CN109520436B - Butterfly spring three-dimensional size automatic measurement system based on machine vision and measurement method thereof - Google Patents
Butterfly spring three-dimensional size automatic measurement system based on machine vision and measurement method thereof Download PDFInfo
- Publication number
- CN109520436B CN109520436B CN201811433825.7A CN201811433825A CN109520436B CN 109520436 B CN109520436 B CN 109520436B CN 201811433825 A CN201811433825 A CN 201811433825A CN 109520436 B CN109520436 B CN 109520436B
- Authority
- CN
- China
- Prior art keywords
- belleville spring
- size
- camera
- spring
- machine vision
- 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
- 238000005259 measurement Methods 0.000 title claims abstract description 38
- 238000000691 measurement method Methods 0.000 title description 4
- 238000001514 detection method Methods 0.000 claims abstract description 48
- 238000000034 method Methods 0.000 claims abstract description 40
- 230000003287 optical effect Effects 0.000 claims description 10
- 238000012545 processing Methods 0.000 claims description 5
- 239000005338 frosted glass Substances 0.000 claims 3
- 239000005337 ground glass Substances 0.000 description 9
- 238000010586 diagram Methods 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000001914 filtration Methods 0.000 description 3
- 239000011159 matrix material Substances 0.000 description 3
- 238000003708 edge detection Methods 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000003754 machining Methods 0.000 description 1
- 239000003550 marker Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/08—Measuring arrangements characterised by the use of optical techniques for measuring diameters
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
- G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
- G01B11/0608—Height gauges
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/08—Measuring arrangements characterised by the use of optical techniques for measuring diameters
- G01B11/12—Measuring arrangements characterised by the use of optical techniques for measuring diameters internal diameters
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention discloses a butterfly spring three-dimensional automatic dimension measuring system based on machine vision, which comprises a hardware part, wherein the hardware part comprises a detecting device, the detecting device comprises a base, two upright posts are symmetrically and fixedly installed on one side of the upper part of the base through a corner connecting piece, a cross rod is fixedly installed between the two upright posts and close to the upper ends of the two upright posts, when field measurement is carried out, the butterfly spring only needs to be placed in a region to be measured, and can be replaced at any time when a plurality of butterfly springs are detected, so that automatic judgment and detection are realized, the operation is convenient and simple, and the detection efficiency is high; the invention also discloses a machine vision-based automatic measuring system and a measuring method thereof for the three-dimensional size of the belleville spring, which comprises three steps, wherein the adopted machine vision measuring method reduces the damage of the belleville spring in the manual measuring process by a non-contact measuring mode, and particularly reduces the belleville spring with smaller specification.
Description
Technical Field
The invention relates to the technical field of optical three-dimensional size detection, in particular to a butterfly spring three-dimensional size automatic measuring system based on machine vision and a measuring method thereof.
Background
Part size detection has high repeatability, high intelligence, receives parts machining's random error to influence, and the part size detection must add artificial judgement, but manual detection work load is big, and is slow, easy tired, poor stability, with high costs to complicated, small, mass production part, manual detection work load is big, the degree of difficulty is high.
The belleville spring is a mechanical part widely applied to the fields of aerospace, mechanical equipment industry and the like, and has certain difficulty in size measurement due to the fact that the belleville spring is in a bowl and dish shape. The existing detection technology is that a go gauge, a no-go gauge and a plug gauge are used for measurement, each belleville spring needs to be measured for 6 times to measure the whole size and judge whether the whole size is qualified or not, the workload is large, the speed is low, the naked eye is easy to fatigue, and parts are easy to damage in the manual detection process.
The existing part size detection based on machine vision is not applied to the size detection of the belleville spring, the existing part detection based on machine vision can only obtain two-dimensional size, only three-dimensional size is converted into two-dimensional plane for measurement, and the installation and detection device of the industrial camera is relatively complex. The detected part has a regular shape and cannot be applied to three-dimensional measurement of the belleville spring.
