CN113701626A - 3D machine vision detection method for automobile longitudinal beam - Google Patents
3D machine vision detection method for automobile longitudinal beam Download PDFInfo
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- CN113701626A CN113701626A CN202110913528.8A CN202110913528A CN113701626A CN 113701626 A CN113701626 A CN 113701626A CN 202110913528 A CN202110913528 A CN 202110913528A CN 113701626 A CN113701626 A CN 113701626A
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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
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
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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
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
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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
- G01B11/08—Measuring arrangements characterised by the use of optical techniques for measuring diameters
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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
- G01B11/14—Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
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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
- G01B11/16—Measuring arrangements characterised by the use of optical techniques for measuring the deformation in a solid, e.g. optical strain gauge
- G01B11/167—Measuring arrangements characterised by the use of optical techniques for measuring the deformation in a solid, e.g. optical strain gauge by projecting a pattern on the object
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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
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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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- 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
- G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
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- Length Measuring Devices By Optical Means (AREA)
- Length Measuring Devices With Unspecified Measuring Means (AREA)
Abstract
The invention discloses a 3D machine vision detection method for an automobile longitudinal beam, which comprises the following steps: 5 laser profilometers of the same type are configured and arranged in a U-shaped structure; scanning a calibration block by using 5 laser profilometers of the same model, and calculating the spatial position relation of the laser profilometers in a world coordinate system by using rough matching and precise matching; scanning a workpiece to be detected by using 5 laser contourmeters of the same model to obtain point cloud data, performing conversion splicing on the point cloud data through a spatial position relationship to obtain integral point cloud data of the workpiece to be detected, and solving the length, hole position degree, aperture, hole interval, ventral surface-airfoil surface hole edge distance, airfoil surface-ventral surface hole edge distance, ventral surface planeness, airfoil surface planeness, ventral surface warping, airfoil surface lateral bending, end head deformation size, maximum distortion deflection and R angle of the workpiece to be detected according to the integral point cloud data. The method greatly retains the three-dimensional space information of the longitudinal beam, can obtain a more accurate detection result of the longitudinal beam, and can further more accurately judge whether the longitudinal beam meets the factory standards.
Description
Technical Field
The invention relates to the technical field of longitudinal beam detection in the automobile industry, in particular to a detection method for detecting whether an automobile longitudinal beam meets factory standards or not by using 3D machine vision.
Background
The longitudinal beam is an important component of a chassis frame assembly of the heavy truck, the longitudinal beam and the cross beam assembly are connected and assembled through bolts or rivets to form the frame assembly, the longitudinal beam is generally of a hot-rolled steel plate U-shaped structure, the plate thickness is 4-12mm, the length is 4-14m, the width of an airfoil surface is 55-100mm, and holes with different sizes are designed on the ventral surface or the airfoil surface of the longitudinal beam and used for mounting various parts or assemblies of the whole truck. The accuracy of hole site processing in the longeron will influence the mounted position precision of other spare parts, has important influence to the final assembly quality of whole car. All holes in the longitudinal beam are processed in a numerical control punching process mode, a single or a plurality of hydraulic punching units punch the blank according to a punching program compiled by a longitudinal beam drawing, and a servo motor controls the movement of the plate to punch the holes in sequence. The automobile longitudinal beam punching machine tool often causes hole leakage due to the reasons of punch cutter breakage, pulse interference and the like, causes hole error due to the reasons of plate position deviation, punch cutter abrasion and the like, and can cause material waste, delayed production and other adverse consequences if not found in time, so that online detection equipment for the automobile longitudinal beam becomes an important requirement of automobile frame manufacturers. The traditional detection mode is that the box ruler and the vernier caliper contrast two-dimensional drawing are used manually, the hole positions are detected one by one, the defects of missing detection, reading error, long detection time and the like easily occur, the box ruler cannot meet the requirement of dimensional tolerance precision when the long-distance hole distance is measured, the requirements of modern industrial production are not met, the longitudinal beam punching detection equipment based on the 2D machine vision technology carries out analysis and detection in the picture obtained by shooting the longitudinal beam from the camera, the problems that the fusion effect of an image splicing algorithm is poor, the robustness to the external illumination condition is low, the hole is deformed, the detection error is large and the like exist, the flatness of the longitudinal beam cannot be detected, the hole edge distance cannot be accurately detected, and the situations that various bends and the like occur on the longitudinal beam surface and the wing surface cannot be responded.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, the invention aims to provide a 3D machine vision detection method for automobile longitudinal beams.
