CN115790440A - Profile tolerance measuring method and measuring system based on 3D scanning - Google Patents
Profile tolerance measuring method and measuring system based on 3D scanning Download PDFInfo
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Abstract
The invention provides a profile tolerance measuring method and a measuring system based on 3D scanning, wherein the measuring method comprises the following steps: (a) Acquiring 3D point cloud data of a surface to be detected based on a depth coordinate; (b) Reconstructing a three-dimensional model curved surface corresponding to the surface to be measured based on the acquired 3D point cloud data; and (c) calculating the profile degree of the surface to be measured according to the three-dimensional model curved surface and the theoretical point cloud model curved surface of the surface to be measured.
Description
Technical Field
The invention relates to the field of machine vision measurement, in particular to a profile tolerance measuring method and system based on 3D scanning.
Background
In the production of automobile parts, curved surface designs are increasingly used, such as vehicle doors, vehicle body shells and the like. However, due to the process parameters and the complexity of the curved surface design, the accuracy of the curved surface dimension of the workpiece is easily disturbed, and therefore, the surface profile of the workpiece needs to be measured. The surface profile degree reflects the variation condition of the measured actual profile relative to the ideal profile, and the main description index is a profile degree error. The measurement of the profile degree of the workpiece surface has great significance on the precision and the sealing performance of vehicle assembly.
The method for measuring the surface profile error mainly comprises the following steps: profiling device measurement, cross-sectional profile template measurement, optical tracking profile gauge measurement, three-coordinate measuring device measurement, and the like, wherein three-coordinate measuring device measurement methods can be further divided into three-coordinate measuring machine measurement methods and structured light methods. In addition to the three-coordinate measuring device measurement, the other three measurement methods all need to provide a theoretical profile template, and compare the actual profile surface of the measured workpiece with the profile surface of the theoretical profile template to determine the surface profile error value of the workpiece. The three methods are only suitable for inspection in the production process of mass workpieces, and the measurement precision is low.
Although the measuring method of the three-coordinate measuring machine has high precision, the single-point scanning speed is low, the efficiency is low, and the method cannot be applied to the detection of the profile tolerance of a production-level large-area surface. The structured light method is suitable for measuring covering parts with large areas and easy deformation.
Disclosure of Invention
The invention has the main advantages that the method and the system for measuring the profile tolerance based on the 3D scanning are provided, the sampling frequency of the method based on the 3D scanning is high, a large amount of position information can be obtained in a short time to carry out three-dimensional reconstruction, the speed is high, and the efficiency is high.
Another advantage of the present invention is to provide a method and a system for measuring a profile based on 3D scanning, wherein the method has high scanning accuracy based on a 3D camera, and can meet the high-accuracy measurement requirement of precision product production.
Another advantage of the present invention is to provide a profile measurement method and a measurement system based on 3D scanning, wherein the measurement method employs non-contact point taking, and uses a 3D camera to scan a curved surface to be measured of a workpiece along the XY coordinate axis direction, so as to avoid damage to the surface of the workpiece by the contact point taking, and achieve fast sampling frequency and high precision.
Another advantage of the present invention is to provide a method and a system for measuring a profile tolerance based on 3D scanning, wherein the method plans an optimal scanning path based on the principles of dynamic programming and interior point method, obtains a scanning scheme with the shortest total length of the scanning path and the fewest number of turns, and achieves a large amount of available data obtained in a unit time and high efficiency.
Another advantage of the present invention is to provide a method and a system for measuring a profile based on 3D scanning, wherein the method performs three-dimensional reconstruction on a surface to be measured, so that geometric information of the surface to be measured is more complete and specific, a problem of missing of a part of points is solved, and a calculation accuracy of the profile is higher.
Another advantage of the present invention is to provide a method and a system for measuring a profile based on 3D scanning, wherein the measuring method obtains a point cloud model of a 3D three-dimensional surface of a surface to be measured by means of point cloud splicing based on depth information of the surface to be measured of the 3D scanning, and calculates the profile of the surface to be measured according to the three-dimensional point cloud model, which is beneficial to improving measurement accuracy and precision.
In accordance with one aspect of the present invention, the foregoing and other objects and advantages are achieved in the present invention by a 3D scanning-based profile degree measuring method, wherein the measuring method comprises the steps of:
(a) Acquiring 3D point cloud data of a surface to be detected based on depth coordinates;
(b) Reconstructing a three-dimensional model curved surface corresponding to the surface to be measured based on the acquired 3D point cloud data; and
(c) And calculating the profile degree of the surface to be detected according to the three-dimensional model curved surface and the theoretical point cloud model curved surface of the surface to be detected.
According to one embodiment of the present invention, the step (a) of the measuring method includes:
(a.1) scanning the surface to be measured line by line along the set scanning path through a depth information acquisition device to obtain a depth image corresponding to the surface to be measured; and
and (a.2) analyzing the depth image of the surface to be detected, and acquiring 3D coordinate information corresponding to the depth image to obtain 3D point cloud data corresponding to the surface to be detected.
According to one embodiment of the invention, step (a.1) of the measurement method further comprises the steps of:
(a.1) scanning the surface to be measured along a set scanning path to obtain a depth image corresponding to a sub-area of the surface to be measured; and
and (a.2) switching the scanning path of the surface to be measured, and scanning the surface to be measured along the scanning path to acquire a depth image corresponding to another sub-area of the surface to be measured, so that the surface to be measured is completely scanned.
According to one embodiment of the invention, step (a) of the measurement method is preceded by the further steps of:
(a0) Based on the scanning path optimization principle:
obtaining an optimal scan path, where Δ y i Represents the nth scan area along the Y direction of the coordinate axis.
According to an embodiment of the present invention, the step (a 0) of the measuring method further comprises the steps of:
(a 0.1) integrally dividing the surface to be detected into a plurality of small areas; and
(a 0.2) determining small areas of invalid scanning, combining the small areas and deleting the small areas in the whole to determine the optimal scanning path.
According to one embodiment of the invention, step (b) of the measuring method further comprises the steps of:
(b.1) establishing a reference coordinate system corresponding to the 3D point cloud data; and
and (b.2) acquiring a three-dimensional model curved surface by utilizing a surface reconstruction algorithm of grid growth based on the reference coordinate system and the 3D point cloud data.
According to one embodiment of the invention, step (b.2) of the measuring method further comprises:
carrying out local triangular meshing on the point cloud data; and
and searching more point connection grids according to the neighborhood standard of the curved surface, and growing the grids until all possible points are connected so as to complete the reconstruction of the curved surface of the three-dimensional model of the workpiece.
According to one embodiment of the invention, step (a) of the measuring method further comprises:
and (a.3) splicing each 3D point cloud data unit into a complete 3D point cloud data set corresponding to the surface to be detected.
According to one embodiment of the invention, said step (a.3) of said measuring method further comprises the steps of:
(a.3.1) moving other 3D point cloud data units to their theoretical positions based on the position of one piece of 3D point cloud data unit;
(a.3.2) calculating the offset, the height difference and the rotation angle between any two adjacent 3D point cloud data units, and adjusting the relative position between the adjacent 3D point cloud data units based on the offset, the height difference and the rotation angle to obtain a 3D point cloud data set corresponding to the surface to be detected.
According to one embodiment of the invention, said step (a.3.2) of said measuring method further comprises the steps of:
(a.3.2.1) acquiring a superposition area of two adjacent 3D point cloud data units, and recording a subgraph A and a subgraph B; and
(a.3.2.2) calculating the offset, the height difference and the rotation angle of two adjacent 3D point cloud data units based on the subgraph A and the subgraph B.
According to one embodiment of the invention, said step (a.3.2.2) of said measuring method further comprises:
at least 3 Mark points are arranged in each overlapping area; and
and calculating the offset or rigid body transformation matrix of one 3D point cloud data unit based on the corresponding relation of the 3 Mark points in the coordinate system of the two adjacent 3D point cloud data units.
According to an embodiment of the present invention, in the step (c) of the measuring method, a distance from each point of the three-dimensional model surface to a corresponding point of the theoretical model surface is calculated, and 2 times of a maximum value among all the distances is determined as a contour error.
According to an embodiment of the present invention, the step (c) further comprises the steps of:
(c.1) creating a plane model corresponding to the surface to be measured;
(c.2) acquiring a common part of the three-dimensional model curved surface and the planar model at the position corresponding to the surface to be detected, and extracting a contour line at a specified position; and
and (c.3) aligning the extracted contour line with a theoretical contour line, and solving the maximum deviation of the contour line to obtain the line profile degree.
According to another aspect of the present application, the present application further provides a profile-degree measuring system based on 3D scanning, comprising:
the point cloud processing module is used for acquiring 3D point cloud data corresponding to the surface to be detected;
a three-dimensional reconstruction module, wherein the three-dimensional reconstruction module reconstructs a three-dimensional model surface based on the 3D point cloud data; and
and the contour degree calculation module is used for comparing the three-dimensional model curved surface with a theoretical point cloud model curved surface to obtain the contour degree of the surface to be measured.
According to an embodiment of the invention, the system further comprises a depth information acquisition module, wherein the depth information acquisition module scans the curved surface of the workpiece to be detected line by line along a set scanning route to obtain 3D coordinate information under a depth image.
According to one embodiment of the invention, the point cloud processing module comprises an image analysis unit and a point cloud splicing unit, wherein the image analysis unit is used for analyzing the depth image of the surface to be detected to obtain 3D point cloud data corresponding to the surface to be detected, and the point cloud splicing unit is used for splicing the 3D point cloud data units corresponding to each sub-area of the area to be detected into a complete 3D point cloud data set.
According to an embodiment of the present invention, the depth information acquisition device further includes a path planning module, wherein the path planning module is connected to the depth information acquisition device, and the path planning module makes a suitable scanning path for the depth information acquisition device based on the surface to be measured.
Further objects and advantages of the invention will be fully apparent from the ensuing description and drawings.
These and other objects, features and advantages of the present invention will become more fully apparent from the following detailed description and the accompanying drawings.
Drawings
Fig. 1 is a flowchart of a method for measuring a profile based on 3D scanning according to a first preferred embodiment of the present invention.
Fig. 2 is a step diagram of the method for measuring profile based on 3D scanning according to the first preferred embodiment of the present invention.
Fig. 3A and 3B are schematic views illustrating scanning paths of the profile measuring method based on 3D scanning according to the first preferred embodiment of the present invention.
Fig. 4 is a schematic diagram of the 3D scanning-based profile measurement method for joining point cloud data according to the first preferred embodiment of the present invention.
Fig. 5A is a schematic diagram of the overlapping region of two adjacent sub-regions in the process of joining point cloud data according to the 3D scanning-based profile measuring method of the first preferred embodiment of the present invention.
Fig. 5B is a schematic diagram of the method for measuring profile based on 3D scanning according to the first preferred embodiment of the present invention, with respect to the transformation matrix.
Fig. 6 is a schematic diagram of triangularization for reconstructing a three-dimensional curved surface model in the 3D scanning-based profilometry method according to the first preferred embodiment of the present invention.
Fig. 7 is a schematic diagram of the method for measuring profile degree based on 3D scanning according to the first preferred embodiment of the present invention, with respect to the calculation of profile degree.
Fig. 8 is a system block diagram of a 3D scanning-based profile measurement system according to a second preferred embodiment of the present invention.
Detailed Description
The following description is presented to disclose the invention so as to enable any person skilled in the art to practice the invention. The preferred embodiments in the following description are given by way of example only, and other obvious variations will occur to those skilled in the art. The basic principles of the invention, as defined in the following description, may be applied to other embodiments, variations, modifications, equivalents, and other technical solutions without departing from the spirit and scope of the invention.
It will be understood by those skilled in the art that in the present disclosure, the terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are used in an orientation or positional relationship indicated in the drawings for ease of description and simplicity of description, and do not indicate or imply that the referenced devices or components must be in a particular orientation, constructed and operated in a particular orientation, and thus the above terms are not to be construed as limiting the present invention.
It is understood that the terms "a" and "an" should be interpreted as meaning that a number of one element or element is one in one embodiment, while a number of other elements is one in another embodiment, and the terms "a" and "an" should not be interpreted as limiting the number.
Referring to fig. 1 to 8 of the drawings of the present specification, a 3D scanning-based profile tolerance measuring method and measuring system according to a first preferred embodiment of the present invention will be explained in the following description, and hereinafter, referred to as a 3D scanning-based profile tolerance measuring method as a measuring method. The measuring method mainly comprises the following steps: planning an optimal scanning path; recording coordinate information of a curved surface to be measured of the workpiece in a motion and scanning combined mode along the XY coordinate axis direction by using a 3D camera; splicing the sub-regions scanned for multiple times into a complete curved surface, and reconstructing a three-dimensional model; and calculating the surface profile degree by comparing the theoretical profile with the actual profile. It can be understood that the measuring method based on the 3D scanning method has the advantages of high sampling frequency, capability of acquiring a large amount of position information in a short time to carry out three-dimensional reconstruction, high speed and high efficiency, and the measuring system has high scanning precision and can meet the high-precision measuring requirement of production of precision products (workpieces). It should be noted that, in the preferred embodiment of the present application, the measurement method can achieve fast and accurate measurement of the dimensional accuracy of the curved surface of the workpiece.
It is worth mentioning that the measuring method adopts non-contact point taking, uses a 3D camera to scan the curved surface to be measured of the workpiece along the XY coordinate axis direction, avoids the damage of the contact point to the surface of the workpiece, and has fast sampling frequency and high precision. In addition, the measuring method is based on the principles of dynamic planning and an interior point method, an optimal scanning path is planned, the scanning scheme with the shortest total length of the scanning path and the minimum steering times is obtained, and the method achieves the large obtaining amount of effective data in unit time and high efficiency.
As shown in fig. 1 and 2, the method for measuring the profile based on 3D scanning according to the preferred embodiment of the present invention includes the following steps:
(a) Acquiring 3D point cloud data of a surface to be detected based on a depth coordinate;
(b) Reconstructing a three-dimensional model curved surface corresponding to the surface to be measured based on the acquired 3D point cloud data; and
(c) And calculating the profile degree of the surface to be detected according to the three-dimensional model curved surface and the theoretical point cloud model curved surface of the surface to be detected.
In the step (a) of the measuring method according to the above preferred embodiment of the present invention, the depth information collecting device is used to sequentially scan the curved surface to be measured line by line along the set scanning path, so as to obtain the 3D coordinate information under the depth image. The scanning path direction is adjusted by adjusting the relative position of the depth information acquisition device and the surface to be measured, and 3D coordinate information under another sub-area can be obtained by using the method. And repeating the steps until the whole workpiece surface is completely scanned.
In detail, in step (a) of the measurement method, the surface to be measured is scanned line by line along a set scanning path to obtain 3D point cloud data corresponding to the surface to be measured. It is worth mentioning that step (a) of the measurement method of the preferred embodiment of the present application includes:
(a.1) scanning the surface to be measured line by line along the set scanning path through a depth information acquisition device to obtain a depth image corresponding to the surface to be measured; and
and (a.2) analyzing the depth image of the surface to be detected, and acquiring 3D coordinate information corresponding to the depth image to obtain 3D point cloud data corresponding to the surface to be detected.
In particular, step (a.1) of the measurement method further comprises the steps of:
(a.1) scanning the surface to be measured along a set scanning path to obtain a depth image corresponding to a sub-area of the surface to be measured; and
and (a.2) switching the scanning path of the surface to be measured, and scanning the surface to be measured along the scanning path to acquire a depth image corresponding to another sub-area of the surface to be measured, so that the surface to be measured is completely scanned.
It should be noted that, in the preferred embodiment of the present application, the surface to be measured is entirely divided into a plurality of sub-regions, and the sub-regions are scanned line by the depth information acquisition device. Therefore, the depth information acquisition device scans the sub-region of the surface to be detected once to obtain a depth image corresponding to the sub-region, and resolves the depth image of the sub-region into a corresponding 3D point cloud data unit. That is, the 3D point cloud data corresponding to the surface under test in the present application is composed of 3D point cloud data units corresponding to several sub-regions.
It is worth mentioning that in this preferred embodiment of the present application, the depth information collecting device may be, but is not limited to, a structured light shooting device, a 3D camera, or the like.
The method further comprises the following steps before the step (a) of the measuring method of the invention:
(a0) Based on the scanning path optimization principle:
obtaining an optimal scan path, where Δ y i Represents the nth scan area along the Y direction of the coordinate axis.
The step (a 0) of the measuring method of the present invention further comprises the steps of:
(a 0.1) integrally dividing the surface to be measured into a plurality of small areas; and
(a 0.2) determining small areas of invalid scanning, combining the small areas and deleting the small areas in the whole to determine the optimal scanning path.
Those skilled in the art can understand that the measurement method of the preferred embodiment of the present application plans an optimal scanning path based on the principles of dynamic planning and interior point method, obtains a scanning scheme with the shortest total length of the scanning path and the fewest number of turns, and realizes large acquisition amount and high efficiency of effective data in unit time.
As shown in fig. 3A and 3B, the 3D camera scans the surface to be scanned during the movement, and moves the 3D camera along the direction perpendicular to the scanning direction after each scanning to switch the scanning path. For example, the scan area is increased by moving in the y direction, and the number of scans is increased by moving only the switching position in the x direction.
In the step (a) of the measurement method according to the above preferred embodiment of the present invention, the depth coordinate information corresponding to the surface to be measured is obtained by scanning the surface to be measured. For directly selecting discrete points to calculate the profile tolerance, the method has the problems of unbalanced sample set and low calculation result precision, so that point cloud data needs to be subjected to three-dimensional reconstruction. And furthermore, the geometric information of the surface of the workpiece is more complete and concrete, and the problem of partial point deletion is solved, so that the calculation precision of the profile tolerance is higher.
In the measuring method according to the above preferred embodiment of the present invention, the step (b) is to reconstruct a three-dimensional model curved surface based on the acquired 3D point cloud data. Firstly, establishing a reference coordinate system for point cloud, then utilizing a surface reconstruction algorithm based on grid growth, carrying out local triangular meshing on point cloud data by the algorithm, then searching more point connection grids according to a curved surface neighborhood standard, enabling the grids to grow until all possible points are connected, and further completing reconstruction of a three-dimensional curved surface model of a workpiece.
As shown in fig. 6, in the 3D point cloud data obtained in step (a) of the measurement method according to the above preferred embodiment, data points D1, D2, D3, D4, D5, D6 … are included, where any three points in the 3D point cloud data may form a plane, and the plane formed by the three points closest to each other is closest to the structure of the actual plane. Therefore, after local triangulation is performed on the three closest data points D1, D2, and D3 by using a surface reconstruction algorithm for mesh growth, a plane (a mesh) formed by the data points D1, D2, and D3 is obtained, and two meshes connected to each other are formed by the data points D2, D3, and D4 according to the same method based on the proximity principle. Therefore, the two interconnected planes are formed by the D1, the D2, the D3 and the D4, more point connection grids are searched according to the curved surface neighborhood standard, the grids are grown until all possible data points are connected, and all 3D point cloud data are connected to form a three-dimensional model surface close to the surface to be measured.
The step (b) of the measuring method according to the above preferred embodiment of the present invention further comprises the steps of:
(b.1) establishing a reference coordinate system corresponding to the 3D point cloud data; and
and (b.2) acquiring a three-dimensional model curved surface by using a surface reconstruction algorithm of grid growth based on the reference coordinate system and the 3D point cloud data.
The step (b.2) of the measuring method according to the above preferred embodiment of the present invention further comprises:
carrying out local triangular meshing on the point cloud data; and
and searching more point connection grids according to the neighborhood standard of the curved surface, and growing the grids until all possible points are connected so as to complete the reconstruction of the curved surface of the three-dimensional model of the workpiece.
It should be noted that, for some workpieces with large surfaces, such as car doors, car bodies, etc., a depth image corresponding to the entire surface cannot be obtained by one scanning, and a complete depth image and 3D point cloud data corresponding to the surface to be measured can be obtained by multiple scanning and splicing.
Therefore, step (a) of the measuring method in the above preferred embodiment of the present invention further comprises:
and (a.3) splicing all the 3D point cloud data units into a complete 3D point cloud data set corresponding to the surface to be detected.
That is to say, in the step (a.3) of the measurement method according to the above preferred embodiment of the present invention, the plurality of pieces of 3D point cloud data units obtained in the step (a) are spliced into 3D point cloud data corresponding to the whole surface to be measured by feature-based point cloud splicing, so as to reconstruct the three-dimensional model curved surface.
In step (a.3) of the measurement method according to the above preferred embodiment of the present invention, coordinates (x 1, y 1) of the starting point pixel of each sub-region are sorted, the coordinates are translated to the theoretical position of the whole image, and the overlapping region of the adjacent regions is obtained and is marked as sub-image A, B. The subgraph A, B is subjected to translation matching and height difference calculation, and the offset (offset) is calculated x ,offset y ) And a height difference offset z . At least 3 Mark points are added in each overlapping area. And calculating the offset or rigid transformation matrix by using the corresponding relation of the Maker point under different coordinate systems. And converting the depth image coordinate information into point cloud coordinate information based on a coordinate system transformation principle, and finally obtaining the 3D point cloud data of the workpiece based on the obtained offset or rigid body transformation.
In detail, in the preferred embodiment of the present application, any 3D point cloud data unit may be used as a reference data unit, and the position relationship of the other 3D point cloud data units is adjusted to splice the 3D point cloud data units into a complete 3D point cloud data group corresponding to the surface to be measured. As an example, in the preferred embodiment of the present application, the data units with the first piece of point cloud data unit as the reference sequentially adjust the relative positions of the subsequently acquired 3D point cloud data units, and further splice into the 3D point cloud data set corresponding to the surface to be measured.
As shown in fig. 5A, as an example, the starting point pixel coordinate of the first sub-region of the surface to be measured is (x 1, y 1), the starting point pixel coordinate of the second sub-region of the surface to be measured is (x 2, y 2), and the second 3D point cloud data unit is entirely translated to the theoretical position of the image (i.e. the second 3D point cloud data unit is moved according to the moving step of the scanning room). The first piece of 3D point cloud data unit and the second piece of 3D point cloud data unit have an overlapping area after moving, namely the adjacent edge areas of the first piece of 3D point cloud data unit and the second piece of 3D point cloud data unit are overlapped. And setting the overlapping area of the first piece of 3D point cloud data unit as a subgraph A, and the overlapping area of the second piece of 3D point cloud data unit as a subgraph B, wherein the subgraph A and the subgraph B are not necessarily completely overlapped, namely, a height difference, an angle difference or a position offset may exist between the subgraph A and the subgraph B. Therefore, the relative position relationship between the sub-image a and the sub-image B needs to be adjusted, so that after the sub-image a and the sub-image B are completely overlapped, the first piece of 3D point cloud data and the second piece of 3D point cloud data are spliced, that is, each 3D point cloud data unit can be accurately spliced in such a way. The subgraph A, B is subjected to translation matching and height difference calculation, and the offset (offset) is calculated x ,offset y ) And a height difference offset z 。
Accordingly, the step (a.3) of the measuring method in the present application further comprises the steps of:
(a.3.1) moving other 3D point cloud data units to their theoretical positions based on the position of one piece of 3D point cloud data unit;
(a.3.2) calculating the offset, the height difference and the rotation angle between any two adjacent 3D point cloud data units, and adjusting the relative position between the adjacent 3D point cloud data units based on the offset, the height difference and the rotation angle to obtain a 3D point cloud data set corresponding to the surface to be detected.
It is worth mentioning that, in the step (a.3.1) of the measurement method of the present application, each 3D point cloud data unit is moved to a theoretical position based on the coordinate value of the starting point pixel of each sub-region in the region to be measured.
Said step (a.3.2) of said measurement method of the present application further comprises the steps of:
(a.3.2.1) acquiring a superposition area of two adjacent 3D point cloud data units, and recording a subgraph A and a subgraph B; and
(a.3.2.2) calculating the offset, the height difference and the rotation angle of two adjacent 3D point cloud data units based on the subgraph A and the subgraph B.
Further, the step (a.3.2.2) of the measuring method of the present application further comprises:
at least 3 Mark points are arranged in each overlapping area; and
and calculating the offset or rigid body transformation matrix of one 3D point cloud data unit based on the corresponding relation of the 3 Mark points in the coordinate system of the two adjacent 3D point cloud data units.
It should be noted that, in the preferred embodiment of the present application, the 3 Mark points provided in the overlapping area are (M1, M2, M3), where the Mark point under the coordinate system of one of the 3D point cloud data units is (x 1, y1, z 1), and the Mark point under the coordinate system of the other adjacent 3D point cloud data unit is (x 2, y2, z 2), and then the offset, the height difference, and the rotation angle between the two adjacent 3D point cloud data units at this time are calculated based on the above coordinates.
In the step (a.3.2.2) of the measurement method of the present application: and converting the depth image coordinate information into point cloud coordinate information based on a coordinate system transformation principle, and adjusting the position of the 3D point cloud data unit based on calculated offset or rigid body transformation to obtain a 3D point cloud data set corresponding to the surface to be detected.
The step (c) of the measuring method of the application is to calculate the profile degree of the surface to be measured, to calculate the surface profile degree of the surface to be measured, a method of comparing an actual point cloud model curved surface with a theoretical point cloud model curved surface is adopted, the distance from each point of the actual point cloud model to the corresponding point of the theoretical point cloud model is calculated, and 2 times of the maximum value in all the distances is determined as the profile degree error. Optionally, in another optional embodiment of the present application, the profile is a directed distance, that is, the positive minimum value minus the negative minimum value is used as the profile, that is, the deviation values on both sides are respectively the maximum, and the corresponding profile is obtained after adding.
Therefore, in the step (c) of the measurement method of the present application, the distance from each point of the three-dimensional model curved surface to the corresponding point of the theoretical model curved surface is calculated, and 2 times of the maximum value among all the distances is determined as the profile error.
The technical personnel in the field can understand that the measuring method can also be used for measuring the line profile degree of the surface to be measured, and for the condition that the line profile degree needs to be calculated, a plane model can be created firstly, then a common part of a three-dimensional model at the corresponding position of a workpiece and the plane model is obtained, and the contour line of the specified position is further extracted. And (4) performing polynomial fitting after contour line coordinates are extracted, and aligning with a theoretical contour line to obtain the maximum deviation, namely line contour degree.
Therefore, the step (c) of the measurement method of the present application further comprises the steps of:
(c.1) creating a plane model corresponding to the surface to be measured;
(c.2) acquiring a common part of the three-dimensional model curved surface and the planar model at the position corresponding to the surface to be detected, and extracting a contour line of the specified position; and
and (c.3) aligning the extracted contour line with a theoretical contour line, and solving the maximum deviation of the contour line to obtain the line profile degree.
Referring to fig. 8 of the drawings accompanying the present application, a 3D scanning-based profile tolerance measuring system according to a second preferred embodiment of the present invention is illustrated in the following description, hereinafter referred to as measuring system. The measurement system plans an optimal scanning path; recording coordinate information of a curved surface to be measured of the workpiece in a motion and scanning combined mode along the XY coordinate axis direction by using a 3D camera; splicing the sub-regions scanned for multiple times into a complete curved surface, and reconstructing a three-dimensional model; and calculating the surface profile degree by a method of comparing the theoretical profile with the actual profile. It can be understood that the measuring system is fast in sampling frequency based on a 3D scanning method, capable of acquiring a large amount of position information in a short time to carry out three-dimensional reconstruction, fast in speed, high in efficiency, high in scanning precision and capable of meeting the high-precision measuring requirement of production of precision products (workpieces). It is worth mentioning that in the preferred embodiment of the present application, the measurement system can achieve fast and accurate measurement of the accuracy of the dimension of the curved surface of the workpiece.
It is worth mentioning that the measurement system adopts non-contact point taking, and the 3D camera is used for scanning the curved surface to be measured of the workpiece along the XY coordinate axis direction, so that the damage of the contact point taking to the surface of the workpiece is avoided, the sampling frequency is high, and the precision is high. In addition, the measuring system plans the optimal scanning path based on the principles of dynamic planning and an interior point method, obtains the scanning scheme with the shortest total length of the scanning path and the minimum steering times, and realizes large acquisition amount of effective data in unit time and high efficiency.
The measuring system comprises a depth information acquisition device 10, a point cloud processing module 20, a three-dimensional reconstruction module 30 and a profile degree calculation module 40, wherein the depth information acquisition device 10 is used for acquiring depth information of a surface to be measured to obtain depth image information corresponding to the surface to be measured; the point cloud processing module 20 acquires 3D point cloud data corresponding to the surface to be measured based on the depth image acquired by the depth information acquisition device; the three-dimensional reconstruction module reconstructs a three-dimensional surface according to the 3D point cloud data obtained by the point cloud processing module to obtain a three-dimensional model curved surface corresponding to the surface to be measured; and the contour degree calculation module 40 compares the three-dimensional model curved surface with the theoretical point cloud model curved surface to obtain the contour degree information of the surface to be measured.
In detail, the depth information collecting apparatus 10 may be, but is not limited to, a 3D camera or a structured light camera. The depth information acquisition device 10 scans the curved surface of the workpiece to be measured line by line along a set scanning route to obtain 3D coordinate information under the depth image. Then, the 3D camera running direction is transformed, and 3D coordinate information under another sub-area can be obtained by using the method. And repeating the steps until the whole workpiece surface is completely scanned.
The depth information acquisition device 10 sequentially scans the curved surface to be measured line by line along a set scanning path to acquire 3D coordinate information under the depth image. By adjusting the relative position of the depth information acquisition device 10 and the surface to be measured, the scanning path direction is adjusted, and 3D coordinate information under another sub-region can be obtained by using the above method. And repeating the steps until the whole workpiece surface is completely scanned.
The depth information acquisition device 10 scans the surface to be measured line by line along a set scanning path to acquire 3D point cloud data corresponding to the surface to be measured. It should be noted that the depth information collecting device 10 scans the surface to be measured line by line along the set scanning path through the depth information collecting device to obtain a depth image corresponding to the surface to be measured, the depth image information is transmitted to the point cloud processing module 20, and the point cloud processing module 20 resolves the depth image into 3D point cloud data.
The point cloud processing module 20 includes an image analyzing unit 21 and a point cloud splicing unit 22, where the image analyzing unit 21 is configured to analyze a depth image of the surface to be measured, and obtain 3D coordinate information corresponding to the depth image, so as to obtain 3D point cloud data corresponding to the surface to be measured.
In the preferred embodiment of the present invention, the depth information collecting device 10 scans the surface to be measured along a set scanning path to obtain a depth image corresponding to a sub-region of the surface to be measured; when the depth information collecting device 10 switches the scanning path of the surface to be measured, and scans the surface to be measured along the scanning path to obtain a depth image corresponding to another sub-area of the surface to be measured, so as to completely scan the surface to be measured.
Therefore, in the preferred embodiment of the present application, the depth information acquisition device 10 scans line by line along a set scanning path to acquire a plurality of depth image units corresponding to the surface to be measured, and the depth image units are resolved into corresponding 3D point cloud data units by the image resolution unit 21. The point cloud registration unit 22 registers 3D point cloud data units corresponding to sub-regions of the region to be measured into a complete 3D point cloud data set, so that the three-dimensional reconstruction module 30 reconstructs the 3D point cloud data set into a three-dimensional model surface.
The point cloud stitching unit 22 stitches each 3D point cloud data unit into a complete 3D point cloud data set corresponding to the surface to be measured. That is to say, in the measuring system according to the above preferred embodiment of the present invention, the point cloud splicing unit 22 splices the obtained multiple pieces of 3D point cloud data units into 3D point cloud data corresponding to the whole surface to be measured by feature-based point cloud splicing, so as to reconstruct the curved surface of the three-dimensional model.
The point cloud registration unit 22 arranges the starting point pixel coordinates (x 1, y 1) of each sub-region, translates the coordinates to the theoretical position of the whole image, and obtains the overlapping region of the adjacent regions, which is marked as sub-image A, B. The subgraph A, B is subjected to translation matching and height difference calculation, and the offset (offset) is calculated x ,offset y ) And a height difference offset z . At least 3 Mark points are added in each overlapping area. And calculating the offset or rigid transformation matrix by using the corresponding relation of the Maker point under different coordinate systems. And converting the depth image coordinate information into point cloud coordinate information based on a coordinate system transformation principle, and finally obtaining the 3D point cloud data of the workpiece based on the obtained offset or rigid body transformation.
The point cloud splicing unit 22 may use any one of the 3D point cloud data units as a reference data unit, and splice each of the 3D point cloud data units into a complete 3D point cloud data set corresponding to the surface to be measured by adjusting the positional relationship of the remaining 3D point cloud data units. For example, in the preferred embodiment of the present application, the point cloud stitching unit 22 sequentially adjusts the relative positions of the subsequently acquired 3D point cloud data units by using the first piece of point cloud data unit as a reference data unit, and further stitches the 3D point cloud data groups corresponding to the surface to be measured.
Illustratively, the point cloud stitching unit 22 stitches the surface to be measuredThe starting point pixel coordinates of the first sub-area are (x 1, y 1), the starting point pixel coordinates of the second sub-area of the surface to be measured are (x 2, y 2), and the second 3D point cloud data unit is integrally translated to the theoretical position of the image (namely, the second 3D point cloud data unit is moved according to the moving step length of the scanning room). The first piece of 3D point cloud data unit and the second piece of 3D point cloud data unit have an overlapping area after moving, namely the adjacent edge areas of the first piece of 3D point cloud data unit and the second piece of 3D point cloud data unit are overlapped. And setting the overlapping area of the first piece of 3D point cloud data unit as a subgraph A, and the overlapping area of the second piece of 3D point cloud data unit as a subgraph B, wherein the subgraph A and the subgraph B are not necessarily completely overlapped, namely, a height difference, an angle difference or a position offset may exist between the subgraph A and the subgraph B. Therefore, the relative position relationship between the sub-image a and the sub-image B needs to be adjusted, so that after the sub-image a and the sub-image B are completely overlapped, the first piece of 3D point cloud data and the second piece of 3D point cloud data are spliced, that is, each 3D point cloud data unit can be accurately spliced in such a way. The point cloud splicing unit 22 performs translation matching and height difference calculation on the subgraph A, B, and calculates the offset (offset) x ,offset y ) And a height difference offset z 。
The point cloud splicing unit 22 moves other 3D point cloud data units to theoretical positions thereof based on the position of one piece of 3D point cloud data unit, calculates an offset, a height difference and a rotation angle between any two adjacent 3D point cloud data units, and adjusts relative positions between the adjacent 3D point cloud data units based on the offset, the height difference and the rotation angle to acquire a 3D point cloud data set corresponding to the surface to be measured.
It should be noted that the point cloud stitching unit 22 moves each 3D point cloud data unit to a theoretical position based on the coordinate values of the starting point pixels of each sub-region in the region to be detected.
The point cloud splicing unit 22 acquires the overlapping area of two adjacent 3D point cloud data units, records a subgraph A and a subgraph B, and calculates the offset, the height difference and the rotation angle of the two adjacent 3D point cloud data units based on the subgraph A and the subgraph B.
The point cloud splicing unit 22 sets at least 3 Mark points in each overlapping area, and calculates the offset or rigid transformation matrix of one of the 3D point cloud data units based on the corresponding relationship of the 3 Mark points in the coordinate system where the two adjacent 3D point cloud data units are located.
It should be noted that, in the preferred embodiment of the present application, the 3 Mark points provided in the overlapping area are (M1, M2, M3), where the Mark point is marked as (x 1, y1, z 1) in the coordinate system of one of the 3D point cloud data units, and is marked as (x 2, y2, z 2) in the coordinate system of the other adjacent 3D point cloud data unit, and then the offset, the height difference, and the rotation angle between the two adjacent 3D point cloud data units at this time are calculated based on the coordinates.
The point cloud stitching unit 22 converts the depth image coordinate information into point cloud coordinate information based on a coordinate system transformation principle, and adjusts the position of the 3D point cloud data unit based on calculation to obtain an offset or rigid transformation, so as to obtain a 3D point cloud data set corresponding to the surface to be measured.
For directly selecting discrete points to calculate the profile tolerance, the method has the problems of unbalanced sample set and low calculation result precision, so that point cloud data needs to be subjected to three-dimensional reconstruction. Therefore, the geometric information of the workpiece is more complete and concrete, the problem of partial point loss is solved, and the calculation precision of the profile degree is higher.
Therefore, in the preferred embodiment of the present application, the three-dimensional reconstruction module 30 reconstructs a three-dimensional model surface corresponding to an actual surface to be measured based on the 3D point cloud data set processed by the point cloud processing module 20. Specifically, the three-dimensional reconstruction module 30 reconstructs a three-dimensional model curved surface based on the acquired 3D point cloud data. The three-dimensional reconstruction module 30 establishes a reference coordinate system for point clouds, and then uses a surface reconstruction algorithm based on grid growth, the algorithm firstly carries out local triangular gridding on point cloud data, and then searches for more point connection grids according to a curved surface neighborhood standard, so that the grids grow until all possible points are connected, and then the reconstruction of the workpiece three-dimensional curved surface model is completed.
The three-dimensional reconstruction module 30 establishes a reference coordinate system corresponding to the 3D point cloud data, and obtains a three-dimensional model curved surface by using a surface reconstruction algorithm of mesh growth based on the reference coordinate system and the 3D point cloud data.
The three-dimensional reconstruction module 30 performs local triangulation gridding on the point cloud data, and searches for more point connection grids according to the neighborhood standard of the curved surface, so that the grids grow until all possible points are connected, and the reconstruction of the curved surface of the three-dimensional model of the workpiece is completed.
It should be noted that, for some workpieces with large surfaces, such as car doors, car bodies, etc., a depth image corresponding to the entire surface cannot be obtained by one scanning, and a complete depth image and 3D point cloud data corresponding to the surface to be measured can be obtained by multiple scanning and splicing.
And the contour calculation module 40 compares the reconstructed three-dimensional model surface with the theoretical point cloud model surface to obtain the contour degree information of the surface to be measured. In detail, for the calculation of the profile of the workpiece surface, the profile calculation module 40 calculates the distance from each point of the actual point cloud model to the corresponding point of the theoretical point cloud model by comparing the curved surface of the actual point cloud model with the curved surface of the theoretical point cloud model, and determines that 2 times of the maximum value among all the distances is the profile error.
For the case that the line profile degree needs to be calculated, the profile calculating module 40 may first create a planar model, then obtain the three-dimensional model of the corresponding position of the workpiece and the common part of the planar model, and further extract the profile line of the specified position. And (4) performing polynomial fitting after contour line coordinates are extracted, and aligning with a theoretical contour line to obtain the maximum deviation, namely line contour degree.
As shown in fig. 8, the measurement system further includes a path planning module 50, wherein the path planning module 50 is connected to the depth information collecting device 10, and the path planning module 50 formulates a suitable scanning path for the depth information collecting device 10 based on the surface to be measured. That is to say, in this preferred embodiment of this application, the measurement system adopts contactless point taking, uses the 3D camera to scan the curved surface to be measured of the workpiece along the XY coordinate axis direction, avoids the contact point to the damage of workpiece surface, and sampling frequency is fast, and the precision is high. Based on the principles of dynamic planning and interior point method, the optimal scanning path is planned, the scanning scheme with the shortest total length of the scanning path and the minimum steering times is obtained, and the method realizes large acquisition amount and high efficiency of effective data in unit time.
The path planning module 50 is based on the scan path optimization principle:
wherein Δ y i Representing the Nth scanning area along the Y direction of the coordinate axis, dividing the whole body to be detected into a plurality of small areas, determining the small areas of invalid scanning, combining the small areas, deleting the whole body, and finally determining the optimal scanning path.
In the measurement system according to the above preferred embodiment of the present invention, the depth coordinate information corresponding to the surface to be measured is obtained by scanning the surface to be measured. For directly selecting discrete points to calculate the profile tolerance, the method has the problems of unbalanced sample set and low calculation result precision, so that point cloud data needs to be subjected to three-dimensional reconstruction. And furthermore, the geometric information of the surface of the workpiece is more complete and concrete, and the problem of partial point loss is solved, so that the calculation precision of the profile tolerance is higher.
It will be appreciated by persons skilled in the art that the embodiments of the invention described above and shown in the drawings are given by way of example only and are not limiting of the invention. The objects of the invention have been fully and effectively accomplished. The functional and structural principles of the present invention have been shown and described in the examples, and any variations or modifications of the embodiments of the present invention may be made without departing from the principles.
Claims (17)
1. A profile tolerance measuring method based on 3D scanning is characterized in that the measuring method comprises the following steps:
(a) Acquiring 3D point cloud data of a surface to be detected based on a depth coordinate;
(b) Reconstructing a three-dimensional model curved surface corresponding to the surface to be measured based on the acquired 3D point cloud data; and
(c) And calculating the profile degree of the surface to be detected according to the three-dimensional model curved surface and the theoretical point cloud model curved surface of the surface to be detected.
2. The measuring method according to claim 1, wherein the step (a) of the measuring method comprises:
(a.1) scanning the surface to be measured line by line along a set scanning path through a depth information acquisition device to obtain a depth image corresponding to the surface to be measured; and
and (a.2) analyzing the depth image of the surface to be detected, and acquiring 3D coordinate information corresponding to the depth image to obtain 3D point cloud data corresponding to the surface to be detected.
3. The measurement method according to claim 2, wherein step (a.1) of the measurement method further comprises the steps of:
(a.1) scanning the surface to be measured along a set scanning path to obtain a depth image corresponding to a sub-area of the surface to be measured; and
and (a.2) switching a scanning path of the surface to be detected, and scanning the surface to be detected along the scanning path to obtain a depth image corresponding to another sub-area of the surface to be detected until the surface to be detected is completely scanned.
4. The measurement method according to claim 2, wherein step (a) of the measurement method further comprises the steps of:
(a0) Based on the scanning path optimization principle:
obtaining an optimal scan path, where Δ y i Represents the nth scan area along the Y direction of the coordinate axis.
5. The measuring method according to claim 4, wherein the step (a 0) of the measuring method further comprises the steps of:
(a 0.1) integrally dividing the surface to be measured into a plurality of small areas; and
(a 0.2) small areas of invalid scanning are determined, and the small areas are combined and deleted in whole to determine the optimal scanning path.
6. The measuring method according to claim 2, wherein the step (b) of the measuring method further comprises the steps of:
(b.1) establishing a reference coordinate system corresponding to the 3D point cloud data; and
and (b.2) acquiring a three-dimensional model curved surface by utilizing a surface reconstruction algorithm of grid growth based on the reference coordinate system and the 3D point cloud data.
7. The measurement method of claim 6, wherein step (b.2) of the measurement method further comprises:
carrying out local triangular meshing on the point cloud data; and
and searching more point connection grids according to the neighborhood standard of the curved surface, and growing the grids until all possible points are connected so as to complete the reconstruction of the curved surface of the three-dimensional model of the workpiece.
8. The measuring method according to any one of claims 2 to 7, wherein the step (a) of the measuring method further comprises:
and (a.3) splicing each 3D point cloud data unit into a complete 3D point cloud data set corresponding to the surface to be detected.
9. The measurement method according to claim 8, wherein the step (a.3) of the measurement method further comprises the steps of:
(a.3.1) moving other 3D point cloud data units to their theoretical positions based on the position of one piece of 3D point cloud data unit;
(a.3.2) calculating the offset, the height difference and the rotation angle between any two adjacent 3D point cloud data units, and adjusting the relative position between the adjacent 3D point cloud data units based on the offset, the height difference and the rotation angle to obtain a 3D point cloud data set corresponding to the surface to be detected.
10. The measurement method according to claim 9, wherein the step (a.3.2) of the measurement method further comprises the steps of:
(a.3.2.1) acquiring a superposition area of two adjacent 3D point cloud data units, and recording a subgraph A and a subgraph B; and
(a.3.2.2) calculating the offset, the height difference and the rotation angle of two adjacent 3D point cloud data units based on the subgraph A and the subgraph B.
11. The measurement method of claim 10, wherein the step (a.3.2.2) of the measurement method further comprises:
at least 3 Mark points are arranged in each overlapping area; and
and calculating the offset or rigid body transformation matrix of one 3D point cloud data unit based on the corresponding relation of the 3 Mark points in the coordinate system of the two adjacent 3D point cloud data units.
12. The measuring method according to claim 8, wherein in the step (c) of the measuring method, a distance from each point of the three-dimensional model surface to a corresponding point of the theoretical model surface is calculated, and 2 times the maximum value among all the distances is determined as a profilometry error.
13. The measuring method of claim 8, wherein the step (c) further comprises the steps of:
(c.1) creating a plane model corresponding to the surface to be measured;
(c.2) acquiring a common part of the three-dimensional model curved surface and the planar model at the position corresponding to the surface to be detected, and extracting a contour line of the specified position; and
and (c.3) aligning the extracted contour line with the theoretical contour line, and solving the maximum deviation of the contour line to obtain the line profile degree.
14. A profile tolerance measurement system based on 3D scanning is characterized by comprising:
the point cloud processing module is used for acquiring 3D point cloud data corresponding to the surface to be detected;
a three-dimensional reconstruction module, wherein the three-dimensional reconstruction module reconstructs a three-dimensional model surface based on the 3D point cloud data; and
and the contour degree calculation module is used for comparing the three-dimensional model curved surface with a theoretical point cloud model curved surface to obtain the contour degree of the surface to be measured.
15. The measuring system according to claim 14, further comprising a depth information collecting module, wherein the depth information collecting module scans the curved surface of the workpiece to be measured line by line along the set scanning route to obtain 3D coordinate information under the depth image.
16. The measurement system of claim 15, wherein the point cloud processing module comprises an image parsing unit and a point cloud stitching unit, wherein the image parsing unit is configured to parse a depth image of the surface under test to obtain 3D point cloud data corresponding to the surface under test, and the point cloud stitching unit stitches the 3D point cloud data units corresponding to sub-regions of the area under test into a complete 3D point cloud data set.
17. The measurement system according to claim 16, further comprising a path planning module, wherein the path planning module is connected to the depth information acquisition device, and the path planning module is configured to make a suitable scanning path for the depth information acquisition device based on the surface to be measured.
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| CN117272522B (en) * | 2023-11-21 | 2024-02-02 | 上海弥彧网络科技有限责任公司 | Portable aircraft curved surface skin rivet hole profile measurement system and method thereof |
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