CN1156708C - Method and system for measuring wool fiber fineness measurement - Google Patents
Method and system for measuring wool fiber fineness measurement Download PDFInfo
- Publication number
- CN1156708C CN1156708C CNB021000565A CN02100056A CN1156708C CN 1156708 C CN1156708 C CN 1156708C CN B021000565 A CNB021000565 A CN B021000565A CN 02100056 A CN02100056 A CN 02100056A CN 1156708 C CN1156708 C CN 1156708C
- Authority
- CN
- China
- Prior art keywords
- fiber
- fineness
- measuring
- edge
- image
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- 239000000835 fiber Substances 0.000 title claims abstract description 116
- 238000000034 method Methods 0.000 title claims abstract description 47
- 238000005259 measurement Methods 0.000 title claims abstract description 30
- 210000002268 wool Anatomy 0.000 title claims abstract description 16
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 23
- 230000008569 process Effects 0.000 claims description 21
- 238000003384 imaging method Methods 0.000 claims description 11
- 238000000605 extraction Methods 0.000 claims description 9
- 238000005286 illumination Methods 0.000 claims description 8
- 238000000691 measurement method Methods 0.000 claims description 6
- 241000276498 Pollachius virens Species 0.000 claims description 5
- 230000003287 optical effect Effects 0.000 claims description 4
- 238000000879 optical micrograph Methods 0.000 claims description 4
- 238000010276 construction Methods 0.000 claims description 3
- 238000006243 chemical reaction Methods 0.000 claims description 2
- 238000009826 distribution Methods 0.000 abstract description 7
- 239000004753 textile Substances 0.000 abstract description 5
- 241001465754 Metazoa Species 0.000 abstract description 3
- 210000000050 mohair Anatomy 0.000 abstract description 3
- 230000008901 benefit Effects 0.000 abstract description 2
- 230000033001 locomotion Effects 0.000 description 12
- 238000004364 calculation method Methods 0.000 description 9
- 230000008859 change Effects 0.000 description 9
- 238000010586 diagram Methods 0.000 description 7
- 239000000284 extract Substances 0.000 description 6
- 238000012545 processing Methods 0.000 description 4
- 230000004075 alteration Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 210000000085 cashmere Anatomy 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000001914 filtration Methods 0.000 description 2
- 239000012634 fragment Substances 0.000 description 2
- 230000008676 import Effects 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 238000003199 nucleic acid amplification method Methods 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 238000011000 absolute method Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 210000001747 pupil Anatomy 0.000 description 1
- 238000001303 quality assessment method Methods 0.000 description 1
- 238000013441 quality evaluation Methods 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 238000005096 rolling process Methods 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Images
Landscapes
- Treatment Of Fiber Materials (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The present invention discloses a method and a system for measuring the fineness of wool fibers, which relates to a method and equipment for measuring the fineness of wool, pashm, mohair and other textile fibers with round sections. A digital camera (CCD) is used for converting amplified fiber images into digital images which are transmitted into a computer to be processed in real time so as to obtain fiber outlines, and the fineness of each single fiber is calculated; the data, such as average fineness of all measured fibers, fineness distribution, etc., are counted. Because the present invention uses a common light source, an algorithm and software for rapidly extracting fiber hems and measuring the fineness are designed. Thus, the present invention has the advantages of easy operation, automatic continuous measurement, many measurement parameters and accurate and reliable result, and has the characteristics that the cost can be reduced, the measuring precision is high, and the measuring speed is high. The animal fibers within the measuring range of 4 to 300 mu m can be measured, the measuring repetition precision is (+/-) 0.135 mu m, and the measuring speed is 140 fibers per second.
Description
Technical field
The invention belongs to the precision measuring instrument technical field, particularly a kind of diameter measurement method and apparatus that comprises the textile fibres of wool, cashmere, mohair yarn and other round section is widely used in the quality management of textile import and export and production industry.