In order to achieve the purpose, the embodiment of the invention provides a 3D machine vision detection method for an automobile longitudinal beam, which comprises the following steps: step S1, configuring 5 laser profilometers with the same model and arranging the laser profilometers in a U-shaped structure; step S2, scanning a calibration block by using the 5 laser profilers of the same model, and calculating the spatial position relation of the laser profilers in a world coordinate system by using rough matching and fine matching; step S3, scanning a workpiece to be detected by using the 5 laser profilers of the same type to obtain point cloud data, and performing conversion splicing on the point cloud data through the spatial position relation to obtain integral point cloud data of the workpiece to be detected, wherein the integral point cloud data comprises ventral surface point cloud data and two-side airfoil surface point cloud data; and step S4, solving the length, hole position degree, aperture, hole spacing, ventral surface-airfoil surface hole edge distance, airfoil surface-ventral surface hole edge distance, ventral surface planeness, airfoil surface planeness, ventral surface warping, airfoil surface lateral bending, end deformation size, maximum distortion deflection and R angle of the workpiece to be detected according to the integral point cloud data.
According to the 3D machine vision detection method for the automobile longitudinal beam, the size of the longitudinal beam is 1400cm multiplied by 30cm multiplied by 8cm, 3min is consumed from the scanning start stage to the detection end stage, the detection precision reaches 0.1mm, the repeated detection precision is 0.03mm, the three-dimensional space information of the longitudinal beam is reserved to the greatest extent, and the detection results of length, hole position degree, aperture, hole interval, ventral surface-ventral surface hole edge distance, aerofoil surface-ventral surface hole edge distance, ventral surface planeness, aerofoil planeness, ventral surface warping (ventral surface straightness), aerofoil side bending (aerofoil straightness), end deformation (aerofoil perpendicularity), maximum distortion, R angle and the like can be obtained more accurately through three-dimensional data detection, so that whether the longitudinal beam meets the factory standards or not can be judged more accurately.
In addition, the method for detecting the 3D machine vision of the automobile longitudinal beam according to the above embodiment of the present invention may further have the following additional technical features:
further, in an embodiment of the present invention, in step S1, any three laser profiles of the same type are disposed right above the ventral surface of the calibration block, and the other two laser profiles of the same type are disposed on the two side wing surfaces of the calibration block, respectively.
Further, in an embodiment of the present invention, the calibration block is designed based on a principle that point cloud data in a private field of view of a single laser profiler is used as a main point and point cloud data in a public field of view of a plurality of laser profilers is used as an auxiliary point, and digital-analog data of the calibration block is retained in the design process, wherein three groups of holes are arranged on a ventral surface of the calibration block, a group of holes are respectively arranged on two side wing surfaces, and three holes are arranged in each group of holes.
Further, in an embodiment of the present invention, the step S2 specifically includes: step S201, scanning the calibration blocks by using each laser profiler to obtain five calibration block point cloud data, wherein each calibration block point cloud data comprises 3 complete hole information; step S202, denoising and projecting point cloud data in the hole to a local plane and fitting a circle to obtain a point cloud circle center coordinate; and S203, roughly matching the point cloud circle center coordinates with the circle center coordinates in the digital-to-analog data, finely matching the point cloud data in the public view after rough matching, and calculating the spatial position relation of the laser profilometer under a world coordinate system.
Further, in an embodiment of the present invention, in step S4, the maximum value is taken as the length, which is measured from a position 30mm below the ventral surface of the workpiece to be measured to both wing surfaces.
Further, in an embodiment of the present invention, in step S4, the point cloud data obtained by scanning with the 5 laser profilers of the same model are respectively subjected to rapid triangulation to obtain a triangular mesh, triangular mesh hole boundary points are extracted, a point cloud fitting plane within a range of 5-10mm from a hole is taken, the triangular mesh hole boundary points are projected into the point cloud fitting plane to obtain projection points, a circle fitting operation is performed on the projection points, and the hole location degree and the hole diameter are calculated; comparing the hole position degree with the digital-analog data of the workpiece to be detected, and calculating the deviation of the position degree; and calculating the distance between the apertures to obtain the aperture spacing.
