to each connected region zoning size (promptly to target pixel summation), whether judges in certain sub-aperture defectiveness or little to ignoring, with quickening subsequent operation speed after binaryzation.
The morphology refinement
The morphology refinement is a kind of main image processing method, to above-mentioned binary image, adopts morphologic erosion operation and hits the miss computing, carries out refinement, is convenient to line tracking subsequently, to carry out length computation.In the defect standard lines length L there is special tolerance limit requirement.
To the defect image A of a frame binaryzation, the setting structure element is its corrosion E to A of S, and mathematical expression is:
E = A ⊗ S = { ( x , y ) | S x , y ⊆ A } - - - ( 3 )
And the normally set of structural element origin position of E.Relatively being fit to program by the displacement computing realizes.By erosion operation lines are attenuated.But, when eroding to certain depth, lines are eroded than narrow, same lines are divided into two sections.Therefore in order compensating its defect, to keep the connectedness of target lines, correctly to reflect the rationality (, then defective, and produce flase drop when being separated into the two-lines bar) of plane was seized lines length and element as the long 40mm of surpassing of lines.Erosion operation improved promptly judge earlier, corrode and keep the connective thinning method that adopts of former lines, its mathematical definition is
AoS = A - A ⇑ S - - - ( 4 )
In the formula Be to hit the miss computing, it is defined as:
A ⇑ S = ( A ⊗ S 1 ) I ( A ‾ ⊗ S 2 ) - - - ( 5 )
S is by two disjoint structural element S in the formula 1, S 2Form, A is the supplementary set of A.Hit or miss transform can keep the connectedness of target lines in the following formula.When specific procedure is implemented, be provided with Rule of judgment, meet then and peel off, otherwise then keep.After refinement, the different thicknesses lines are refined as the lines that single pixel is wide, can calculate the physical length of cut.
Line tracking
After refinement, removed and the irrelevant information of cut lines length, made the cut that is detected high-visible." 1 " is target, and " 0 " is no information.Therefore, in routine processes, exploring with target pixel 1 to 8 neighborhood direction.Set priority, track explored in record, lines all searched for finish.When operation, can utilize multiple method for limiting to finish the line tracking record, and the course of the initial and terminal point of lines is the lines length L.
Differentiating for characterize edge chips with A , is that the physical pore size edge with plane was seized is the boundary, and there is fixed size in the aperture, is stored in advance and is aided with scanning by computing machine and determine, also can utilize the aforesaid method such as image segmentation of doing according to the edge gray feature to obtain.
(2) sub-aperture scanning system
The beauty defects of heavy-calibre element detects, and is that full aperture is progressively implemented sub-aperture scanning, implements splicing during last Flame Image Process.Set up the translation that utilizes the XY both direction as shown in Figure 4 and obtained surperficial sub-aperture scanning, wherein A 11, A 12Deng being sub-aperture, the straight line running fix that moves guiding systems has at present reached the bearing accuracy (promptly less than CCD a pixel value) of micron, sub-micron.For the sub-aperture scanning of lens, can utilize the beat scanning of plane was seized (centre of sphere) simultaneously, sphere is carried out the full aperture imaging around meridian ellipse and sagittal surface.
(3) comparison of defect width criteria and evaluation
The image that detection system of the present invention produces is to detect with bright elephant the on the dark background, therefore, for the physical size size of correct evaluation defect, can set one group of defect standard groove and carry out the actual detection calibration.
The substrate of defect standard and width are selected:
Owing to measure,, make the image of detection and the standard scale can be consistent because enlargement factor difference at every turn so will correctly will resemble the face size conversion to the object plane physical size, is promptly obtained a correct enlargement factor with a varifocal optical microscope system.Therefore adopted the optical glass substrate, made the cut groove of different in width by lithography, width is (length unanimity) from several microns to tens microns; From technologies such as polishings as can be known, the line that particulate marks from the teeth outwards generally is " V " shape, and the scattered light that produces along the edge to be exactly CCD resemble the bright target that forms on the face resembles.These width are to utilize equipment such as step instrument, contourgraph, accurately ask for.When detecting, this on-gauge plate is called contrast when storage supplies calibration as built-in function.
In setting up standard cut groove,, suitably select the substrate of different reflectivity according to different measured targets.Research by analysis, the calibration of the reflective dark ground illumination image of usefulness native system is better than the image comparison of transmission-type, and by the groove calibration, can guarantee the accuracy of its detection fully, and be suitable for any reflecting element surface.
The evaluation of defect and classification:
The classification of defect is to be based upon on the image model base of recognition, handles and the database of the geometric configuration of different defects such as all kinds of cuts in the full aperture, defective, broken limit has been set up in calibration through the scanner uni a series of images.According to the engineering specification of industry, the number of picture elements of defect of identification is carried out mathematical computations, calculate the length of cut and width, the square root of pit area, the length of edge damage etc.
The present invention has set up the novel scanning scattering image-forming detecting system that is suitable for heavy caliber, high-precision surface according to international defect engineering specification; Set up a comprehensive, scientifical evaluation heavy caliber of energy and detected the mathematical model of scanning imagery and the mode identificating software system of Flame Image Process; Can promote domestic and international beauty defects evaluation to develop greatly to the digitizing reference direction.
Embodiment 1
The automated detection method of smooth surface defect of the present invention and system as shown in Figure 1, when tested surperficial bore hour, detected element 6 is placed on the worktable 18, is dark background 7 in the detected element bottom.But adjustment rack 3 makes optical fiber source (light source be incandescent lamp and can carry out light intensity regulating) 9 with the specific tested element of angular illumination, from other end outgoing, collected and image on the CCD 1 by varifocal optical microphotograph amplification system 2 after then becoming the α corner reflection by the part scattered light that the beauty defects edge brings out after being positioned at the surface reflection on the optical system object plane for incident light.Monitoring when image one tunnel supplies to detect through watch-dog 11, computer patterns disposal system 13 is sent the view data that collects into through image capturing system 10 in another road, machine carries out a series of pattern-recognition digitized processing of defect image and compares with the groove of standard as calculated, the width that can draw the long lines of accompanying drawing 2 is about 42 microns, and length is about 7 millimeters.
Embodiment 2
When tested surperficial bore is big, the automated detection system of the smooth surface defect of employing as shown in Figure 1, the laying and adjust of detected element as embodiment 1.When tested surface is heavy caliber, can carry out scan mode as shown in Figure 4, the X of computing machine 12 control sub-aperture scannings, the driving circuit 14,15 of Y worktable, make X, Y motor 16,17 drive worktable 18 and carry out a plurality of sub-aperture scannings of X, Y direction, thereby can obtain unified defect view data.And finish sub-aperture stitching according to the coordinate of each scan aperture.Heavy caliber detects and must be made up of a plurality of sub-aperture stitchings, so data volume is very big, for amount of compressed data, can remove the sub-aperture of no defect information, satisfies the accuracy of defect measurement and the demand between the processing speed simultaneously.Final can carry out and obtain the measurement result identical equally with embodiment 1.

