CN110986834A - Automatic assembly pipe penetration monitoring method - Google Patents
Automatic assembly pipe penetration monitoring method Download PDFInfo
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- CN110986834A CN110986834A CN201911383939.XA CN201911383939A CN110986834A CN 110986834 A CN110986834 A CN 110986834A CN 201911383939 A CN201911383939 A CN 201911383939A CN 110986834 A CN110986834 A CN 110986834A
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- 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
- G01B11/26—Measuring arrangements characterised by the use of optical techniques for measuring angles or tapers; for testing the alignment of axes
- G01B11/27—Measuring arrangements characterised by the use of optical techniques for measuring angles or tapers; for testing the alignment of axes for testing the alignment of axes
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23P—METAL-WORKING NOT OTHERWISE PROVIDED FOR; COMBINED OPERATIONS; UNIVERSAL MACHINE TOOLS
- B23P19/00—Machines for simply fitting together or separating metal parts or objects, or metal and non-metal parts, whether or not involving some deformation; Tools or devices therefor so far as not provided for in other classes
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
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- 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
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- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention discloses an automatic assembly pipe penetration monitoring method, which adopts a machine vision mode to measure concentricity, monitors the pipe penetration process in real time, analyzes images, visually monitors a hole B of a product and a cylinder of the product A, measures the coaxial deviation of a thin pipe and the hole of the product A, calculates the rotation angle required by the product A, and displays an expected movement position by a track; measuring the gap between the thin tube and the hole in the radius direction, feeding back a circumferential multi-point measurement value, after the camera is calibrated by a manipulator, firstly carrying out image acquisition on the semi-spherical product by a high-definition industrial camera at a position 1, and processing the acquired image to obtain the position and pose data of the product; and acquiring an image of the hemispherical product at the position 5, performing three-dimensional template matching to obtain a product space position, and calculating deviation with a rotating base position mark.
Description
Technical Field
The invention relates to the technical field of automatic assembly, in particular to a method for monitoring automatic assembly pipe penetration.
Background
The robot grabs four types of hemispherical revolution bodies (including partial cylindrical sections) products to assemble, and carries out position measurement and monitoring on the products in the assembling process, wherein the position measurement and the monitoring mainly comprise revolution axis vision measurement, circumference direction measurement, pipe penetration monitoring and assembling clearance measurement.
For dislocation measurement, the hemispherical revolving body may not have a hole, so that the hemispherical revolving body cannot be positioned by using the characteristic mark points, and the measurement precision of the vision 3D positioning can only be 0.1mm, so that the measurement precision of the task cannot be ensured.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides an automatic assembling and pipe penetrating monitoring method which is high in precision and convenient to use.
In order to achieve the purpose, the invention adopts the following technical scheme: an automatic assembly pipe penetration monitoring method comprises a product A and a product B, and comprises the following steps:
the method comprises the following steps: assembling product a and product B:
step two: the concentricity is measured by adopting a machine vision mode, the pipe penetrating process is monitored in real time, and image analysis is carried out:
visually monitoring a hole with the diameter of 25mm of the product B and a cylinder with the diameter of 23mm of the product A, measuring the coaxial deviation between a thin tube with the diameter of 3mm of the product A and the hole with the diameter of 25mm, calculating the rotation angle required by the product A, and displaying the expected movement position by a track;
and (3) performing clearance measurement on the phi 3mm thin tube and the R2mm hole in the radius direction, and feeding back a circumferential multipoint measurement value.
Furthermore, the product A is made of stainless steel, the diameter of the product is phi 250mm, the surface roughness Ra0.8-1.6, the product A is fixed on the rotatable bracket, and the rotation precision is 0.01 degrees; a phi 3 thin tube is arranged at the position of the top end 30mm away from the central axis, the length of the thin tube is 200mm, the parallelism is less than phi 0.2mm, and the head of the thin tube is provided with a phi 23 cylindrical head with the length of 40 mm; the product is provided with a deep groove with the width of 10mm and the width of 3mm and a scribed line with the width of 0.2mm in the circumferential direction.