Further, in an embodiment of the present invention, in step S4, the point cloud in the hole, the point cloud near the hole, and the boundary point cloud in the ventral surface point cloud and the two side airfoil surface point clouds are removed, and planes are respectively fitted, a distance between a centre of the ventral surface hole and an airfoil surface plane is calculated as the ventral surface-ventral surface hole edge distance, and a distance between a centre of the airfoil surface hole and the ventral surface plane is calculated as the airfoil surface-ventral surface hole edge distance.
Further, in an embodiment of the present invention, in step S4, calculating a distance between the abdominal point cloud data and an abdominal plane, screening out a point set with a distance exceeding 0.3mm, classifying the point set by a density-based clustering algorithm to remove outliers, and using a maximum distance in the distances between the points in the point set and the plane as the abdominal plane flatness; and calculating the distance between the point cloud data of the two airfoil surfaces and the respective airfoil surface plane, screening out a point set with the distance exceeding 0.3mm, classifying the point set by a density-based clustering algorithm to remove outliers, and taking the maximum distance from the point in the point set to the plane as the flatness of the airfoil surface.
Further, in an embodiment of the present invention, in step S4, the position of the center line of the ventral surface is taken, and both ends are respectively moved away from 30mm for measurement, a point which is less than 0.1mm away from the plane passing through the center line of the ventral surface is taken from the point cloud data of the ventral surface, the distance from the point to the center line of the ventral surface is calculated, and the maximum value is taken as the warpage of the ventral surface; and (3) measuring by avoiding two ends by 200mm from the position 30mm below the ventral surface and the position of the central line of the airfoil surface, taking a point which is less than 0.1mm away from the plane passing through the central line of the airfoil surface in the point cloud data of the airfoil surface, calculating the distance from the point to the central line of the airfoil surface, and taking the maximum value as the lateral curvature of the airfoil surface.
Further, in an embodiment of the present invention, in step S4, point cloud data of the workpiece to be measured at positions 30mm and 150mm from two ends are respectively obtained, and an included angle between the airfoil surface and the ventral surface is calculated as the deformation dimension of the ends; taking four points at each of the positions of 30 multiplied by 50 at the four corners of the ventral surface, defining a reference plane by the three points, measuring the distance from the fourth point to the reference plane, and taking the maximum absolute value as the maximum distortion deflection; and (3) point cloud data of the bending part of the workpiece to be measured is taken, a cylinder is fitted, and the excircle radius R obtained through calculation is used as the R angle.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The foregoing and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a flow chart of a method for 3D machine vision inspection of automobile stringers in accordance with one embodiment of the present disclosure;
FIG. 2 is a schematic structural view of a laser profiler mount according to one embodiment of the present invention;
FIG. 3 is a schematic diagram of a calibration block digital-to-analog architecture according to an embodiment of the present invention;
FIG. 4 is a schematic illustration of a calculated length of one embodiment of the present invention;
FIG. 5 is a schematic illustration of calculating ventral warpage in accordance with an embodiment of the present invention;
FIG. 6 is a schematic illustration of calculating an airfoil cornering according to an embodiment of the invention;
FIG. 7 is a schematic diagram of a computing tip deformation according to one embodiment of the present invention;
figure 8 is a schematic illustration of calculating maximum torsional deflection according to one embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The following describes a flow chart of a 3D machine vision detection method for automobile longitudinal beams, which is proposed according to an embodiment of the invention, with reference to the attached drawings.
Fig. 1 is a flowchart of a 3D machine vision inspection method for automobile longitudinal beams according to an embodiment of the present invention.
As shown in fig. 1, the 3D machine vision detection method for the automobile longitudinal beam comprises the following steps:
in step S1, 5 laser profilers of the same model are configured and arranged in a U-shaped configuration.
Specifically, according to the size of a workpiece to be measured, the laser profilers are subjected to model selection and the using number of the laser profilers is determined, as shown in fig. 2, a laser profiler support is designed according to the visual field of the laser profilers, the scheme adopts a U-shaped design, any three laser profilers of the same model are arranged right above the ventral surface of a calibration block, and the rest two laser profilers of the same model are respectively arranged on the wing surfaces on two sides of the calibration block, so that all the laser profilers are cooperated to have the visual field fully covering the workpiece.
In step S2, the calibration block is scanned by 5 laser profilers of the same model, and the spatial position relationship of the laser profilers in the world coordinate system is calculated by rough matching and fine matching.
It should be noted that the calibration block is designed to accurately calculate the position relationship between a plurality of laser profilers, and therefore, as shown in fig. 3, the calibration block according to the embodiment of the present invention is designed based on the principle that point cloud data in a private field of a single laser profiler is used as a main point and point cloud data in a public field of a plurality of laser profilers is used as an auxiliary point, digital-analog data of the calibration block is retained in the design process, the calibration block is compared with the digital-analog data through three-coordinate measurement, and the processing accuracy is 0.01mm, wherein three groups of holes are disposed on the ventral surface of the calibration block, a group of holes are disposed on the airfoil surfaces on both sides, and three holes are disposed in each group of holes. The patterns in the public vision field of the plurality of laser profilometers are designed into a high-low fluctuation shape, such as a trapezoidal groove, a spherical groove, an arrow-shaped groove and the like, and the patterns can be fully scanned by the laser profilometers related to the areas in the public vision field, and a blind area cannot exist, so that the part of the patterns cannot be completely reflected in point cloud data.
Specifically, each laser profiler is utilized to scan a calibration block to obtain five pieces of calibration block point cloud data, wherein each piece of calibration block point cloud data comprises 3 pieces of complete hole information; denoising point cloud data in the hole, projecting the point cloud data to a local plane, fitting a circle, and obtaining a point cloud circle center coordinate; roughly matching the point cloud center coordinates with the center coordinates in the digital-analog data, finely matching the point cloud coordinates in the public view after rough matching, and calculating the spatial position relation of the laser profilometer under a world coordinate system.
In step S3, scanning the workpiece to be measured with 5 laser profilers of the same model to obtain point cloud data, and performing conversion and splicing on the point cloud data through a spatial position relationship to obtain integral point cloud data of the workpiece to be measured, where the integral point cloud data includes ventral surface point cloud data and both side airfoil surface point cloud data.
In step S4, the length, hole position degree, hole diameter, hole pitch, ventral surface-airfoil surface hole margin, airfoil surface-ventral surface hole margin, ventral surface flatness, airfoil surface flatness, ventral surface warpage, airfoil surface lateral bending, end deformation size, maximum distortion deflection and R angle of the workpiece to be measured are solved according to the integral point cloud data.
Further, as shown in fig. 4, the length is measured from the position 30mm below the ventral surface of the workpiece to be measured toward both wing surfaces, and the maximum value is taken as the length.
Further, in an embodiment of the present invention, step S2 specifically includes:
step S201, scanning the calibration blocks by using each laser profiler to obtain five calibration block point cloud data, wherein each calibration block point cloud data comprises 3 complete hole information;
step S202, denoising and projecting point cloud data in the hole to a local plane and fitting a circle to obtain a point cloud circle center coordinate;
and S203, roughly matching the point cloud circle center coordinates with the circle center coordinates in the digital-to-analog data, finely matching the point cloud data in the public view after rough matching, and calculating the spatial position relation of the laser profilometer under a world coordinate system.
Specifically, the hole circle center position and the hole circle radius are calculated from the point cloud data obtained by scanning of a single laser profiler, so that the loss in calculation time can be greatly reduced. According to the embodiment of the invention, on the premise of keeping hole boundary point data, data in a hole of point cloud data are removed, because the point cloud data obtained by scanning of a laser profiler are processed into uniform intervals in the direction of X, Y, rapid triangulation can be carried out, the boundary points of holes of a triangular grid are extracted, a point cloud fitting plane within the range of 5-10mm from the hole is taken, the boundary points of the holes of the triangular grid are projected into the plane, and projected points obtained after the boundary points are projected are subjected to circle fitting operation to calculate the coordinates and the radius of the center of the hole; converting the hole center coordinates through the space position relation of the laser profiler, comparing the hole center coordinates with a workpiece digital analog, and calculating the position degree deviation; and calculating the distance between the circle centers to obtain hole spacing information.
Further, in step S4, the point cloud in the hole, the point cloud near the hole, and the boundary point cloud in the ventral surface point cloud and the airfoil surface point clouds on both sides are removed, and the planes are fitted respectively, the distance between the center of the ventral surface hole and the airfoil surface plane is calculated as the ventral surface-airfoil surface hole edge distance, and the distance between the center of the airfoil surface hole and the ventral surface plane is calculated as the airfoil surface-ventral surface hole edge distance.
Further, in step S4, calculating a distance between the abdominal surface point cloud data and the abdominal surface plane, screening out a point set with a distance exceeding 0.3mm, removing outliers by classification, and taking a maximum distance between a point in the point set and the plane as an abdominal surface flatness; and calculating the distance between the point cloud data of the two airfoil surfaces and the airfoil surface plane, screening out a point set with the distance exceeding 0.3mm, removing outliers through classification, and taking the maximum distance in the distance between the points in the point set and the plane as the airfoil surface flatness.
Further, as shown in fig. 5, in step S4, the position of the center line of the ventral surface is taken, the two ends are respectively moved away by 30mm for measurement, the point which is less than 0.1mm away from the plane passing through the center line of the ventral surface is taken from the point cloud data of the ventral surface, the distance from the point to the center line of the ventral surface is calculated, and the maximum value is taken as the warpage of the ventral surface;
as shown in fig. 6, the two ends of the airfoil surface are moved back and forth by 200mm from the position 30mm below the ventral surface and the position of the central line of the airfoil surface for measurement, the point which is less than 0.1mm away from the plane passing through the central line of the airfoil surface is taken from the point cloud data of the airfoil surface, the distance from the point to the central line of the airfoil surface is calculated, and the maximum value is taken as the lateral camber of the airfoil surface.
Further, as shown in fig. 7, in step S4, point cloud data of the workpiece to be measured at positions 30mm and 150mm from the two ends are respectively taken, and an included angle between the airfoil surface and the ventral surface is calculated as an end deformation dimension; as shown in fig. 8, four points are taken at each of the positions of 30 × 50 on the four corners of the ventral surface, three points define a reference plane, the distance from the fourth point to the reference plane is measured, and the maximum absolute value is taken as the maximum distortion deflection; and (3) point cloud data of the bending part of the workpiece to be measured is taken, a cylinder is fitted, and the excircle radius R obtained through calculation is used as an R angle.
According to the 3D machine vision detection method for the automobile longitudinal beam, provided by the embodiment of the invention, the size of the longitudinal beam is 1400cm multiplied by 30cm multiplied by 8cm, 3min is consumed from the scanning start stage to the detection end stage, the detection precision reaches 0.1mm, the repeated detection precision is 0.03mm, the three-dimensional space information of the longitudinal beam is greatly reserved, and the detection results of length, hole position degree, aperture, hole spacing, ventral surface-flank hole edge distance, aerofoil surface-flank hole edge distance, ventral surface planeness, aerofoil planeness, ventral surface warping (ventral surface straightness), aerofoil side bending (aerofoil straightness), end deformation (aerofoil perpendicularity), maximum distortion deflection, R angle and the like can be more accurately obtained through three-dimensional data detection, so that whether the longitudinal beam meets the factory standards or not can be more accurately judged.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. The 3D machine vision detection method for the automobile longitudinal beam is characterized by comprising the following steps:
step S1, configuring 5 laser profilometers with the same model and arranging the laser profilometers in a U-shaped structure;
step S2, scanning a calibration block by using the 5 laser profilers of the same model, and calculating the spatial position relation of the laser profilers in a world coordinate system by using rough matching and fine matching;
step S3, scanning a workpiece to be detected by using the 5 laser profilers of the same type to obtain point cloud data, and performing conversion splicing on the point cloud data through the spatial position relation to obtain integral point cloud data of the workpiece to be detected, wherein the integral point cloud data comprises ventral surface point cloud data and two-side airfoil surface point cloud data;
and step S4, solving the length, hole position degree, aperture, hole spacing, ventral surface-airfoil surface hole edge distance, airfoil surface-ventral surface hole edge distance, ventral surface planeness, airfoil surface planeness, ventral surface warping, airfoil surface lateral bending, end deformation size, maximum distortion deflection and R angle of the workpiece to be detected according to the integral point cloud data.
2. The 3D machine vision detection method for the automobile longitudinal beam as claimed in claim 1, wherein in the step S1, any three laser profiles of the same type are arranged right above the ventral surface of the calibration block, and the other two laser profiles of the same type are respectively arranged on the two side wing surfaces of the calibration block.
3. The 3D machine vision detection method for the automobile longitudinal beam as claimed in claim 1, wherein the calibration block is designed by adopting a principle that point cloud data in a private view of a single laser profiler is used as a main part and point cloud data in a public view of a plurality of laser profilers is used as an auxiliary part, digital-analog data of the calibration block are stored in the design process, three groups of holes are arranged on the ventral surface of the calibration block, two side wing surfaces are respectively provided with one group of holes, and three holes are arranged in each group of holes.
4. The method for 3D machine vision inspection of automobile longitudinal beams according to claim 1, wherein the step S2 specifically comprises the following steps:
step S201, scanning the calibration blocks by using each laser profiler to obtain five calibration block point cloud data, wherein each calibration block point cloud data comprises 3 complete hole information;
step S202, denoising and projecting point cloud data in the hole to a local plane and fitting a circle to obtain a point cloud circle center coordinate;
and S203, roughly matching the point cloud circle center coordinates with the circle center coordinates in the digital-to-analog data, finely matching the point cloud data in the public view after rough matching, and calculating the spatial position relation of the laser profilometer under a world coordinate system.
5. The 3D machine vision inspection method for automobile longitudinal beams according to claim 1, wherein in step S4, the maximum value is taken as the length, which is measured from a position 30mm below the ventral surface of the workpiece to be inspected to both wing surfaces.
6. The automobile longitudinal beam 3D machine vision detection method as claimed in claim 1, wherein in step S4, point cloud data obtained by scanning the 5 laser profilers of the same model are respectively subjected to rapid triangulation to obtain a triangular mesh, triangular mesh hole boundary points are extracted, a point cloud fitting plane within a range of 5-10mm from a hole is taken, the triangular mesh hole boundary points are projected into the point cloud fitting plane to obtain projection points, circle fitting operation is performed on the projection points, and the hole position and the hole diameter are calculated; comparing the hole position degree with the digital-analog data of the workpiece to be detected, and calculating the deviation of the position degree; and calculating the distance between the apertures to obtain the aperture spacing.
7. The 3D machine vision detection method for the automobile longitudinal beam as claimed in claim 1, wherein in the step S4, the point cloud in the hole, the point cloud near the hole and the boundary point cloud in the ventral surface point cloud and the two side airfoil surface point clouds are removed, planes are respectively fitted, the distance between the center of the ventral surface hole and the airfoil surface is calculated as the ventral surface-airfoil surface hole edge distance, and the distance between the center of the airfoil surface hole and the ventral surface plane is calculated as the airfoil surface-ventral surface hole edge distance.
8. The automobile longitudinal beam 3D machine vision detection method of claim 1, wherein in the step S4, the distance between the ventral point cloud data and a ventral plane is calculated, a point set with the distance exceeding 0.3mm is screened out, the point set is classified through a density-based clustering algorithm, and outliers are removed, wherein the maximum distance in the distance between a point in the point set and the plane is used as the ventral plane degree;
and calculating the distance between the point cloud data of the two airfoil surfaces and the respective airfoil surface plane, screening out a point set with the distance exceeding 0.3mm, classifying the point set by a density-based clustering algorithm to remove outliers, and taking the maximum distance from the point in the point set to the plane as the flatness of the airfoil surface.
9. The automobile longitudinal beam 3D machine vision detection method of claim 1, wherein in step S4, the position of a ventral surface center line is taken, two ends of the ventral surface center line are respectively avoided by 30mm for measurement, a point which is less than 0.1mm away from a plane passing through the ventral surface center line is taken from the ventral surface point cloud data, the distance from the point to the ventral surface center line is calculated, and the maximum value is taken as the ventral surface warpage;
and (3) measuring by avoiding two ends by 200mm from the position 30mm below the ventral surface and the position of the central line of the airfoil surface, taking a point which is less than 0.1mm away from the plane passing through the central line of the airfoil surface in the point cloud data of the airfoil surface, calculating the distance from the point to the central line of the airfoil surface, and taking the maximum value as the lateral curvature of the airfoil surface.
10. The automobile longitudinal beam 3D machine vision detection method as claimed in claim 1, wherein in step S4, point cloud data of the workpiece to be detected at positions 30mm and 150mm from two ends are respectively taken, and an included angle between an airfoil surface and a ventral surface is calculated to serve as the deformation size of the ends;
taking four points at each of the positions of 30 multiplied by 50 at the four corners of the ventral surface, defining a reference plane by the three points, measuring the distance from the fourth point to the reference plane, and taking the maximum absolute value as the maximum distortion deflection;
and (3) point cloud data of the bending part of the workpiece to be measured is taken, a cylinder is fitted, and the excircle radius R obtained through calculation is used as the R angle.
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