Background technology
It is one of most important parameters of estimating the lint quality that the average fineness of fine animal fibre and fineness distribute, and has important use value in textile industry.In the method commonly used at present, the microprojection instrument measurement method is a kind of absolute method of measurement, and is simple and easy directly perceived; But single surveying work efficient is very low, and manual personal error is big; Though the air-flow method fast, still can only obtain mean diameter and can not obtain reflecting that the fineness of quality distributes; Adopt the laser fineness analytic approach of laser diffraction principle development to realize all automatic measurement, measuring speed is fast, the measurement data amount is big, the result is objective, but the service condition of complex structure, instrument requires height, and is difficult in maintenance.
At present available technology adopting optical microphotograph imaging method, by graphical analysis realize wool and suede fibrid quality assessment, can measure multiple quality evaluation indexs such as comprising mean diameter, standard deviation, the coefficient of variation, fibre fineness distribution, all automatic measurement, speed are soon, the measurement data amount is big, the result is objective and accurate.The OFDA100 type optical fiber diameter analyser that adopts the maturing apparatus of this method development to have only Australian Uster company to produce at present, this Instrument Illumination system adopts special light source, drive system to place worktable one side, adopts simulation CCD to be equipped with that image pick-up card obtains fibre image, Survey Software is used dedicated monitor based on dos operating system, fibre image echo.This instrument has following shortcoming: use special light source, improved system cost, and increase the maintenance difficulties of system; Drive system places worktable one side to make the worktable discontinuity, can influence accuracy of platform and stability; Use simulation CCD to increase the number of times of signal transformation, strengthen image fault; Owing to, cost an arm and a leg from external import.
Summary of the invention
The purpose of this invention is to provide a kind of wool fiber diameter measurement method and system, make it can not only realize full-automatic continuous coverage, and can further improve measuring accuracy and measuring speed, reduce cost.
The present invention is achieved through the following technical solutions: a kind of wool fiber diameter measurement method is characterized in that this method comprises the steps:
(1) obtains fibre section, amplify fibre image by optical microscope system;
(2) adopt digital camera CCD to convert fibre image to digital picture;
(3) read digital picture by computing machine, and carry out Flame Image Process and measure calculating, measure calculating and comprise fiber edge extraction, the identification that fiber is little section, the calculating of little section fineness of fiber; Described fiber edge is extracted the algorithm that adopts binaryzation-edge to follow the tracks of, the method of little section separation-condition judgment of fiber edge is adopted in little section identification of described fiber, thereby described fibre fineness adopts the sub-pixel positioning method to determine that edge point position realizes the calculating of fibre fineness in calculating;
(4) worktable x, y direction feeding employing are that control module, digital camera are the closed loop control method of feedback assembly with the computing machine;
(5) table feed repeats the step of 2--4 to the next position, realizes all automatic measurement of wool fiber fineness.
A kind of wool fiber diameter measurement system that realizes above-mentioned measuring method, mainly comprise the optical microscope system that constitutes by illuminator and micro-amplification system, image acquisition and disposal system, realize X, the worktable and the driving control system thereof of the feeding of Y both direction, measure annex, it is characterized in that described illuminator adopts ordinary light source and uses the Kohler illumination mode, image acquisition and disposal system comprise digital camera (CCD) and be equipped with to be handled image, the data computation and the computing machine of software for display as a result, this computing machine is connected with digital camera by the IEEE1394 interface.
Above-mentioned worktable adopts the monolithic construction of servomotor symmetric arrangement, and its worktable driving control system adopts by computing machine, digital-to-analog conversion, driving circuit, servomotor and the closed-loop control system formed as the operating position feedback assembly with digital camera.
Measuring principle of the present invention and method are as follows: the General layout Plan that adopts precision stage-optical microscope system-digital camera (CCD) Computer Processing.During concrete the measurement, at first fiber to be measured is cut section by cutter, on glass sheet, make print, again print is fixed on the worktable through the dispenser uniformly dispersing.Afterwards, start this system, worktable at first moves to the reference position of measurement, and system begins to measure, and worktable is according to the predefined mode of motion feeding of program; In the measuring process, fibre section images in digital CCD target surface through Liar, digital camera (CCD) is sent being converted into digital picture through the fibre image that amplifies into the Computer Processing terminal, computing machine is handled in real time to digital picture, obtain the fiber profile, all single fiber fineness in the computed image; In the process of table feed, the continuous images acquired of computing machine is handled, and adds up data such as all average fineness of measuring fiber, fineness distribution, is presented in real time on the screen with digital form or represented as histograms, finishes until measuring.After measuring end, worktable is got back to initial position, prepares to measure next time.