Claims (4)

1, a kind of automated detection method of smooth surface defect is characterized in that adopting the cold light source with cola illumination of many optical fiber position angle layout, realizes the reflective imaging of the scattered light of defect; The scattered light that the beauty defects edge brings out is collected and is imaged on the CCD through optical microphotograph zoom amplification system; When tested surface was heavy caliber, X, Y table translation that sub-aperture scanning is carried out in computer control obtained surperficial a plurality of sub-aperture scannings, obtain unified defect view data; Image imports, utilizes medium filtering to suppress random impulsive noise; Utilize gray scale linear transformation efficiently effectively to extract the target signature image; Realize image segmentation and binaryzation; Remove redundant information; Adopt the erosion operation of morphology refinement to make the lines refinement be convenient to subsequently line tracking; Set up the defect java standard library; Sort out and estimate and calibration.
2, a kind of automated detection system of smooth surface defect, it is characterized in that: it has the optical microphotograph zoom system, pancreatic system successively, light source, scanning workbench and image acquisition and data handling system, the optical microphotograph zoom system, pancreatic system has CCD (1) successively, varifocal optical microphotograph amplification system (2), light source has incandescent light source (8) successively, the optical fiber that angles of azimuth is arranged (9), cola illumination head (5), fiber angle is adjustable (3), scanning workbench has the X of sub-aperture scanning successively, Y worktable driving circuit (14), (15), X, the motor of Y scanning direction (16), (17), X, Y scanning workbench (18), be positioned at the dark background (7) that plane was seized (6) on the scanning workbench and bottom are provided with, image acquisition and data handling system have watch-dog (11), image capturing system (10), computing machine (12), the digitizing mode treatment system (13) of computing machine defect, described incandescent light source (8) is for Halogen lamp LED and adopt the cola illumination.
3, the automated detection system of a kind of smooth surface defect according to claim 2 is characterized in that described computer digital mode treatment system (13) is: image imports, utilizes medium filtering to suppress random impulsive noise; Utilize gray scale linear transformation efficiently effectively to extract the target signature image; Realize image segmentation and binaryzation; Remove redundant information; Adopt the erosion operation of morphology refinement to make the lines refinement be convenient to subsequently line tracking; Set up the defect java standard library; Sort out and estimate and calibration.
4, the automated detection system of a kind of smooth surface defect according to claim 2, it is characterized in that the optical fiber (9) that described angles of azimuth is arranged is: the array of angles of azimuth cold light source is arranged.
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CN113447489B (en) * 2021-06-28 2022-12-13 上饶市中科院云计算中心大数据研究院 Method and device for removing influence of halation in surface defect detection of large-curvature optical lens

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1074293A (en) * 1992-07-11 1993-07-14 浙江大学 The laser detection method and the detector thereof of object's surface defects
WO1998005945A1 (en) * 1996-08-01 1998-02-12 Michael John Phillips Inspection apparatus
JP2004109068A (en) * 2002-09-20 2004-04-08 Nippon Steel Corp Movable metal material flaw type discrimination device
CN2729708Y (en) * 2004-06-22 2005-09-28 浙江大学 Automatic detection system for defect on smooth surface

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1074293A (en) * 1992-07-11 1993-07-14 浙江大学 The laser detection method and the detector thereof of object's surface defects
WO1998005945A1 (en) * 1996-08-01 1998-02-12 Michael John Phillips Inspection apparatus
JP2004109068A (en) * 2002-09-20 2004-04-08 Nippon Steel Corp Movable metal material flaw type discrimination device
CN2729708Y (en) * 2004-06-22 2005-09-28 浙江大学 Automatic detection system for defect on smooth surface

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