Further, the product B is made of powder die-casting materials, the surface roughness is Ra1.6-3.2, the product A is grabbed by a robot to be sleeved, the diameter is 300mm, the height is 250mm, and the wall thickness is 25mm; a vertical phi 25mm large hole is formed at the position, 30mm away from the central axis, of the top end of the product, and an R2mm half hole is formed at the edge of the large hole, wherein the distance from the center of the half hole to the central axis of the product is 30mm; the product also has a deep groove with the width of 10mm and the width of 3mm and a scribed line with the width of 0.2mm in the circumferential direction.
Further, the first step comprises:
the robot grabs the product B to a position to be assembled, and the position is marked as a position 1;
the robot grabs the product B to vertically move downwards, so that the large hole of the product B is assembled with the cylindrical head of the product A, and the position is marked as a position 2;
the product B descends to a position 5mm above the product A. At the moment, a phi 3mm thin tube is coaxial with a phi 25mm large hole theory, and the position is marked as a position 3;
the product A rotates to 24 degrees, so that the phi 3mm thin tube is screwed into the R2mm half hole, the phi 3mm thin tube is coaxial with the R2mm half hole, the uniform gap is ensured, the interference does not occur, and the position is marked as position 4;
and the product B continues to descend for 5mm, so that the lower end faces are attached, and after the assembly is finished, the position is marked as position 5.
Further, the concentricity measurement includes:
at the position 3, performing visual synthesis by using a left camera and a right camera, and performing visual correction; performing edge processing on the thin tube and the hole, extracting an edge arc, fitting the circle center, wherein the circle distance is the deviation of the edge arc and the circle center, and the measurement precision is less than or equal to 0.1 mm;
and at the position 4, performing edge treatment on the thin tube and the R2mm hole, extracting an edge arc, fitting the circle center to obtain the deviation distance between the thin tube and the hole wall, wherein the measurement precision is less than or equal to 0.1 mm.
Further, the process of pipe penetration of the semi-spherical product is verified through experiments, whether verification software can carry out accurate quantitative analysis on product image data or not is verified, deviation data of the thin pipe and the hole is obtained and fed back to the robot for position adjustment, and the qualified range is 0.1 mm. The single detection time is less than 10 s.
The invention has the beneficial effects that:
(1) the invention provides an automatic assembly pipe penetration monitoring method, wherein after a camera is calibrated by a manipulator, at a position 1, image acquisition is firstly carried out on a semi-spherical product by a high-definition industrial camera, and the acquired image is processed to obtain position and posture data of the product; and acquiring an image of the hemispherical product at the position 5, performing three-dimensional template matching to obtain a product space position, and calculating deviation with a rotating base position mark.
Drawings
FIG. 1 is a schematic view of a concentricity measurement camera installation as proposed by the present invention;
fig. 2 is a flow chart of concentricity measurement according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
The image analysis software adopted in the invention is Halcon software of Germany MVTec company. The MVTec company is located in Munich of Germany, stands in 1996, only focuses on the development and production of machine vision software in more than a decade, is a well-known development company of machine vision software of Germany, and is also a leader of standard machine vision software in the world.
HALCON is a full-function machine vision software package, provides a prototype integrated development environment, and users can flexibly set up own machine vision systems. ActivVisionTools-based on HALCON algorithm library, part of processing functions are controlled, and users can quickly and easily set up own machine vision system. The great-constant image company obtains the trust of the MVTec company with the great technical strength, so that the MVTec company becomes the only official partner of the MVTec in the Chinese market, and a support team receives special training in the MVTec company and can provide high-quality training and technical support for MVTec product users in the Chinese market.
HALCON is a full-featured machine vision software package, which provides the most powerful vision algorithm development package based on the latest computer image processing and computer vision technology. The world's most popular hardware-independent machine vision software products. Comprehensive functions and application. The software interface is shown in fig. 5.
HALCON is applicable to all industries that provide libraries of functions that have been used in hundreds of thousands of devices in each industry, including blob analysis, morphology, matching, measurement, recognition, and 3D vision, among others.