Native system is applicable to the textile fibres of wool, cashmere, mohair yarn and other round section, accurately provide the fibre fineness statistical measures of indexs such as comprising mean diameter, standard deviation, the coefficient of variation, shouting pain factor, applied range, measurement parameter is many, the result accurately and reliably; Because the present invention adopts ordinary light source, and designed algorithm and the software that adapts to fiber edge rapid extraction and diameter measurement, therefore the present invention not only has easy and simple to handle, automatically continuous coverage, measurement parameter is many, result's advantage accurately and reliably, and can reduce cost, have the measuring accuracy height, the characteristics that measuring speed is fast; Can measure the animal origin in 4～300 μ m measurement ranges, measure repeatable accuracy and can reach ± 0.135 μ m the measuring accuracy height; 140 fibers of measuring speed per second, continuous coverage automatically, measuring speed is fast, and is easy and simple to handle, in the employing/and English two kinds of working languages, the way of output is versatile and flexible, the functional reliability height.
Description of drawings:
Fig. 1 is a wool fiber diameter measurement system architecture schematic diagram.
Fig. 2-a is the Kohler illumination principle.
Fig. 2-b is the micro-imaging schematic diagram.
Fig. 3 is the image collection processing system fundamental diagram.
Fig. 4 is the Flame Image Process process flow diagram.
Fig. 5 is the edge extracting process flow diagram.
Fig. 6 is fiber identification process figure.
Fig. 7 is the fibre fineness calculation flow chart.
Fig. 8 is a worktable type of drive schematic diagram.
Fig. 9 is that workstation control system connects.
Figure 10 is the working table movement control flow chart.
Figure 11 is a sample feeding mode synoptic diagram.
Embodiment
Below in conjunction with accompanying drawing technical scheme of the present invention is described in detail:
The present invention mainly comprises precision stage, optical microphotograph imaging system, image acquisition and disposal system, Flame Image Process and Measurement Algorithm and measurement annex.Its measuring principle is as shown in Figure 1: the fibre section 3 on 1 pair of worktable 2 of illuminator provides even illumination, micro-little section on the fibre section 3 images in digital camera 5 target surfaces through micro-amplification system 4, digital camera 5 is being converted into digital picture through the fibre image that amplifies, computing machine 8 reads digital picture and handles in real time, obtain the fiber profile, calculate the single fiber fineness, and calculate data such as all average fineness of measuring fiber, fineness distribution, the coefficient of variation, realize measuring automatically.After instrument began test, according to the predefined mode of motion feeding of program, instrument constantly repeated said process to computing machine 6 simultaneously by D/A converter module 7, driving circuit 8, servomotor 9 Control work platforms 1, finishes until measuring.
The concrete structure of system's each several part and act on as follows:
Precision stage: realize the auto-feed campaign of X, Y both direction, the monolithic construction that adopts drive motor and worktable to join together, motor is symmetrically arranged in the worktable both sides, is made up of following parts: table slide, two V-arrangement ball roundlet arc straight line moving guide rail, rack and pinion drive mechanism and computer-controlled closed-loop control drive system (as shown in Figure 9).
Optical microphotograph imaging system: comprise illuminator and micro imaging system.Illuminator adopts ordinary light source, uses the Kohler illumination mode uniform visual field that obtains to throw light on.The optical principle of Kohler illumination system is shown in Fig. 2-a: by collecting lens 12, the light-emitting area that makes light source 11 becomes real image at object space focal plane 13 places of condenser, then, light source once as through condenser 14 in the place's imaging of microscopical entrance pupil, object is thrown light on.Simultaneously, adjustable aperture diaphragm 13 and field stop 14 can be set in illuminator, the aperture of illumination beam and the size of visual field are regulated.Micro imaging system is shown in Fig. 2-b: measuring object is positioned at object lens object space focal plane place accurately, and light becomes parallel beam by lens barrel after seeing through object lens, is positioned at unlimited distance (conjugate distance that is object lens is for infinitely great) through the object lens imaging.In parallel light path, add attachment objective, image on the CCD target surface.Imaging system adopt flat-field achromatic objective lens to the wool fiber sample amplify, imaging, to reduce the systematic error that aberration, aberration cause.