Because the detection precision and the efficiency of the small-size and large-batch-produced belleville springs are high, and an automatic, high-precision, non-contact and high-efficiency size measurement and evaluation system has important significance, the three-dimensional size automatic measurement system and the measurement method of the belleville springs based on machine vision are provided.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a butterfly spring three-dimensional dimension automatic measuring system based on machine vision and a measuring method thereof, so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
a disc spring three-dimensional size automatic measuring system based on machine vision comprises a hardware part, wherein the hardware part comprises a detection device, the detection device comprises a base, two upright posts are symmetrically and fixedly installed on one side of the upper portion of the base through a corner connecting piece, a cross rod is fixedly installed between the two upright posts and close to the upper end of the two upright posts, a camera CL and a camera CR are fixedly installed in the middle of the two upright posts through a connecting seat respectively, a camera CT is fixedly installed at the bottom of the middle of the cross rod through a mounting seat, common optical lenses are installed on the camera CL and the camera CR, a telecentric optical lens is installed on the camera CT, a backlight light source is installed at the bottom of the base, ground glass is installed above the backlight light source on the upper portion of the base, a disc spring to be measured is placed at the center of the upper portion, and a plurality of mark points are arranged on the upper part of the ground glass and positioned on the periphery of the butterfly spring.
Furthermore, the mark points are common outer black inner circle round mark points.
Further, the device also comprises a software part, wherein the software part comprises a CT camera display window, a CL camera display window, a CT camera calibration interface, a CL camera calibration interface, a display window with a measuring size, a belleville spring size standard setting window and a belleville spring size qualified window;
the CT, CL and CR camera display windows are used for displaying images acquired by the cameras in real time;
the CT, CL and CR camera calibration interfaces are used for calibrating cameras and preparing for size detection of the belleville springs;
the measurement size display window is used for displaying the measurement result in real time;
the size standard setting window of the belleville spring is used for interactively inputting the standard size and the allowable error;
and the qualified or unqualified belleville spring window is used for displaying whether the size of the detected belleville spring is qualified or not.
Further, the measurement result includes: the inner diameter, the outer diameter and the height of the belleville spring, detection errors of the inner diameter, the outer diameter and the height, and whether the inner diameter, the outer diameter and the height meet the standard size and tolerance requirements or not, if the belleville spring is not detected, the detection result is 0.
The invention also provides a machine vision-based method for automatically measuring the three-dimensional size of the belleville spring, which comprises the following steps of:
firstly, comparing each frame of image collected by a camera CT with the previous frame of image, and automatically entering a detection program for the gray information of the previous and next images within a certain threshold range;
secondly, detecting the inner and outer diameter sizes of the belleville spring by using a telecentric lens, and acquiring contour information to be detected of the belleville spring through real-time image processing;
and thirdly, measuring the three-dimensional size of the belleville spring by using an automatic measuring system, distinguishing mark points and the belleville spring, projecting the mark points to a world coordinate system again for plane fitting, obtaining the coordinates of the elliptic central point on the belleville spring of the camera CL and the elliptic central point on the belleville spring of the camera CR according to an elliptic fitting method, performing left-right matching and then projecting the marks to the world coordinate system again according to the principle of left-right stereoscopic vision to obtain the elliptic center on the belleville spring, and calculating the height by calculating the distance from the elliptic center to a fitting plane.