HALCON supports Windows, Linux, and macOS operating environments, which ensures investment efficiency. The whole function library can be accessed by various general programming languages such as C, C + + and.NET (such as C # or VB.NET). HALCON provides interfaces for hundreds of industrial cameras and image acquisition cards, particularly standard interfaces such as GenlCam, GigE Vision and USB3 Vision, and ensures the independence of hardware.
In image processing, it is often necessary to first perform some degree of noise reduction before further processing, such as edge detection, can take place. Median filtering is a non-linear digital filter technique that is often used to remove noise from images or other signals. The idea is to examine the samples in the input signal and determine whether it represents a signal, and to use an observation window consisting of an odd number of samples to achieve this function. The values in the observation window are sorted, and the median value in the middle of the observation window is used as output. The oldest value is then discarded, a new sample is taken, and the above calculation is repeated. Median filtering is a common step in image processing and is particularly useful for speckle noise and salt and pepper noise. Preserving the edge characteristics makes it useful in situations where edge blurring is undesirable.
In the imaging process, due to the influences of the factors of non-uniformity and defocusing of the illumination light source, the difference of the absorption rate and the reflectivity of the surface of the detected object to light rays and the like, the image background can have a non-uniform phenomenon, and the detection and the extraction of subsequent defects can be seriously influenced. Aiming at the problem, a method based on image morphology is designed to carry out background correction on the acquired image, so that the nonuniformity compensation can be better carried out on the image background. Generally, threshold segmentation is one of the commonly used and simple and effective image segmentation methods. The one-dimensional maximum inter-class variance method of the typical threshold segmentation algorithm has the advantages of good segmentation effect, wide application range, simplicity and high efficiency, is a self-adaptive threshold selection algorithm, and can effectively avoid the limitation of the threshold determination algorithm. The method has the best effect on image segmentation with a histogram in a bimodal structure (the image background and the target are obviously separated). The searching of the boundary between the target and the background is the key of image segmentation, the project provides an improved image segmentation algorithm combining image gradient information and a one-dimensional maximum inter-class variance method, and the target in the groove region can be accurately extracted by using the image gradient information to better distinguish the edge of the groove target from the background. And finally, calculating information such as the center line, the width and the like of the groove.
An automatic assembly pipe penetration monitoring method comprises a product A and a product B, and comprises the following steps:
the method comprises the following steps: assembling product a and product B:
step two: the concentricity is measured by adopting a machine vision mode, the pipe penetrating process is monitored in real time, and image analysis is carried out:
visually monitoring a hole with the diameter of 25mm of the product B and a cylinder with the diameter of 23mm of the product A, measuring the coaxial deviation between a thin tube with the diameter of 3mm of the product A and the hole with the diameter of 25mm, calculating the rotation angle required by the product A, and displaying the expected movement position by a track;
and (3) performing clearance measurement on the phi 3mm thin tube and the R2mm hole in the radius direction, and feeding back a circumferential multipoint measurement value.
Furthermore, the product A is made of stainless steel, the diameter of the product is phi 250mm, the surface roughness Ra0.8-1.6, the product A is fixed on the rotatable bracket, and the rotation precision is 0.01 degrees; a phi 3 thin tube is arranged at the position of the top end 30mm away from the central axis, the length of the thin tube is 200mm, the parallelism is less than phi 0.2mm, and the head of the thin tube is provided with a phi 23 cylindrical head with the length of 40 mm; the product is provided with a deep groove with the width of 10mm and the width of 3mm and a scribed line with the width of 0.2mm in the circumferential direction.
Further, the product B is made of powder die-casting materials, the surface roughness is Ra1.6-3.2, the product A is grabbed by a robot to be sleeved, the diameter is 300mm, the height is 250mm, and the wall thickness is 25mm; a vertical phi 25mm large hole is formed at the position, 30mm away from the central axis, of the top end of the product, and an R2mm half hole is formed at the edge of the large hole, wherein the distance from the center of the half hole to the central axis of the product is 30mm; the product also has a deep groove with the width of 10mm and the width of 3mm and a scribed line with the width of 0.2mm in the circumferential direction.