Image acquisition and disposal system: comprise digital camera (CCD), IEEE 1394 interfaces and be equipped with image processing software, computing machine.Digital camera directly converts the fibre image that amplifies to digital picture, has reduced the number of transitions of image in digitized process, reduces the distortion of picture signal to greatest extent; The IEEE1394 interface is used for the data-interface of digital ccd signal and computing machine, is the interface of present peripheral hardware and computer data transmission of digital image; Computing machine is handled the image that obtains, and carries out diameter measurement and calculating; Flame Image Process and Survey Software be based on Windows 98 operating systems exploitations, and friendly interface, interactivity are strong, the collection of Measurement Algorithm partial image, edge extracting and tracking, little section extraction and identification, four steps of diameter measurement, and measuring speed is fast, the measuring accuracy height.Its principle of work is as shown in Figure 3: the CCD camera is being converted into digital picture through the fibre image that amplifies; Computing machine is handled digital picture, obtains the fiber profile, calculates the single fiber fineness, and calculates the average fineness that all measure fiber.Because instrument requires image acquisition and handles and carry out in real time, therefore, requires algorithm should have high counting yield.For satisfying this requirement, Survey Software adopts the scheme of image acquisition and Flame Image Process concurrent working, descends the collection of piece image when handling image.Simultaneously, for improving image processing velocity, according to the characteristics of image and measurement parameter, designed the algorithm that adapts to fiber edge rapid extraction and diameter measurement: edge extracting one fiber is discerned a fineness and is calculated.The Flame Image Process flow process is as shown in Figure 4: at first gather fibre image, extract the fiber edge in the image then, discern little section of fiber again, calculate fibre fineness at last.
Flame Image Process and Measurement Algorithm: the fibre image of process object for having obtained, requirement can be calculated the fineness that obtains the fiber in the image fast, to improve the measuring speed of system.Mainly comprise following content: fiber edge extraction, the identification of fiber fragment and the calculating of fiber fragment fineness.Its algorithm flow is as shown in Figure 4: at first gather fibre image, extract the fiber edge in the image then, discern little section of fiber again, calculate fibre fineness at last.Fiber edge is extracted the algorithm adopted binaryzation-edge to follow the tracks of, and the method for little section separations-condition judgment of fiber edge is adopted in little section identification of fiber, thus fibre fineness calculate in employing sub-pixel positioning method determine that edge point position determines fibre fineness.
(1) edge extracting algorithm:
The edge extracting algorithm that the edge extracting algorithm adopts image binaryzation processing-edge to follow the tracks of.Algorithm flow such as Fig. 5, the detailed algorithm flow process is as follows:
At first, determine binary-state threshold, detailed process is as follows:
Computed image intensity profile, and normalized.
Eigenwert when the calculating gray scale is j, computing formula is as follows:
B[j] eigenwert when a gray scale is j
Hist[i] gray scale is that the pixel of i accounts for total pixel ratio.
Compare the gray feature value, the gray scale of getting the eigenwert maximum is the image binaryzation threshold value.
Secondly, binary image
The 3rd, determine the edge starting point: at regular intervals the image after the binaryzation is scanned, be the edge starting point when the gray-scale value of putting satisfies following condition.
Or
The 4th, search next marginal point: from a nGray[i-1, j] beginning, checkpoint nGray[i clockwise, j] the gray scale of eight neighborhood points, use nGray[i] represent.If the neighborhood point satisfies following condition, then be frontier point
With
The 5th, whether new marginal point the edge starting point: be that then end edge is followed the tracks of; Not, got back to for the 4th step, seek new marginal point.
At last, judging whether edge in the image is searched finishes: be to finish to search; Not, got back to for the 3rd step, search next closed edge.
(2) little section extraction algorithm of fiber:
Before little section of extraction fiber, must extract the edge of the different fibers in the same closed edge curve for little section earlier, this part mainly comprises the content of two aspects: fiber edge is separated, little section identification of fiber, algorithm flow such as Fig. 6.