In summary, the invention mainly has the following beneficial effects:
1. according to the invention, the three-dimensional sizes of the inner diameter, the outer diameter and the height of the belleville spring are automatically detected, the workload of the traditional plug gauge measuring mode is reduced, the detection efficiency and the detection precision are improved, the absolute error of the inner diameter and the outer diameter is ensured to be 0.02-0.1mm, and the absolute error of the height is ensured to be 0.02 mm;
2. according to the invention, the detection device is an optical measurement instrument based on machine vision, and when field measurement is carried out, only the belleville springs are required to be placed in a region to be detected, and the belleville springs can be replaced at any time when being detected, so that automatic judgment and detection are realized, the operation is convenient and simple, and the detection efficiency is high;
3. according to the invention, a telecentric lens and backlight measurement mode is adopted, and an improved image contour searching technology is adopted, so that the boundary detection of the belleville spring in the image is more accurate, and the measurement precision is improved;
4. according to the invention, when the height is measured, the mark points can be movably placed, and the position of the measuring plane can be changed, so that the measuring plane is not restricted, and the measurement is more flexible;
5. according to the method, the marking points and the target belleville springs are distinguished by adopting a similar distinguishing method, so that the belleville springs in the field of view of the telecentric lens can be detected, and the stability of a measuring system is ensured;
6. according to the invention, the adopted machine vision measuring method reduces the damage of the belleville spring in the manual measuring process through a non-contact measuring mode, especially the belleville spring with smaller specification;
7. according to the invention, a software interface which is simple to operate is developed, the visual field, the detection size and the identification of whether the camera is qualified or not are displayed in real time, the method is suitable for common detection workers, and a software processing program provides support data for later-stage qualified product sorting, automatic detection and sorting;
8. the invention has the characteristics of high precision, high stability and high efficiency for three-dimensional size detection of the belleville spring, and can be popularized to three-dimensional size measurement of thin-wall parts, apertures and stamping parts.
Drawings
FIG. 1 is a diagram illustrating a hardware configuration of an embodiment of the present invention;
FIG. 2 is a schematic diagram of a software main interface according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a Belleville spring according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a reconstruction marker point and the center of an ellipse on a Belleville spring in accordance with one embodiment of the present invention;
fig. 5 is an image of a 31.5 x 16.3 x 2.45mm belleville spring specification and processed captured by a camera CL in accordance with an embodiment of the present invention;
FIG. 6 is a graph of Belleville spring measurements according to one embodiment of the present invention;
FIG. 7 is a graph of the error in the measurement of the Belleville spring in accordance with one embodiment of the present invention.
In the figure: 1-1, corner connectors; 1-2, a base; 1-3, camera CR; 1-4, a connecting seat; 1-5, a common optical lens; 1-6, camera CT; 1-7, assembling base; 1-8, telecentric optical lens; 1-9, camera CL; 1-10, a belleville spring; 1-11, marking points; 1-12, ground glass; 1-13, a backlight source; 1-14, standing; 1-15, cross bar;
2-1 functional area, 2-2 standard area, 2-3 prompt area, 2-4 left camera CL display area, 2-5 detection result display area, 2-6 camera CT display area and 2-7 right camera CR display area;
the size to be measured: the outer diameter D of the belleville spring, the inner diameter D of the belleville spring and the height H of the belleville spring.
Detailed Description
The present invention is described in further detail below with reference to fig. 1-7.
Example 1
A butterfly spring three-dimensional dimension automatic measuring system based on machine vision is disclosed, as shown in figure 1, and comprises a hardware part, wherein the hardware part comprises a detecting device, the detecting device comprises a base 1-2, one side of the upper part of the base 1-2 is symmetrically and fixedly provided with two upright rods 1-14 through a corner connecting piece 1-1, a cross rod 1-15 is fixedly arranged between the two upright rods 1-14 near the upper end thereof, the middle parts of the two upright rods 1-14 are respectively and fixedly provided with a camera CL1-9 and a camera CR1-3 through connecting seats 1-4, the bottom of the middle part of the cross rod 1-15 is fixedly provided with a camera CT1-6 through an assembling seat 1-7, the camera CL1-9 and the camera CR1-3 are both provided with common optical lenses 1-5, the camera CT1-6 is provided with a telecentric optical lens 1-8, the bottom of the base 1-2 is provided with a backlight light source 1-13, the upper part of the base 1-2 is positioned above the backlight light source 1-13 and is provided with ground glass 1-12, the upper central position of the ground glass 1-12 is provided with a belleville spring 1-10 to be measured, and the upper part of the ground glass 1-12 is positioned at the periphery of the belleville spring 1-10 and is provided with a plurality of mark points 1-11.
Preferably, as shown in fig. 4 and 5, the mark points 1-11 are ordinary outer black inner circle mark points.
By adopting the technical scheme, the common round mark points with black outside and round inside are easy to identify, and the measurement efficiency is convenient to improve.