Further, the first step comprises:
the robot grabs the product B to a position to be assembled, and the position is marked as a position 1;
the robot grabs the product B to vertically move downwards, so that the large hole of the product B is assembled with the cylindrical head of the product A, and the position is marked as a position 2;
the product B descends to a position 5mm above the product A. At the moment, a phi 3mm thin tube is coaxial with a phi 25mm large hole theory, and the position is marked as a position 3;
the product A rotates to 24 degrees, so that the phi 3mm thin tube is screwed into the R2mm half hole, the phi 3mm thin tube is coaxial with the R2mm half hole, the uniform gap is ensured, the interference does not occur, and the position is marked as position 4;
and the product B continues to descend for 5mm, so that the lower end faces are attached, and after the assembly is finished, the position is marked as position 5.
Further, the concentricity measurement includes:
at the position 3, performing visual synthesis by using a left camera and a right camera, and performing visual correction; performing edge processing on the thin tube and the hole, extracting an edge arc, fitting the circle center, wherein the circle distance is the deviation of the edge arc and the circle center, and the measurement precision is less than or equal to 0.1 mm;
and at the position 4, performing edge treatment on the thin tube and the R2mm hole, extracting an edge arc, fitting the circle center to obtain the deviation distance between the thin tube and the hole wall, wherein the measurement precision is less than or equal to 0.1 mm.
Further, the process of pipe penetration of the semi-spherical product is verified through experiments, whether verification software can carry out accurate quantitative analysis on product image data or not is verified, deviation data of the thin pipe and the hole is obtained and fed back to the robot for position adjustment, and the qualified range is 0.1 mm. The single detection time is less than 10 s.
Example 1:
as shown in fig. 1-2:
measuring the circumferential direction:
hemispherical product B was assembled and a pipe penetration measurement was taken at position 3. Firstly, a camera is calibrated through a calibration board to obtain pixel size data. In visual hardware, 2 black and white cameras with 500W pixels are adopted, a SonyIMX 226CMOS photosensitive chip is adopted in a MER-500-81220-9GM model, image data are transmitted through a GigE data interface, and an I/O (GPIO) interface is integrated to provide a cable locking device, so that the cable locking device can stably work in various severe environments and is an industrial camera product with high reliability and high cost performance. And a telecentric lens is arranged, and the camera is fixed on the table top where the rotating base is positioned and is used for viewing the product B.
The lens adopts a telecentric lens, the model is DTCM120-56-AL, the field range is 45x32mm, and the irradiation light source adopts a ring-shaped LED light source. Under the field range, the imaging resolution of the camera is 2592(H) multiplied by 1944(V), namely, the initial detection precision of 16um in the unit pixel can reach the high precision of 1.6um by matching with the sub-pixel processing.
The external dimension of the camera is 29 multiplied by 29mm, the lens is 147 multiplied by 78mm, and the working distance is 200 mm.
Firstly, collecting images of two cameras, correcting the images, splicing the images to obtain complete images of the tubule and the hole, detecting edges, extracting arcs, fitting circle centers, and calculating the coordinate difference of the circle centers of the tubule and the hole.
Since the camera monitors the canal hole by looking obliquely, the image is seen as a large image and a small image, and therefore the image needs to be corrected by perspective transformation. Perspective transformation maps the current image to another plane by projection, like a motion picture projector in a movie theater, and if either the curtain or tape is not perpendicular 90 degrees to the optical fiber from the projector, the image projected onto the curtain will be distorted.
The correction of the distorted image by perspective transformation needs to obtain the coordinates of a group of 4 points of the distorted image and the coordinates of a group of 4 points of the target image, a transformation matrix of the perspective transformation can be calculated through the two groups of coordinate points, and then the transformation of the transformation matrix is executed on the whole original image, so that the image correction can be realized.
After the images are corrected, 2 cameras simultaneously look at the pore, so that the 2 collected images have overlapping parts, and the 2 images are spliced. When splicing, firstly obtaining the characteristic points of the two images, then calculating an affine transformation matrix according to the characteristic points of the 2 images, and finally splicing according to the affine transformation matrix.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (6)
1. An automatic assembly pipe penetration monitoring method comprises a product A and a product B, and is characterized by comprising the following steps:
the method comprises the following steps: assembling product a and product B:
step two: the concentricity is measured by adopting a machine vision mode, the pipe penetrating process is monitored in real time, and image analysis is carried out:
visually monitoring a hole with the diameter of 25mm of the product B and a cylinder with the diameter of 23mm of the product A, measuring the coaxial deviation between a thin tube with the diameter of 3mm of the product A and the hole with the diameter of 25mm, calculating the rotation angle required by the product A, and displaying the expected movement position by a track;
and (3) performing clearance measurement on the phi 3mm thin tube and the R2mm hole in the radius direction, and feeding back a circumferential multipoint measurement value.
2. The automatic assembling pipe-penetrating monitoring method according to claim 1, wherein the product A is made of stainless steel, the diameter of the product is phi 250mm, the surface roughness Ra0.8-1.6 is fixed on a rotatable bracket, the rotation precision is 0.01 degrees, a phi 3 thin pipe is arranged at the position, 30mm away from the central axis, of the top end of the thin pipe, the length of the thin pipe is 200mm, the parallelism is less than phi 0.2mm, and the head of the thin pipe is provided with a phi 23 cylinder head 40mm long; the product is provided with a deep groove with the width of 10mm and the width of 3mm and a scribed line with the width of 0.2mm in the circumferential direction.
3. The automatic assembling pipe-penetrating monitoring method of claim 1, wherein the product B is made of powder die-casting materials, the surface roughness is Ra1.6-3.2, the product A is sleeved by a robot, the diameter is 300mm, the height is 250mm, the wall thickness is 25mm, a vertical phi 25mm large hole is arranged at a position 30mm away from the central axis of the top end of the product, an R2mm half hole is arranged at the edge of the large hole, the center of the half hole is 30mm away from the central axis of the product, and a 10mm deep groove with the width of 3mm and a 0.2mm wide scribed line are arranged in the circumferential direction of the product.
4. The automated assembly penetration monitoring method of claim 1, wherein the first step comprises:
the robot grabs the product B to a position to be assembled, and the position is marked as a position 1;
the robot grabs the product B to vertically move downwards, so that the large hole of the product B is assembled with the cylindrical head of the product A, and the position is marked as a position 2;
the product B descends to a position 5mm above the product A, at the moment, a phi 3mm thin pipe is coaxial with a phi 25mm large hole in theory, and the position is marked as a position 3;
the product A rotates to 24 degrees, so that the phi 3mm thin tube is screwed into the R2mm half hole, the phi 3mm thin tube is coaxial with the R2mm half hole, the uniform gap is ensured, the interference does not occur, and the position is marked as position 4;
and the product B continues to descend for 5mm, so that the lower end faces are attached, and after the assembly is finished, the position is marked as position 5.
5. An automated assembly puncture monitoring method according to claim 1, wherein the concentricity measurement comprises:
at the position 3, performing visual synthesis by using a left camera and a right camera, and performing visual correction; performing edge processing on the thin tube and the hole, extracting an edge arc, fitting the circle center, wherein the circle distance is the deviation of the edge arc and the circle center, and the measurement precision is less than or equal to 0.1 mm;
and at the position 4, performing edge treatment on the thin tube and the R2mm hole, extracting an edge arc, fitting the circle center to obtain the deviation distance between the thin tube and the hole wall, wherein the measurement precision is less than or equal to 0.1 mm.
6. The automatic assembly pipe penetration monitoring method according to claim 1, wherein experimental verification is performed on a semi-spherical product pipe penetration process, whether verification software can perform accurate quantitative analysis on product image data is verified, deviation data of a thin pipe and a hole is obtained, the deviation data is fed back to a robot for position adjustment, the qualified range is 0.1mm, and the single detection time is less than 10 s.
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| CN114918637A (en) * | 2022-05-30 | 2022-08-19 | 中国电子科技集团公司第十四研究所 | Visual positioning method of shaft hole assembling robot |
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| CN114918637A (en) * | 2022-05-30 | 2022-08-19 | 中国电子科技集团公司第十四研究所 | Visual positioning method of shaft hole assembling robot |
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