Below, the content of this two aspect is compared detailed explanation.
1) fiber edge is separated:
In the closed edge curve, the catastrophe point on the curve is the best parameters of the different fiber edge of difference.Therefore, this paper differentiates the edge of different fibers by the catastrophe point of extracting curve.The extraction of catastrophe point adopts the relevant bonding position sudden change method of chain code to realize.
The related coefficient that the chain code correlation method distributes according to chain code in the neighborhood of the boundary curve point left and right sides is determined whether catastrophe point of marginal point, nChainCode[j] j chain code value of putting in the expression neighborhood, specific algorithm is as follows:
1. determine the neighborhood length M.
2. get the initial wheel profile.
3. contouring starting point.
4. the chain code distribution L in the neighborhood of a calculation level left side
1
L
nChainCode[j]＝L
nChainCode[j]+10≤j＜8 (8)
5. the chain code distribution R in the right neighborhood of calculation level
1
R
nChainCode[j]＝R
nChainCode[j]+10≤j＜8 (9)
6. calculate left and right neighborhood chain code distribution related coefficient, formula is as follows:
7. starting point whether: not, take off a point, got back to for the 4th step; Be to carry out further work.
8. seek the contour curve unique point: the chain code related coefficient is that the curve point of local minimum is the contour curve unique point.
9. judge curvilinear characteristic point unique point whether really: adopt direction sudden change method to judge, direction sudden change method is further judged the catastrophe point of having found out according to the variation of the left and right directions of point, determines whether it is the point of crossing of different fiber edge.In concrete realization, the left and right directions of point is represented with the direction that is judged between the breakpoint with certain point in the neighborhood of the left and right sides, is claimed that the change point that extracts in the chain code correlation method is a unique point.Direction sudden change method algorithm is as follows:
(1) gets first unique point (x of curve
1, y
1) for being judged to breakpoint.
(2) calculating is judged to number of edge points between breakpoint and the left unique point.
(3) if N the point that number of edge points greater than the N that ascertains the number, is got in the left neighborhood is calculation level, be calculation level otherwise get left unique point, calculation level is (x
1, y
1).
(4) calculate the left be judged to breakpoint to.Formula is as follows:
(5) calculating is judged to number of edge points between breakpoint and the right unique point.
(6) if N the point that number of edge points greater than the N that ascertains the number, is got in the right neighborhood is calculation level, be calculation level otherwise get right unique point.
(7) calculate the left be judged to breakpoint to.Formula is as follows:
(8) difference of calculating left and right directions, difference is:
Δθ＝θ
r-θ
l
(9) whether difference DELTA θ is greater than threshold value: greater than, then being judged to breakpoint is the edge catastrophe point, is changed to left unique point being judged to breakpoint.
(10) the preliminary catastrophe point in the right side is changed to is judged to breakpoint, get next unique point.
(11), finish to judge if all unique points are judged to finish; Otherwise, got back to for second step, judge next time.
10. whether last outline line: not, take off an outline line, got back to for the 3rd step; Be to carry out further work.
2) little section identification: the fiber edge that extracts is previously connected for little section, extract little section of independent fiber.According to little section at edge each other geometric relationship and little section at edge between the situation that changes of pixel grey scale determine, algorithm flow such as Fig. 6, specific algorithm is as follows:
(1) gets little section of fiber edge.
(2) search little section of corresponding edge.
A. point coordinate in little section of the edge calculation.
B. set up the little section normal equation of crossing mid point in edge.
C. search for little section of additional fibers along normal to fibrous inside.
If d. search little section at new edge, judge whether little section at new edge and former edge are the edges of little section of same fiber for little section.If not, get back to previous step, again search.
(3) whether fiber is discerned and is finished: not, take off a fiber, got back to for second step: be to finish.