Preferably, as shown in fig. 2, the device further comprises a software portion, wherein the software portion comprises a CT, CL, CR camera display window, a CT, CL, CR camera calibration interface, a display window with a measurement size, a belleville spring size standard setting window, and a belleville spring size qualified window;
the CT, CL and CR camera display windows are used for displaying images acquired by the cameras in real time;
the CT, CL and CR camera calibration interfaces are used for calibrating cameras and preparing for size detection of the belleville springs;
the measurement size display window is used for displaying the measurement result in real time;
the size standard setting window of the belleville spring is used for interactively inputting the standard size and the allowable error;
and the qualified or unqualified belleville spring window is used for displaying whether the size of the detected belleville spring is qualified or not.
Preferably, the measurement result includes: the inner diameter, the outer diameter and the height of the belleville spring, detection errors of the inner diameter, the outer diameter and the height, and whether the inner diameter, the outer diameter and the height meet the standard size and tolerance requirements or not, if the belleville spring is not detected, the detection result is 0.
The invention also provides a machine vision-based method for automatically measuring the three-dimensional size of the belleville spring, which comprises the following steps of:
firstly, judging that the gray information of each frame of image and the previous frame of image enter a detection program within a threshold range;
secondly, detecting the inner and outer diameter sizes of the belleville spring by using a telecentric lens, and acquiring contour information to be detected of the belleville spring through real-time image processing;
and thirdly, measuring the three-dimensional size of the belleville spring by using an automatic measuring system, distinguishing the mark points and the belleville spring, projecting the mark points to a world coordinate system again for plane fitting, projecting the ellipse center on the belleville spring to the world coordinate again, and calculating the distance between the ellipse center and the fitting plane to calculate the height.
Example 2
According to the automatic butterfly spring three-dimensional size measuring system based on the machine vision, which is built according to the embodiment 1, the automatic butterfly spring three-dimensional size measuring system software based on the machine vision is operated on a PC, and is connected with cameras CL1-9, CR1-3 and CT1-6 through data lines to carry out system calibration, calibration parameters are stored in the PC, any butterfly spring is placed on ground glass to be detected, a 'start detection' button is selected to enter a detection process in a functional area 2-1 part, a measurement result is displayed in a detection result display area 2-5 in real time, and a detector carries out sorting of qualified butterfly springs by observing the detection result or prompt bar information.
Example 3
The method for automatically measuring the three-dimensional size of the belleville spring based on the machine vision according to the embodiment 2 comprises the following steps: the camera works at a certain frame rate, each frame of image acquired by the camera CT is compared with the previous frame of image, the gray information represents the attribute of each frame of image, and the gray information of the previous and the next images automatically enter a detection program within a certain threshold range.
Example 4
The automatic measuring system of the three-dimensional size of the belleville spring based on the machine vision and the measuring method thereof according to the embodiments 1 to 3 are divided into the measuring method of the inner and outer diameter sizes (D, d) of the belleville spring and the measuring method of the height (H) of the belleville spring.
(1) The inner and outer diameter measuring method comprises three steps of telecentric lens camera calibration, image processing and size calculation;
the camera calibration method comprises the following steps: manufacturing a concentric circular calibration plate with standard size and actual diameter D0＝{D01,D02,D03Finding the size D of the diameter corresponding to the ring on the image of the circular ring calibration plate acquired by the camera CT1-60'＝{D01',D02',D03' } the nominal magnification K is defined as
The image processing method comprises the following steps: the method comprises the following steps of image filtering, edge detection, ellipse fitting and ellipse long axis calculation, wherein the image filtering adopts a Gaussian filter operator, the edge detection adopts a Canny operator, the ellipse fitting adopts a least square method, because the mark points and the belleville springs are simultaneously placed on the upper surface of the ground glass, if the belleville springs and the mark points are simultaneously in the visual field of a camera, the mark points and the belleville springs need to be distinguished, and the method for distinguishing the mark points and the belleville springs comprises the following steps: the attribute table of the fitting circle obtained by fitting the ellipse is pj＝{nj,wj,Sj1,2, m, where m is the number of fitted ellipses, nj,wjThe inner ellipse parameters, i.e., major and minor axis lengths, for the jth fitted ellipse are noted as N ═ N1j,n2j}，W＝{w1j,w2j}，SjFitting the area property of an ellipse, i.e.
Therefore, the fitting ellipse has 5 parameter sets, and the constructed attribute matrix is: p ═ P (P)ij)m×5＝[N,W,S]Defining an elliptical property gradient matrix
Wherein i is 1,2, 5, j is 2,3
The corresponding line and the adjacent line are ellipses of the belleville springs on the image, and the mark points and the target ellipses can be distinguished through the position relation of the image;
the major axis length D of the inner and outer ellipses on the image can be obtained after the target ellipse is foundimg、dimgThen, the actual length outer diameter D is calculated to be KDimgInside diameter d ═ Kdimg。
(2) The height measurement method comprises the steps of fitting a measurement plane, searching the center of an ellipse on the belleville spring and calculating the distance;
the fitting method of the measuring plane comprises the following steps: the left camera CL1-9 and the right camera CR1-3 simultaneously acquire measurement plane images, the marking circles of the left image and the right image are searched according to the marking point searching method, the marking point matching is carried out By using a limit constraint method, the marking points are re-projected into a world coordinate system By using a projection matrix calibrated By the left camera CL1-9 and the right camera CR1-3 and the parallax of the left camera and the right camera, three-dimensional coordinates of m spatial marking points are obtained, the three-dimensional coordinate points are fitted to a plane By using a least square method, the plane is represented in the world coordinate system, and the plane pi in the world coordinate system in the attached figure 4 is Ax + By + Cz + D which is 0;
the method for searching the left and right butterfly spring ellipses comprises the following steps: firstly, filtering an image to remove noise, particularly noise of a gray part, acquiring an interested region of a belleville spring, dividing a gray value of the image into three levels of black, gray and white, and acquiring interest for clustering in a machine learning modeF (u, v), the initial black, gray, white threshold gray values are given as B through experiments0、G0、W0The classification idea is that the distance between the gray value of any point on the image and the gray threshold is calculated, and the distance from the pixel point belonging to the black area to B0Is the smallest distance of the first and second electrodes,
i.e. having the attribute | f (u, v) -B0|＝min{|f(u,v)-B0|,|f(u,v)-G0|,|f(u,v)-W0After primary classification, all pixel points belonging to the three classes are obtained, in each class, an average pixel gray value is taken to replace threshold values of the initial three classes, clustering is carried out again until the gray threshold value is kept stable, namely the algorithm is converged, after clustering, the gray level in the belleville spring image is obtained preliminarily, contour searching is carried out next, the concept of clustering is adopted again, classification is carried out according to the gray value gradient of the black area transiting to the gray area, the gray gradient value of the gray area transiting to the white area and the gray gradient value of the black area transiting to the white area, the boundary formed by screening the pixel points in the black area transiting to the white area and the pixel points in the black area transiting to the gray area is an upper elliptical contour, and the boundary formed by the pixel points of the gray area transiting to the white area and the pixel points of the white area transiting to the white area is an inner circle, then obtaining the image coordinate (u) of the central point of the upper ellipse according to the ellipse fitting methodL,vL) And the circle centers C of four ellipses of the belleville spring can be obtained simultaneously1、C2、C3、C4. The same processing is performed on the image acquired by the right camera to obtain the coordinates (u) of the center point of the ellipse on the belleville spring of the right camera CRR,vR) According to the principle of left-right stereoscopic vision, after left-right matching, the measured butterfly spring is re-projected into a world coordinate system to obtain the world coordinate (x) of the center of the upper circle of the measured butterfly spring0,y0,z0)。
The height of the belleville spring is converted into the middle point (x) of the world coordinate system0,y0,z0) Distance to plane pi. The height values of the belleville springs measured are then:
example 5
According to examples 1 to 4, in order to verify whether the detected disc spring size is consistent with the actual size, a vernier caliper is used for measurement verification. The detection results and detection errors are shown in FIGS. 6-7. For a belleville spring with a standard specification of 31.5 × 16.3 × 2.45mm, the measurement of the belleville spring is carried out by using a vernier caliper, the measurement size is 31.37 × 16.57 × 2.8mm, and the error between the measurement result of the invention and the measurement result of the vernier caliper is small. Meanwhile, the belleville spring is a non-qualified product.
Example 6
The automatic measuring system and the measuring method for the three-dimensional size of the belleville spring based on the machine vision according to the embodiments 1-5 have the following functions:
1. telecentric lens 1-8: the telecentric lens has ultra-wide depth of field, the size of the camera image is kept unchanged in the depth of field range, and perspective errors caused by the 'big and small distance' of the common camera image are eliminated;
2. left and right cameras: the left camera and the right camera can obtain the depth information of the image, and can realize the reconstruction of the mark points and the center of the ellipse on the belleville spring, so that the three-dimensional size is obtained;
3. backlight light source: the clear characteristic of image acquisition is ensured, the outline is more prominent, and the interference of ambient light on image acquisition, such as light reflection and the like, is reduced;
4. base and pole setting and horizontal pole: connecting the three cameras, the backlight source and the corner connecting piece, and connecting and supporting the normal installation operation of the whole hardware part;
5. a software part: and a friendly user operation interface is provided, a system calibration and detection result display interface can be simply and conveniently carried out, and a current detection result and a message whether the belleville spring is qualified or not are displayed.
The working principle is as follows: according to the automatic measuring system and the automatic measuring method for the three-dimensional size of the belleville spring based on machine vision, a camera is connected at first, the pose and parameters of the camera are adjusted, and camera calibration is carried out. And then, switching on a backlight light source, and placing the butterfly spring to be detected on the upper surface of the ground glass. And carrying out three-dimensional size measurement by using the three-dimensional size detection and calculation method of the belleville spring. And displaying the measurement result in real time through the software interface. The backlight light source enables the collected image outline to be more prominent, and the image quality and the detection precision are improved.
The parts not involved in the present invention are the same as or can be implemented by the prior art.
The present embodiment is only for explaining the present invention, and it is not limited to the present invention, and those skilled in the art can make modifications of the present embodiment without inventive contribution as needed after reading the present specification, but all of them are protected by patent law within the scope of the claims of the present invention.
Claims (4)
1. A method for automatically measuring the three-dimensional size of a belleville spring based on machine vision comprises a hardware part, the hardware part comprises a detection device, the detection device comprises a base (1-2), two upright posts (1-14) are symmetrically and fixedly installed on one side of the upper portion of the base (1-2) through corner connecting pieces (1-1), a cross rod (1-15) is fixedly installed between the two upright posts (1-14) and close to the upper end of the two upright posts, the middle portions of the two upright posts (1-14) are respectively and fixedly provided with cameras CL (1-9) and CR (1-3) through connecting seats (1-4), and the bottoms of the middle portions of the cross rods (1-15) are fixedly provided with cameras CT (1-6) through assembling seats (1-7), common optical lenses (1-5) are mounted on the camera CL (1-9) and the camera CR (1-3), telecentric optical lenses (1-8) are mounted on the camera CT (1-6), a backlight light source (1-13) is mounted at the bottom of the base (1-2), frosted glass (1-12) is mounted on the upper portion of the base (1-2) above the backlight light source (1-13), a disc spring (1-10) to be measured is placed at the central position of the upper portion of the frosted glass (1-12), and a plurality of mark points (1-11) are arranged on the periphery of the disc spring (1-10) on the upper portion of the frosted glass (1-12);
the method is characterized in that: the method comprises the following steps:
firstly, comparing each frame of image collected by a camera CT with the previous frame of image, and automatically entering a detection program for the gray information of the previous and next images within a certain threshold range;
secondly, detecting the inner and outer diameter sizes of the belleville spring by using a telecentric lens, and acquiring contour information to be detected of the belleville spring through real-time image processing;
and thirdly, measuring the three-dimensional size of the belleville spring by using an automatic measuring system, distinguishing mark points and the belleville spring, projecting the mark points to a world coordinate system again for plane fitting, obtaining the coordinates of the elliptic central point on the belleville spring of the camera CL and the elliptic central point on the belleville spring of the camera CR according to an elliptic fitting method, performing left-right matching and then projecting the marks to the world coordinate system again according to the principle of left-right stereoscopic vision to obtain the elliptic center on the belleville spring, and calculating the height by calculating the distance from the elliptic center to a fitting plane.
2. The method for automatically measuring the three-dimensional size of the belleville spring based on the machine vision as claimed in claim 1, wherein: the mark points (1-11) are common outer black inner circle round mark points.
3. The method for automatically measuring the three-dimensional size of the belleville spring based on the machine vision as claimed in claim 1, wherein: the device also comprises a software part, wherein the software part comprises a CT, CL and CR camera display window, a CT, CL and CR camera calibration interface, a display window for measuring the size, a belleville spring size standard setting window and a belleville spring size qualified window;
the CT, CL and CR camera display windows are used for displaying images acquired by the cameras in real time;
the CT, CL and CR camera calibration interfaces are used for calibrating cameras and preparing for size detection of the belleville springs;
the measurement size display window is used for displaying the measurement result in real time;
the size standard setting window of the belleville spring is used for interactively inputting the standard size and the allowable error;
and the qualified or unqualified belleville spring window is used for displaying whether the size of the detected belleville spring is qualified or not.
4. The machine vision-based method for automatically measuring the three-dimensional size of the belleville spring according to claim 3, wherein the method comprises the following steps: the measurement result comprises: the inner diameter, the outer diameter and the height of the belleville spring, detection errors of the inner diameter, the outer diameter and the height, and whether the inner diameter, the outer diameter and the height meet the standard size and tolerance requirements or not, if the belleville spring is not detected, the detection result is 0.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811433825.7A CN109520436B (en) | 2018-11-28 | 2018-11-28 | Butterfly spring three-dimensional size automatic measurement system based on machine vision and measurement method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811433825.7A CN109520436B (en) | 2018-11-28 | 2018-11-28 | Butterfly spring three-dimensional size automatic measurement system based on machine vision and measurement method thereof |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109520436A CN109520436A (en) | 2019-03-26 |
| CN109520436B true CN109520436B (en) | 2020-06-30 |
Family
ID=65794519
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811433825.7A Expired - Fee Related CN109520436B (en) | 2018-11-28 | 2018-11-28 | Butterfly spring three-dimensional size automatic measurement system based on machine vision and measurement method thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109520436B (en) |
Families Citing this family (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110132859A (en) * | 2019-05-28 | 2019-08-16 | 上汽通用五菱汽车股份有限公司 | A kind of spring detection device and application method based on machine vision |
| CN110375680A (en) * | 2019-07-17 | 2019-10-25 | 朱承智 | The measuring method of revolving body dynamic shaft core position based on binocular visual positioning technology |
| CN110455182B (en) * | 2019-07-23 | 2021-02-09 | 中广核检测技术有限公司 | Method for measuring abrasion loss of control rod guide card based on image recognition technology |
| CN110986793A (en) * | 2019-12-16 | 2020-04-10 | 天津工程机械研究院有限公司 | Quasi-square workpiece detection system based on machine vision detection |
| CN111336937B (en) * | 2020-04-14 | 2021-06-15 | 珠海博明视觉科技有限公司 | 2D device for improving measurement precision of cylinder diameter and measurement method thereof |
| CN111652874B (en) * | 2020-06-04 | 2023-10-20 | 崧智智能科技(深圳)有限公司 | Method, device, terminal and computer readable storage medium for measuring go-no go gauge |
| CN111906043B (en) * | 2020-07-16 | 2022-03-29 | 深圳市格灵人工智能与机器人研究院有限公司 | Pose detection method and system |
| CN112985298B (en) * | 2021-02-08 | 2022-09-20 | 上海机器人产业技术研究院有限公司 | Mobile phone lens size measuring method based on micro CT |
| CN115630741A (en) * | 2022-10-31 | 2023-01-20 | 中国电建集团成都勘测设计研究院有限公司 | Project-quantity-based mountain wind power development area planning method |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| ITMI20051411A1 (en) * | 2005-07-22 | 2007-01-23 | Microstudio S A S | EQUIPMENT AND METHOD FOR CALCULATING GEOMETRIC CHARACTERISTICS OF A HELICAL SPRING |
| CN102506704B (en) * | 2011-10-14 | 2013-12-25 | 天津大学 | Geometric parameter online measurement method of compression spring |
| CN202304768U (en) * | 2011-10-21 | 2012-07-04 | 深圳市慧耕科技有限公司 | Three-dimension measurement module and measurement instrument |
| CN203443556U (en) * | 2013-09-18 | 2014-02-19 | 廖怀宝 | Device capable of realizing two dimensional measurement and three dimensional measurement of object |
| CN204128502U (en) * | 2014-08-25 | 2015-01-28 | 华中科技大学 | A kind of transmission measurement mechanism measured for shaft part size |
| CN104976959B (en) * | 2015-07-07 | 2017-11-03 | 齐鲁工业大学 | A kind of spring sizes on-line measurement system and its method based on machine vision |
-
2018
- 2018-11-28 CN CN201811433825.7A patent/CN109520436B/en not_active Expired - Fee Related
Also Published As
| Publication number | Publication date |
|---|---|
| CN109520436A (en) | 2019-03-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109520436B (en) | Butterfly spring three-dimensional size automatic measurement system based on machine vision and measurement method thereof | |
| CN106949848B (en) | A kind of high-precision laser 3D profile phone structural detection method | |
| CN103615980B (en) | Method and system for measuring parameters of round holes in plate | |
| CN104266608B (en) | Field calibration device for visual sensor and calibration method | |
| CN107121093A (en) | A kind of gear measurement device and measuring method based on active vision | |
| CN106969706A (en) | Workpiece sensing and three-dimension measuring system and detection method based on binocular stereo vision | |
| CN109443209A (en) | A kind of line-structured light system calibrating method based on homography matrix | |
| CN109579695B (en) | Part measuring method based on heterogeneous stereoscopic vision | |
| CN105021628A (en) | Detection method for surface defects of optical fiber image inverter | |
| CN107869954B (en) | Binocular vision volume weight measurement system and implementation method thereof | |
| CN110672020A (en) | Stand tree height measuring method based on monocular vision | |
| CN107084671B (en) | A kind of recessed bulb diameter measuring system and measurement method based on three wire configuration light | |
| JP2017032548A (en) | Using 3d vision for automated industrial inspection | |
| CN109751964B (en) | High-precision non-contact pipe diameter measuring method and device | |
| CN109540040B (en) | Active vision detection system and method based on unconstrained concentric beam family automobile morphology | |
| CN101793840A (en) | Diamond cutting parameter measurement method and measuring device | |
| CN113119129A (en) | Monocular distance measurement positioning method based on standard ball | |
| JP2021193400A (en) | Method for measuring artefact | |
| CN108805870A (en) | A kind of detection method of the connector with needle stand | |
| CN112161565A (en) | High-precision laser projection vision three-dimensional measurement system | |
| CN110554054A (en) | three-dimensional blade breakage detection system of mechanically-clamped indexable turning tool | |
| WO2020079694A1 (en) | Optimizing defect detection in an automatic visual inspection process | |
| CN114998308A (en) | Defect detection method and system based on photometric stereo | |
| CN103884294A (en) | Wide view field type infrared light three-dimensional morphology measurement method and device thereof | |
| CN106123808B (en) | A method of it is measured for the deflection of automobile rearview mirror specular angle degree |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20201223 Address after: 225000 9 Shuangtang West Road, Weiyang Economic Development Zone, Yangzhou City, Jiangsu Province Patentee after: YANGZHOU HEWEI DISC SPRING MANUFACTURING Co.,Ltd. Address before: 225000 Wenchang West Road, Yangzhou City, Jiangsu Province Patentee before: YANGZHOU POLYTECHNIC College |
|
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20200630 |