(3) fineness is calculated
Fineness calculate to use the sub-pixel positioning method to determine edge point position, calculate the algorithm of fineness again, flow process such as Fig. 7, and its ultimate principle is as follows:
1. get little section of fiber
2. get the fibre section
3. calculate left hand edge point position, fibre section: carry out medium filtering, remove the grey scale change abnormity point, near the grey scale change curve the two edges point of cross section, edge is carried out least square curve fitting, getting the matched curve maximum point is the left hand edge point
4. calculate right hand edge point position, fibre section: carry out medium filtering, remove the grey scale change abnormity point, near the grey scale change curve the two edges point of cross section, edge is carried out least square curve fitting, getting the matched curve maximum point is the left hand edge point
5. calculate fibre fineness.
6. whether last cross section., do not get back to for second step.
7. calculate the fiber average fineness.
8. whether all fibres is all measured., do not get back to for the 3rd step.
9. calculate all fibres average fineness.
The fine-limit work bench control system
The X-Y precision stage adopts the rolling friction guide rail, drag worktable by servomotor by the rack-and-pinion transmission and realize x, the motion of two degree of freedom of y is realized the auto-feed of test process by computer control, be used for the fiber on the scanned sample, principle as shown in Figure 8; Z for manually, adjusts the microscopic system focal length to motion.Control system connects as shown in Figure 9, and Figure 10 is the worktable control flow.The speed of motion and direction are controlled by the D/A plate by computing machine.Feeding route during its work is as shown in figure 11: camera lens moves to the x positive dirction from the upper left corner; When moving to the edge, the stop motion of x direction, y moves a step to fortune, y direction stop motion then, x is to doing counter motion; When x when moving to counter edge, same, the stop motion of x direction, y moves a step to fortune, y direction stop motion then, x is to making positive movement.As mentioned above, the sample feeding that constantly circulates finishes until measuring.
Measure annex: comprise fibre cutter, dispenser, microslide and sample box, printer.Fiber sample after fibre cutter will be put in order cuts off the fiber line segment of growing into 1.8mm～2mm, puts into the dispenser uniformly dispersing then on microslide, and sample box can be placed 16 secondary standby microslides, and printer is used for the output of fibre image and measurement result.
The technical indicator such as the table 1 of instrument.
Table 1 apparatus measures technical indicator
| Measurement range | 4～300μm | ||
| Measuring speed | Maximum can reach 140/s | ||
| Measurement reproducibility and accuracy | Average fineness (μ m) | The measuring limit error | Measuring relative errors |
| 16.66 | ±0.029 | 0.0036 | |
| 18.31 | ±0.059 | -0.0044 | |
| 20.38 | ±0.028 | 0 | |
| 23.54 | ±0.048 | -0.0051 | |
| 26.43 | ±0.030 | -0.0061 | |
| 30.62 | ±0.068 | 0.0029 | |
| 34.69 | ±0.102 | 0.0066 | |
| 37.69 | ±0.135 | 0.0013 | |
| Long-time stability | Numbering | Δ | |
| by01_1 | 0.042 | ||
| by05_1 | 0.045 | ||
| by08_1 | 0.112 | ||
Claims (3)
1, a kind of wool fiber diameter measurement method is characterized in that this method comprises the steps:
(1) obtains fibre section, amplify fibre image by optical microscope system;
(2) adopt the CCD digital camera to convert fibre image to digital picture;
(3) read digital picture by computing machine, and carry out Flame Image Process and measure calculating, measure calculating and comprise fiber edge extraction, the identification that fiber is little section, the calculating of little section fineness of fiber; Described fiber edge is extracted the algorithm that adopts binaryzation-edge to follow the tracks of, the method of little section separation-condition judgment of fiber edge is adopted in little section identification of described fiber, thereby described fibre fineness adopts the sub-pixel positioning method to determine that edge point position realizes the calculating of fibre fineness in calculating;
(4) worktable x, y direction feeding employing are that control module, digital camera are the closed loop control method of feedback assembly with the computing machine;
(5) table feed repeats the step of 2-4 to the next position.
2, adopt a kind of wool fiber diameter measurement system of method according to claim 1, mainly comprise the optical microphotograph imaging system that constitutes by illuminator and microscopic system, image acquisition and disposal system, realize X, the worktable and the driving control system thereof of the feeding of Y both direction, measure annex, it is characterized in that described illuminator adopts ordinary light source and Kohler illumination system, described image acquisition and disposal system comprise the CCD digital camera and be equipped with to be handled image, measure to calculate and the computing machine of software for display as a result, this computing machine is connected with digital camera by the IEEE1394 interface.
3, according to the described wool fiber diameter measurement of claim 2 system, it is characterized in that worktable adopts the monolithic construction of servomotor symmetric arrangement, its worktable driving control system adopts by computing machine, D/A conversion, driving circuit, servomotor and the closed-loop control system formed as the operating position feedback assembly with digital camera.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNB021000565A CN1156708C (en) | 2002-01-14 | 2002-01-14 | Method and system for measuring wool fiber fineness measurement |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNB021000565A CN1156708C (en) | 2002-01-14 | 2002-01-14 | Method and system for measuring wool fiber fineness measurement |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN1359006A CN1359006A (en) | 2002-07-17 |
| CN1156708C true CN1156708C (en) | 2004-07-07 |
Family
ID=4739165
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CNB021000565A Expired - Fee Related CN1156708C (en) | 2002-01-14 | 2002-01-14 | Method and system for measuring wool fiber fineness measurement |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN1156708C (en) |
Families Citing this family (28)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AU2003901910A0 (en) * | 2003-04-17 | 2003-05-08 | Commonwealth Scientific And Industrial Research Organisation | Method and apparatus for testing fibres |
| CN1324310C (en) * | 2004-10-26 | 2007-07-04 | 东华大学 | Combining method for measuring fiber profile and mechanics behavior and equipment |
| CN100406849C (en) * | 2006-10-18 | 2008-07-30 | 东华大学 | Method for measuring non-woven fabric fiber diameter by polymer extruding method, and system |
| CN101178396B (en) * | 2007-11-29 | 2011-08-31 | 东华大学 | Cashmere fibre, fleece fibre blended spinning quantitative determination instrument and method |
| CN101424680B (en) * | 2008-12-11 | 2012-01-04 | 东华大学 | Computer automatic recognition apparatus and method for profile fiber |
| CN101487838B (en) * | 2008-12-11 | 2012-12-05 | 东华大学 | Extraction method for dimension shape characteristics of profiled fiber |
| CN102721377A (en) * | 2012-06-26 | 2012-10-10 | 吴江市金真缝纫机有限公司 | Fiber cross section detection device |
| CN102840835A (en) * | 2012-07-06 | 2012-12-26 | 西安电子科技大学 | Wool diameter detecting method based on Euclidean distance and image block |
| CN103149210B (en) * | 2013-02-25 | 2015-09-30 | 东华大学 | A kind of fabric cashmere content detection system and method based on scale picture and text feature |
| CN103499303B (en) * | 2013-09-27 | 2016-08-24 | 中国人民解放军空军工程大学 | A kind of wool fineness method for automatic measurement |
| CN107645925B (en) * | 2015-05-29 | 2021-06-25 | 荷兰联合利华有限公司 | System and method for measuring hair diameter |
| CN105403482B (en) * | 2015-10-26 | 2019-01-11 | 东华大学 | A kind of optical algorithms of opposite surface density |
| EP3369041A1 (en) | 2015-10-30 | 2018-09-05 | Unilever Plc. | Hair diameter measurement |
| MX2018005143A (en) | 2015-10-30 | 2018-06-06 | Unilever Nv | Hair curl measurement. |
| CN105606483A (en) * | 2016-03-03 | 2016-05-25 | 中国计量学院 | Raw silk fineness detection device and method thereof for detecting raw silk fineness |
| CN106091957B (en) * | 2016-04-21 | 2017-11-24 | 新疆天通兴业农牧科技有限公司 | A kind of method of quick detection raw wool |
| CN105973157A (en) * | 2016-04-21 | 2016-09-28 | 新疆畜牧科学院畜牧业质量标准研究所（新疆维吾尔自治区种羊与羊毛羊绒质量安全监督检验中心） | Animal fiber test section partitioning and fine measurement method |
| CN106091937B (en) * | 2016-04-21 | 2017-11-24 | 新疆天通兴业农牧科技有限公司 | A kind of method of the quick detection lint under non-standard environmental |
| CN106093039A (en) * | 2016-04-21 | 2016-11-09 | 新疆天通兴业农牧科技有限公司 | A kind of without pre-treatment lint Fast Detection Technique |
| AR109925A1 (en) * | 2016-10-18 | 2019-02-06 | Quispe Pena Edgar Carlos | PORTABLE ELECTRONIC EQUIPMENT TO CHARACTERIZE FIBERS OF ANIMAL ORIGIN |
| CN107219223A (en) * | 2017-01-12 | 2017-09-29 | 北京远心科技有限责任公司 | The thick automatic content test method of chamber hair |
| CN107153064A (en) * | 2017-05-22 | 2017-09-12 | 绍兴众舟科技有限公司 | A kind of assay method of monofilament radical and the measurement system of monofilament radical |
| CN107843194A (en) * | 2017-10-17 | 2018-03-27 | 北京和众视野科技有限公司 | The flight image measuring method and device of a kind of natural textile fiber length |
| CN108107560A (en) * | 2018-01-23 | 2018-06-01 | 芜湖市奥尔特光电科技有限公司 | A kind of verification of traces comprehensive instrument |
| CN109029256A (en) * | 2018-07-10 | 2018-12-18 | 内蒙古工业大学 | A kind of point comb cashmere length detecting method based on maximum between-cluster variance |
| CN109916339B (en) * | 2019-03-21 | 2020-11-06 | 浙江理工大学 | Method and device for measuring fiber angle based on illumination stereoscopic system |
| CN110207637B (en) * | 2019-07-02 | 2024-04-12 | 山东鲁普科技有限公司 | Fiber yarn fineness tester and testing method thereof |
| CN113538489B (en) * | 2021-07-19 | 2022-09-09 | 武汉纺织大学 | Method for measuring fiber diameter of non-woven fabric |
-
2002
- 2002-01-14 CN CNB021000565A patent/CN1156708C/en not_active Expired - Fee Related
Also Published As
| Publication number | Publication date |
|---|---|
| CN1359006A (en) | 2002-07-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN1156708C (en) | Method and system for measuring wool fiber fineness measurement | |
| CN107121093B (en) | Gear measuring device and method based on active vision | |
| CN108332689B (en) | Optical measurement system and method for detecting surface roughness and surface damage | |
| CN100351039C (en) | Precisive measurement of static knife profile | |
| CN106197328A (en) | Gather band steel burr and the method for shape wave data and realize the system of the method | |
| CN103033919B (en) | System capable of automatically compensating and focusing in process of automatic scanning and method and application thereof | |
| CN109211110A (en) | A kind of flat-type workpiece size detection system and method based on machine vision | |
| CN111340798A (en) | Application of deep learning in product appearance flaw detection | |
| CN101839696B (en) | Image-based radius template automatic calibrator | |
| CN102141374A (en) | Image type spinneret plate automatic detector | |
| CN102141381A (en) | Thickness and dimension automatic measuring instrument for insulation layer and protective sleeve of image type cable | |
| CN106584273A (en) | Online visual detecting system for robot polishing | |
| CN109693140B (en) | Intelligent flexible production line and working method thereof | |
| CN103308524A (en) | PCB automatic optical inspection system | |
| CN115631138A (en) | Zirconium alloy plate laser cutting quality monitoring method and device | |
| CN111157537A (en) | Strip steel defect detection device and system based on bionic machine vision | |
| CN111761224B (en) | Metal additive manufacturing online mobile monitoring mechanism and online appearance detection equipment | |
| CN112345553A (en) | Hard disk part detection device and detection method | |
| CN207593994U (en) | A kind of automatically scanning cutting optimization sorting device | |
| CN1959404A (en) | Ultrasonic method and device for testing macroscopic cleanness of continuous casting billet | |
| CN211331676U (en) | Aviation blade puncher installs gas film hole site aperture on-line measuring's device additional | |
| CN1369697A (en) | Lens detector for measuring performance of lens or contact lens | |
| CN209858405U (en) | PCB defect detection system device based on machine optics | |
| CN103454283A (en) | Line detection system and method | |
| CN208042989U (en) | A kind of large-scale sheet metal works almost T-stable automatic detection device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C06 | Publication | ||
| PB01 | Publication | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| C19 | Lapse of patent right due to non-payment of the annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |