Method and system for measuring large complex curved surface part based on combined relay method

Abstract

The invention belongs to the technical field of measurement, and particularly relates to a method and a system for measuring a large complex curved surface part based on a combined relay method. According to the invention, the laser tracker and the three-dimensional scanner are combined, the three-dimensional scanner carries out partition measurement on a large complex curved surface part, and the laser tracker is used for direct measurement and is also used for tracking and positioning the three-dimensional scanner. According to the invention, a coordinate transformation matrix between the three-dimensional scanner and the laser tracker is established through common point optimization, and error correction of data measured by the three-dimensional scanner is realized. The laser tracker is used for precisely positioning each station transfer process of the three-dimensional scanner, and then the benchmark of point cloud data obtained through measurement of different partitions is unified. And finally, directly measuring a special area in the to-be-measured large complex curved surface part through the laser tracker so as to complete all measurement tasks. The problem that in the prior art, accurate and efficient measurement of large complex curved surface parts is difficult to achieve is solved.

Description

Technical Field

[0001] The invention belongs to the field of measurement technology, and specifically relates to a measurement method for large complex curved surface parts based on a combined relay method, as well as a data processing module for implementing the measurement method and a measurement system for large complex curved surface parts. Background Art

[0002] There is a wide demand for high-precision large curved surface structural parts in the fields of aviation, aerospace, communications, etc. For example, the wings, fuselages, radars and other parts of large aircraft have very high requirements for the complex surface accuracy of structural parts. If the product accuracy cannot meet the requirements, it may directly affect the performance and safety of the aircraft. In order to ensure the accuracy of large and complex curved surface parts, technicians need to perform multi-point surface measurement on the processed parts.

[0003] There are many ways to measure the surface accuracy of structural parts. Traditional measurement technologies mainly include contact measurement and optical measurement. Contact measurement is to move the measuring element along the surface of the object to be measured, and then measure the fine contour of the object to be measured in combination with the moving trajectory. Optical measurement is to continuously scan a series of points on the surface of the object to be measured, and then obtain point cloud data that represents the contour of the object to be measured. The above two traditional measurement technologies are capable of performing surface measurement tasks for most small curved surface structural parts, but both often face many limitations when dealing with large surfaces. For example, contact measurement may not be able to achieve full coverage due to the irregularity of the surface, resulting in incomplete data collection; while optical measurement may affect accuracy due to the reflective characteristics of the surface or the limitation of the measurement distance.

[0004] A 3D scanner is a typical optical measuring instrument used to obtain point cloud data of the appearance of the object being measured. This device can usually only perform rapid measurements on small curved parts. If you need to measure the surface of a large complex curved part, you need to transfer the 3D scanner, and then scan the large complex curved part in different locations, and finally integrate the measurement results of different partitions. Although this measurement strategy can achieve full-scale scanning of large curved structural parts to a certain extent, the frequent transfer of the measurement process will not only reduce the measurement efficiency, but also cause the measurement data generated by the 3D scanner to accumulate a large number of errors, which will greatly reduce the accuracy of the final measurement results.

[0005] With the continuous development of industrial technology, the industry's demand for accurate measurement of large curved surfaces is growing, and the accuracy requirements for large and complex curved surface parts are also increasing. Traditional measurement methods can no longer meet the needs of high precision and high efficiency. How to develop a solution that can adapt to the characteristics of large and complex curved surface parts and achieve high-precision and high-efficiency measurement of curved surface structural parts is becoming a technical problem that technicians in this field need to solve urgently. Summary of the invention

[0006] In order to solve the problem that the prior art lacks a solution for accurately and efficiently measuring large complex curved surface parts, the present invention provides a measurement method for large complex curved surface parts based on a combined relay method, as well as a data processing module for implementing the measurement method and a measurement system for large complex curved surface parts.

[0007] The technical solution provided by the present invention is as follows:

[0008] A measurement method for large complex curved surface parts based on a combined relay method utilizes a three-dimensional scanner and a laser tracker and adopts a combined relay method to collect overall point cloud data of the complex large curved surface parts.

[0009] The measurement method comprises the following steps:

[0010] S1: Fix the spatial position of the laser tracker and the large complex curved surface part to be measured, and install a mobile multi-degree-of-freedom robotic arm between the two; then install the 3D scanner at the end of the mobile multi-degree-of-freedom robotic arm, and arrange several spherical reflectors on the base of the 3D scanner. The laser tracker measures the relative position of the 3D scanner by tracking the spherical reflectors on the base of the mobile multi-degree-of-freedom robotic arm.

[0011] S2: Use a laser tracker to measure the spatial position of the spherical reflector arranged on the 3D scanner, and record it as the initial position of the 3D scanner.

[0012] S3: Arrange multiple spherical reflectors on the large complex curved surface parts to be measured and use them as common reference points; use a laser tracker and a 3D scanner to simultaneously measure the position information of the common reference points. The 3D scanner installed on the mobile multi-DOF robotic arm avoids the optical path of the laser tracker to detect the common reference points.

[0013] S4: Calculate the coordinate transformation matrix H between the 3D scanner and the laser tracker based on the position information of the common reference point measured by the 3D scanner and the laser tracker using the common point optimization method. The coordinate transformation matrix H is used to calculate the correction value of the scanning detection result of the 3D scanner based on the measurement result of the laser tracker.

[0014] S5: Use a mobile multi-DOF robotic arm to move the 3D scanner to perform partition scanning on large and complex curved parts to be tested; and use a laser tracker to measure the new position of the 3D scanner after each movement;

[0015] S6: Record the point cloud data of each partition collected by the 3D scanner, and calculate the point cloud data of each partition and the corresponding reference offset ΔL according to the initial position and new position of the 3D scanner measured by the laser tracker; combined with the coordinate transformation matrix H:

[0016]

[0017] Among them, (x ik ,y ik ,z ik ) represents the coordinates of the common point measured by the 3D scanner before the kth transfer; (x jk ,y jk ,z jk ) represents the coordinates of the common point measured by the three-dimensional scanner after the k-th station transfer; Indicates the base coordinates of the 3D scanner.

[0018] S7: Combine the coordinate transformation matrix H of the 3D scanner and laser tracker, the point cloud data of each partition, and the corresponding reference offset ΔL to generate the overall point cloud data of the large complex curved surface part to be measured. The process is as follows:

[0019] S71: Adjust the coordinate values ​​of the point cloud data of each partition in combination with the reference offset ΔL to ensure that the coordinates of all data points refer to the same reference.

[0020] S72: Merge the point cloud data in each partition after the unified benchmark into a complete point cloud data, and ensure that the point cloud data of each partition is correctly aligned to avoid overlap or misalignment.

[0021] S73: Using the coordinate transformation matrix H, the point cloud data merged in the previous step is transformed from the local coordinate system of the 3D scanner to the global coordinate system of the laser tracker to obtain the overall point cloud data.

[0022] S8: Place spherical reflectors in special areas of large and complex curved parts that cannot be scanned by 3D scanners, and use the laser tracker to directly measure and add the measurement results to the overall point cloud data. The 3D scanner installed on the mobile multi-DOF robotic arm avoids the detection optical path of the laser tracker.

[0023] As a further improvement of the present invention, in step S3, the number of common reference points is not less than 3.

[0024] As a further improvement of the present invention, in step S4, the format of the coordinate transformation matrix H is as follows:

[0025]

[0026] In the above formula, R 3×3 (αβγ) represents the rotation matrix of the coordinate system; α, β, γ are the rotation angles of a point in space on the x, y, and z axes; T 3×1 (T x T y T z) represents the translation vector of each point, Tx, T y and Tz are the translations of a point in space relative to the origin on the x, y, and z axes, respectively.

[0027] As a further improvement of the present invention, the rotation matrix R 3×3 (αβγ) satisfies the following formula:

[0028]

[0029] As a further improvement of the present invention, the correction value Satisfies the following expression:

[0030]

[0031] In the above formula, Represents the Cartesian coordinates of the common reference point measured by the 3D scanner; Represents the conversion coordinate system between the laser tracker coordinates and the Cartesian coordinates measured by the 3D scanner; Indicates the coordinates of the common reference point measured by the 3D scanner in the laser tracker; Indicates the offset of the common reference point measured by the 3D scanner relative to the origin of the 3D scanner.

[0032] As a further improvement of the present invention, in step S7, the homogeneous coordinates Q of any observation point obtained by the laser tracker gi The laser tracker measures the coordinate system O G -X G Y G Z G Indicated as P gi :

[0033]

[0034] Any observation point Q obtained by the 3D scanner si In the 3D scanner coordinate system O S -X S Y S Z S The homogeneous coordinates in are denoted as P si :

[0035]

[0036] The coordinate transformation formula of the same observation point obtained by the laser tracker and the 3D scanner in different coordinate systems is as follows:

[0037] P gi = G H S P si

[0038] In the above formula, G H S Represents the transformation matrix of the laser tracker and 3D scanner.

[0039] As a further improvement of the present invention, in step S7, the homogeneous coordinates Q of the spherical reflector are ci In the laser tracker's coordinate system O G -X G Y G Z G Indicated as P ci :

[0040]

[0041] Then in the coordinate system O of the laser tracker G -X G Y G Z G In the figure, the coordinates of the spherical reflector are ci It can be calculated by the following formula:

[0042] P ci = G H I Q ci

[0043] In the above formula, G H I Represents the transformation matrix between the measurements of the 3D scanner and the measurements of the laser tracker.

[0044] As a further improvement of the present invention, in step S7, a transformation matrix is ​​used to transform the measurement value of the three-dimensional scanner into the coordinate system of the laser tracker. I H S The expression is as follows:

[0045]

[0046] In the above formula, yes G H I The inverse matrix of .

[0047] The present invention also includes a data processing module, which includes a memory, a processor, and a computer program stored in the memory. When the processor executes the computer program, the steps in the aforementioned method for measuring large complex curved surface parts based on the combined relay method are adopted to realize coordinate conversion of point cloud data measured by the laser tracker and the three-dimensional scanner in their respective coordinate systems.

[0048] The present invention also includes a measurement system for large complex curved surface parts, which includes: a laser tracker, a mobile multi-degree-of-freedom mechanical arm, a three-dimensional scanner, a plurality of spherical reflectors, and a host computer.

[0049] The laser tracker is mounted on the base. The fixing mechanism is used to fix the large complex curved surface parts to be measured. The mobile multi-degree-of-freedom mechanical arm is fixedly installed between the laser tracker and the fixing mechanism and is located on the side close to the fixing mechanism. The 3D scanner is installed at the end of the multi-degree-of-freedom mechanical arm.

[0050] Part of the spherical reflectors are installed on the base of the 3D scanner to assist the laser tracker in measuring the relative position of the 3D scanner. Another part of the spherical reflectors are placed on the large complex curved surface parts to be measured to directly measure some areas of the large complex curved surface parts to be measured.

[0051] The host computer is electrically connected to the laser tracker, the mobile multi-degree-of-freedom robotic arm, and the three-dimensional scanner. The host computer is used to control and record the operating status of the laser tracker, the mobile multi-degree-of-freedom robotic arm, and the three-dimensional scanner, and collect the measurement data of the laser tracker and the three-dimensional scanner. Then, the steps in the aforementioned measurement method of large complex curved surface parts based on the combined relay method are implemented to obtain the overall point cloud data of the large complex curved surface parts to be measured.

[0052] The technical solution provided by the present invention has the following beneficial effects:

[0053] The present invention provides a method and system for measuring large complex curved surface parts based on a combined relay method. The technical solution combines the respective advantages of a laser tracker and a three-dimensional scanner, uses a laser tracker to perform error correction and position tracking on a three-dimensional scanner, and uses direct measurement to supplement the point cloud data of a local area. This overcomes the problems of low efficiency and poor accuracy in traditional solutions that use three-dimensional scanners for transfer measurement.

[0054] The solution of the present invention integrates multiple measurement technologies such as laser scanning and structured light scanning to achieve comprehensive and high-precision measurement of large and complex curved parts. The design of the system takes into account various challenges that may arise during the measurement process, such as ambient light interference, the complexity of curved parts, and the instability of the measuring equipment. Through advanced algorithms and data processing technology, the accuracy and reliability of the measurement results are ensured.

[0055] In addition, the measurement system for large complex curved surface parts provided by the present invention manages each component through the host computer and automatically realizes the spatial coordinate conversion of data from different sources. Therefore, it has a high degree of automation and intelligence, can reduce manual intervention, and thus greatly improve measurement efficiency, while reducing the difficulty of operation. Since the system provided by the present invention can ensure the consistency and accuracy of the measurement results, the measurement error is further reduced.

[0056] The measurement method and system for large complex curved surface parts based on the combined relay method provided by the present invention can not only meet the high standard requirements for the measurement of large complex curved surface parts in the current industrial field, but also provide new possibilities for the development and application of future measurement technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a spatial layout diagram of the laser tracker and three-dimensional scanner in the measurement method provided in Example 1 of the present invention.

[0058] Figure 2 This is a flow chart of the steps of the method for measuring large complex curved surface parts based on the combined relay method provided in Example 1 of the present invention.

[0059] Figure 3 This is a system schematic diagram of the measurement system for large complex curved surface parts provided in Example 3 of the present invention.

[0060] The markings in the figure are:

[0061] 1. Laser tracker; 2. Fixing mechanism; 3. Mobile multi-degree-of-freedom robotic arm; 4. 3D scanner; 5. Spherical reflector. 6. Host computer. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0063] Example 1

[0064] After analysis, the technicians of this embodiment believe that the main reasons for the large errors in the point cloud data of large surfaces obtained by the existing scheme using a 3D scanner include the following three points: First, the accuracy of the data collected by the 3D scanner itself is relatively low. Second, the single scanning range of the 3D scanner is limited, and the spatial position of the 3D scanner is difficult to accurately locate during the frequent station transfer process, resulting in the accumulation of a large number of errors in the point cloud data of different areas due to changes in the reference. Third, the 3D scanner has a poor measurement effect on the concave or special-shaped structures of some special parts. Therefore, in order to overcome the above-mentioned defects of the 3D scanner in the measurement of large and complex curved surface parts, this embodiment provides a measurement method for large and complex curved surface parts based on the combined relay method, which is used to combine the 3D scanner and the laser tracker to realize the collection of the overall point cloud data of large and complex curved surface parts.

[0065] Specifically, the overall idea of ​​the solution provided by this embodiment is to combine a laser tracker and a three-dimensional scanner. The laser tracker is used to directly measure partial areas of the surface structure to be measured, and is also used to track and locate the three-dimensional scanner. In this new measurement system, the role of the laser tracker also includes the following three points. First, the coordinate transformation matrix between the three-dimensional scanner and the laser tracker is established through common point optimization, and the detection data error of the three-dimensional scanner is corrected. Second, it is used to accurately locate each station transfer process of the three-dimensional scanner, and then unify the benchmark of the point cloud data obtained by measuring different partitions. Third, the local area of ​​the surface to be measured that is not suitable for a three-dimensional scanner is directly measured to obtain more accurate point cloud data.

[0066] In detail, Figure 1 As shown, the measurement method of large complex curved surface parts based on the combined relay method provided in this embodiment includes the following steps:

[0067] S1: This embodiment first needs to build a large complex curved surface part measurement system including a laser tracker and a 3D scanner, and install the large complex curved surface part to be measured. Figure 2 As shown, in the scheme of the embodiment, the laser tracker and the large complex curved surface part to be measured need to be fixedly installed so that the positions of the two remain fixed in space. This embodiment also installs a mobile multi-degree-of-freedom robotic arm between the laser tracker and the large complex curved surface part to be measured; and installs the three-dimensional scanner at the end of the mobile multi-degree-of-freedom robotic arm. In this embodiment, considering that the mobile multi-degree-of-freedom robotic arm needs to drive the three-dimensional scanner to move relative to the laser tracker, and then realize the partition measurement of the large complex curved surface part to be measured, the mobile multi-degree-of-freedom robotic arm should be located close to the large complex curved surface part to be measured. Finally, a number of spherical reflectors are arranged on the base of the three-dimensional scanner. Figure 2In the measurement system, the laser tracker measures the spatial position of the 3D scanner relative to itself by tracking the spherical reflector on the base.

[0068] S2: Use a laser tracker to measure the spatial position of the spherical reflector arranged on the 3D scanner, and record it as the initial position of the 3D scanner.

[0069] In this embodiment, a part of the spherical reflector of the laser tracker is fixedly mounted on the base of the 3D scanner, and the laser tracker realizes the position tracking of the 3D scanner through the spherical reflector on the base. In addition, if it is necessary to directly measure the surface to be measured, the spherical reflector can be directly placed on the surface of the large complex curved surface part to be measured.

[0070] Since a laser tracker is needed to track the position changes of the 3D scanner during the measurement process, the laser tracker needs to measure and record the position of the 3D scanner before and after each station transfer.

[0071] S3: Arrange multiple spherical reflectors on the large complex curved surface parts to be measured and use them as common reference points. Use a laser tracker and a 3D scanner to simultaneously measure the position information of the common reference points.

[0072] Among them, the three-dimensional scanner installed on the mobile multi-degree-of-freedom robotic arm avoids the optical path of the laser tracker to detect the common reference point.

[0073] In the measurement system constructed in this embodiment, the scanning area of ​​the 3D scanner is limited and the measurement accuracy is relatively low, but it can achieve multi-point scanning on the surface. Although the laser tracker has very high measurement accuracy, it can only measure the spatial position of a small number of points in a large complex curved surface part by tracking the spherical reflector. It is not suitable for topographic scanning of large complex curved surface parts and it is difficult to obtain large-scale point cloud data.

[0074] On this basis, this embodiment uses a three-dimensional scanner and a laser tracker to measure a set of common reference points, and then establishes a coordinate system transformation relationship between the three-dimensional scanner and the laser tracker based on the measurement results of the two, and corrects the errors of the measurement results of the three-dimensional scanner through the corresponding coordinate transformation matrix.

[0075] In practical applications, this embodiment arranges no less than three spherical reflectors on the large complex curved surface part to be measured, and uses the position corresponding to each spherical reflector as a common reference point. In the scheme of this embodiment, the three spherical reflectors should be placed at intervals on the surface of the large complex curved surface part to be measured, so as to form a plane. Next, this embodiment uses a laser tracker and a three-dimensional scanner to simultaneously measure the position information of the common reference point; and obtains the spatial coordinates of each common reference point in the respective measurement coordinate systems of the laser tracker and the three-dimensional scanner.

[0076] S4: Calculate the coordinate transformation matrix H between the three-dimensional scanner and the laser tracker based on the position information of the common reference point measured by the three-dimensional scanner and the laser tracker using the common point optimization method. The coordinate transformation matrix H includes the correction value of the scanning result of the three-dimensional scanner calculated based on the measurement result of the laser tracker.

[0077] In this embodiment, the process of determining the coordinate transformation matrix H between the 3D scanner and the laser tracker based on the common point optimization method is as follows:

[0078] Assume that the number of selected common reference points is n, and each common reference point is denoted by D i , i = 1 ... n, through the measurement of step S3, the homogeneous coordinates P of each common reference point under the three-dimensional scanner can be obtained i1 :

[0079] P i1 =(x pi1 ,y pi1 ,z pi1 ,1)

[0080] And the homogeneous coordinates P of each common reference point under the laser tracker i2 :

[0081] P i2 =(x pi2 ,y pi2 ,z pi2 ,1)

[0082] Since the positions measured by the two instruments are public points, the two homogeneous coordinates can be converted to each other through the following coordinate transformation matrix H:

[0083] P i1 =HP i2 ,i=1,2,…,n

[0084] Among them, the coordinate transformation matrix H is a homogeneous transformation matrix, and the format of the matrix is:

[0085]

[0086] In the above formula, R 3×3 (αβγ) represents the rotation matrix of the coordinate system; α, β, γ are the rotation angles of a point in space on the x, y, and z axes; T 3×1 (T x T y T z ) represents the translation vector of each point, Tx, T y and Tz are the translations of the point in space relative to the origin on the x, y, and z axes, respectively. 3×3 (αβγ) satisfies the following formula:

[0087]

[0088] Based on the coordinate conversion matrix H, this embodiment can convert the point cloud data measured by the 3D scanner into the coordinate system corresponding to the laser tracker. The coordinate conversion matrix H is an intermediate coordinate system. On this basis, the strategy for implementing error correction in this embodiment is as follows:

[0089] This embodiment optimizes the rotation matrix and translation vector in the coordinate transformation matrix by the common point optimization method to achieve the minimum error. The specific operation is to measure multiple common reference points at M positions. If the coordinate system of the first position is used as the reference coordinate system, the Cartesian coordinates of the common point obtained by the laser tracker and the 3D scanner at the first position can be expressed as and

[0090]

[0091] For easy distinction, the superscript G0 in the coordinates of each point represents the first position (position 0) of the laser tracker coordinate system (G), and the subscript gi represents the i-th point of the laser tracker coordinate system (g). G and g are both marks of the laser tracker coordinate system. Similarly, the superscript S0 represents the first position (position 0) of the 3D scanner coordinate system (S), and the subscript si represents the i-th point of the 3D scanner coordinate system (s). S and s are both marks of the 3D scanner coordinate system.

[0092] On this basis, common points measured at other locations and The Cartesian coordinates of can be expressed as:

[0093]

[0094] Wherein, m represents the serial number of each common point.

[0095] After introducing measurement errors in the two coordinates, the transformation method of the coordinate transformation matrix can be rewritten as:

[0096]

[0097] In the above formula, It indicates the common reference point measured by the laser tracker in Cartesian coordinates; Represents the conversion coordinate system between the laser tracker coordinates and the standard coordinates of the external environment; Represents the Cartesian coordinates of the common reference point measured by the laser tracker; It indicates the offset between the common reference point measured by the laser tracker and the origin of the laser tracker; Represents the Cartesian coordinates of the common reference point measured by the 3D scanner; Represents the Cartesian coordinates of the common reference point measured by the 3D scanner; A coordinate system representing the transformation between the laser tracker coordinates and the Cartesian coordinates measured by the 3D scanner; Indicates the coordinates of the common reference point measured by the 3D scanner in the laser tracker; Indicates the offset of the common reference point measured by the 3D scanner relative to the origin of the 3D scanner.

[0098] in, and They are the correction values ​​of the spatial coordinates of the common reference points measured in the laser tracker and the 3D scanner respectively:

[0099]

[0100] Considering that the present embodiment mainly uses the measurement result of the laser tracker as the standard to calibrate the measurement result of the three-dimensional scanner, the correction value of the measurement result of the laser tracker is set to 0 in the present embodiment, that is, The calibration value of the 3D scanner Satisfies the following expression:

[0101]

[0102] S5: The 3D scanner is moved by a multi-degree-of-freedom robotic arm to perform partition scanning on large and complex curved parts to be tested; and the new position of the 3D scanner after each movement is measured by a laser tracker.

[0103] In the scheme of this embodiment, when measuring large complex curved surface parts of different structures and sizes, the technician should make a measurement plan in advance before measuring. In the measurement plan, the technician divides the entire surface of the large curved surface structure to be measured into multiple partitions according to the maximum scanning range of the 3D scanner, and then determines the device posture of the 3D scanner when scanning each partition, and issues spatial movement instructions to the mobile multi-degree-of-freedom robotic arm. The point cloud data obtained by the 3D scanner after scanning in different partitions should completely cover the surface of the entire large complex curved surface part.

[0104] During the process of the mobile multi-degree-of-freedom robotic arm moving the three-dimensional scanner to perform partition scanning each time, the laser tracker in this embodiment can use the spherical reflector installed on the base to dynamically track the three-dimensional scanner, and then record the spatial position of the three-dimensional scanner after each movement.

[0105] S6: Record the point cloud data of each partition collected by the 3D scanner, and calculate the point cloud data of each partition and the corresponding reference offset ΔL according to the initial position and new position of the 3D scanner measured by the laser tracker; combined with the coordinate transformation matrix H:

[0106]

[0107] Among them, (x ik ,y ik ,z ik ) represents the coordinates of the common point measured by the 3D scanner before the kth transfer; (x jk ,y jk ,z jk ) represents the coordinates of the common point measured by the three-dimensional scanner after the k-th station transfer; Indicates the base coordinates of the 3D scanner.

[0108] In this embodiment, the point cloud data of different partitions obtained by the three-dimensional scanner are measured after the station is moved, so the benchmark of the point cloud data of each partition is inconsistent. The benchmark offset ΔL corresponding to the point cloud data of each partition reflects the difference of each coordinate value in the point cloud data relative to the common benchmark.

[0109] S7: Combine the coordinate transformation matrix H of the 3D scanner and the laser tracker, the point cloud data of each partition, and the corresponding reference offset ΔL to generate the overall point cloud data of the large complex curved surface part to be measured.

[0110] In the solution of this embodiment, the laser tracker is fixed relative to the base, while the 3D scanner is constantly moving. Therefore, this embodiment uses the measurement coordinate system of the laser tracker as the world coordinate system, and then converts the various point cloud data measured by the 3D scanner into the measurement coordinate system of the laser tracker after unifying the reference, and integrates them into complete point cloud data to eliminate duplicate point clouds.

[0111] Specifically, the process of generating the overall point cloud data of a large complex curved surface part in this embodiment is as follows:

[0112] S71: Adjust the coordinate values ​​of the point cloud data of each partition in combination with the reference offset ΔL to ensure that the coordinates of all data points refer to the same reference.

[0113] S72: Merge the point cloud data in each partition after the unified benchmark into a complete point cloud data, and ensure that the point cloud data of each partition is correctly aligned to avoid overlap or misalignment.

[0114] S73: Using the coordinate transformation matrix H, the point cloud data merged in the previous step is transformed from the local coordinate system of the 3D scanner to the global coordinate system of the laser tracker to obtain the overall point cloud data.

[0115] The above process of generating the overall point cloud data of large complex surface parts is essentially the process of coordinate conversion of point cloud data from different sources. The corresponding data processing process can be summarized as follows:

[0116] (1) The homogeneous coordinates Q of any observation point obtained by the laser tracker gi The laser tracker measures the coordinate system O G -X G Y G Z G It can be expressed as P gi :

[0117]

[0118] Any observation point Q obtained by the 3D scanner si In the 3D scanner coordinate system O S -X S Y S Z S The homogeneous coordinates in can be expressed as P si :

[0119]

[0120] The coordinate transformation formula of the same observation point obtained by the laser tracker and the 3D scanner in different coordinate systems is as follows:

[0121] P gi = G H S P si

[0122] In the above formula, G H S Represents the transformation matrix of the laser tracker and 3D scanner.

[0123] (2) The position change of the three-dimensional scanner during the partition scanning can be confirmed based on the movement of the spherical reflector mounted on its base. Specifically, the homogeneous coordinates Q of the spherical reflector are ci In the laser tracker's coordinate system O G -X G Y G Z GIt can be expressed as P ci :

[0124]

[0125] Then in the coordinate system O of the laser tracker G -X G Y G Z G In the figure, the coordinates of the spherical reflector are ci It can be calculated by the following formula:

[0126] P ci = G H I Q ci

[0127] In the above formula, G H I Represents the transformation matrix between the measurements of the 3D scanner and the measurements of the laser tracker.

[0128] Based on the above two points, it can be determined that the transformation matrix used to convert the measurement value of the 3D scanner to the coordinate system of the laser tracker is I H S The expression is as follows:

[0129]

[0130] In the above formula, yes G H I The inverse matrix of .

[0131] Based on the determined transformation matrix IH S In this embodiment, the point cloud data of different partitions measured by the 3D scanner can be converted into the world coordinate system in sequence, and the duplicate point clouds can be deleted. It should be particularly emphasized that the reference offset and error correction are simultaneously realized in the coordinate conversion process of this embodiment, so the final point cloud data obtained has higher accuracy.

[0132] S8: Place a spherical reflector in a special area of ​​the large complex curved surface part to be measured that cannot be scanned by the 3D scanner, and use the laser tracker to directly measure it, and add the measurement results to the overall point cloud data in the previous step. The 3D scanner installed on the mobile multi-degree-of-freedom robotic arm avoids the detection optical path of the laser tracker.

[0133] Combined with the above content, it can be seen that although the laser tracker is not suitable for large-scale curved surface scanning, it is very accurate in measuring the spatial position of a single target point. Therefore, the solution of this embodiment uses this feature and uses a laser tracker instead of a 3D scanner to directly measure part of the large complex curved surface parts to be measured, so as to overcome the defect that the 3D scanner cannot measure certain depressions or special structures on the surface of large complex curved surface parts; and realize the local supplementation of the incomplete point cloud data obtained by the 3D scanner.

[0134] Example 2

[0135] On the basis of the scheme in Example 1, this embodiment provides a data processing module, which includes a memory, a processor, and a computer program stored in the memory. When the processor executes the computer program, the steps in the measurement method of large complex curved surface parts based on the combined relay method in Example 1 are adopted to realize coordinate conversion of point cloud data measured by the laser tracker and the three-dimensional scanner in their respective coordinate systems.

[0136] The data processing module provided in this embodiment is essentially a computer device, which can be in various forms, such as an embedded chip or module, or a general-purpose data processing device, such as an intelligent terminal capable of executing a program, a tablet computer, a notebook computer, a desktop computer, a rack server, a blade server, a tower server or a cabinet server (including an independent server or a server cluster composed of multiple servers).

[0137] The computer device of this embodiment includes at least but is not limited to: a memory and a processor that can be connected to each other through a system bus. The memory (i.e., a readable storage medium) includes a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., an SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory may be an internal storage unit of a computer device, such as a hard disk or a memory of the computer device.

[0138] In other embodiments, the memory may also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the computer device. Of course, the memory may also include both the internal storage unit of the computer device and its external storage device. In this embodiment, the memory is generally used to store the operating system and various application software installed on the computer device. In addition, the memory may also be used to temporarily store various data that have been output or are to be output.

[0139] The processor may be a central processing unit (CPU), a graphics processing unit (GPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor is generally used to control the overall operation of a computer device. In this embodiment, the processor is used to run program codes stored in a memory or process data.

[0140] Example 3

[0141] Based on embodiments 1 and 2, this embodiment further provides a measurement system for large complex curved surface parts, such as Figure 3 As shown, the measurement system includes: a laser tracker 1, a mobile multi-degree-of-freedom mechanical arm 3, a three-dimensional scanner 4, a plurality of spherical reflectors 5, and a host computer 6.

[0142] In the measurement system of large complex curved surface parts provided in this embodiment, the laser tracker 1 is installed on the base. The fixing mechanism 2 is used to fix the large complex curved surface parts to be measured. The mobile multi-degree-of-freedom mechanical arm 3 is fixedly installed between the laser tracker 1 and the fixing mechanism 2 and is located on a side close to the fixing mechanism 2. The three-dimensional scanner 4 is installed at the end of the multi-degree-of-freedom mechanical arm.

[0143] Part of the spherical reflector 5 is mounted on the base of the three-dimensional scanner 4. Another part of the spherical reflector 5 is used to be placed on the large complex curved surface part to be measured, so as to directly measure a part of the area of ​​the large complex curved surface part to be measured. The laser tracker 1 of this embodiment is used in conjunction with the spherical reflector 5 to track the position of the three-dimensional scanner 4 installed at the end of the mobile multi-degree-of-freedom mechanical arm 3 and accurately measure the spatial coordinates of the three-dimensional scanner 4.

[0144] The three-dimensional scanner 4 can perform non-contact scanning on the target, measure and analyze the shape, geometric structure and appearance data of the target; the collected data is saved in the form of point cloud data, which can be used for three-dimensional reconstruction calculations, or to create a digital model of an actual object in the virtual world. In this embodiment, after the three-dimensional scanner 4 is installed at the end of the mobile multi-freedom robot arm 3, the mobile multi-freedom robot arm can move the spatial position of the three-dimensional scanner 4 according to instructions, thereby realizing partition scanning of large complex curved surface parts.

[0145] In the measurement system of large complex curved surface parts provided in this embodiment, the host computer 6 is electrically connected to the laser tracker 1, the mobile multi-degree-of-freedom mechanical arm 3 and the three-dimensional scanner 4. The host computer 6 includes two main parts: a control unit and a data processing unit, wherein the control unit is used to control the operating state of the laser tracker 1, the mobile multi-degree-of-freedom mechanical arm 3 and the three-dimensional scanner 4. The data processing unit is used to obtain the measurement data of the laser tracker 1 and the three-dimensional scanner 4, and adopt the steps in the measurement method of large complex curved surface parts based on the combined relay method in Example 1 to process the obtained data, thereby obtaining the overall point cloud data of the large complex curved surface parts to be measured.

[0146] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for measuring large complex curved surface parts based on a combined relay method, characterized in that: It uses a three-dimensional scanner and a laser tracker and adopts a combined relay method to collect the overall point cloud data of complex large-scale curved surface parts; the measurement method includes the following steps: S1: Fix the spatial positions of the laser tracker and the large complex curved surface part to be measured, and install a mobile multi-degree-of-freedom robotic arm between the two; then install a three-dimensional scanner at the end of the mobile multi-degree-of-freedom robotic arm, and arrange a number of spherical reflectors on the base of the three-dimensional scanner; Wherein, the laser tracker measures the relative position of the three-dimensional scanner by tracking the spherical reflector on the base of the mobile multi-degree-of-freedom mechanical arm; S2: using a laser tracker to measure the spatial position of a spherical reflector arranged on the three-dimensional scanner, and recording it as the initial position of the three-dimensional scanner; S3: Arrange multiple spherical reflectors on the large complex curved surface part to be measured and use them as common reference points, and use the laser tracker and the three-dimensional scanner to simultaneously measure the position information of the common reference points; Among them, the 3D scanner installed on the mobile multi-DOF robotic arm avoids the optical path of the laser tracker to detect the common reference point; S4: using a common point optimization method to calculate a coordinate transformation matrix H between the two based on the position information of the common reference point measured by the 3D scanner and the laser tracker; The coordinate transformation matrix H is used to calculate the correction value of the scanning detection result of the three-dimensional scanner based on the measurement result of the laser tracker. S5: moving the three-dimensional scanner by a mobile multi-degree-of-freedom robotic arm to perform partition scanning on the large complex curved surface part to be tested; and measuring the new position of the three-dimensional scanner after each movement by a laser tracker; S6: Record the point cloud data of each partition collected by the 3D scanner, and calculate the point cloud data of each partition and the corresponding reference offset ΔL according to the initial position and new position of the 3D scanner measured by the laser tracker and the coordinate transformation matrix H: Among them, (x ik ,y ik ,z ik ) represents the coordinates of the common point measured by the 3D scanner before the kth transfer; (x jk ,y jk ,z jk ) represents the coordinates of the common point measured by the three-dimensional scanner after the k-th station transfer; Indicates the reference coordinates of the 3D scanner; S7: Combine the coordinate transformation matrix H of the 3D scanner and the laser tracker, the point cloud data of each partition, and the corresponding reference offset ΔL to generate the overall point cloud data of the large complex curved surface part to be measured. The process is as follows: S71: adjusting the coordinate values ​​of the point cloud data of each partition in combination with the reference offset ΔL to ensure that the coordinates of all data points refer to the same reference; S72: merging the point cloud data in each partition after the unified benchmark into a complete point cloud data, ensuring that the point cloud data of each partition is correctly aligned to avoid overlap or misalignment; S73: using the coordinate transformation matrix H, transforming the point cloud data merged in the previous step from the local coordinate system of the 3D scanner to the global coordinate system of the laser tracker to obtain the overall point cloud data; S8: Place a spherical reflector in a special area of ​​a large complex curved surface part that cannot be scanned by a 3D scanner, and use a laser tracker to directly measure it, and add the measurement result to the overall point cloud data; Among them, the three-dimensional scanner installed on the mobile multi-degree-of-freedom robotic arm avoids the detection light path of the laser tracker.

2. The method for measuring large complex curved surface parts based on the combined relay method according to claim 1, characterized in that: In step S3, the number of the common reference points is no less than 3.

3. The method for measuring large complex curved surface parts based on the combined relay method as claimed in claim 2, characterized in that: In step S4, the format of the coordinate transformation matrix H is as follows: In the above formula, R 3×3 (αβγ) represents the rotation matrix of the coordinate system; α, β, γ are the rotation angles of a point in space on the x, y, and z axes; T 3×1 (T x T y T z ) represents the translation vector of each point, T x , T y and T z They are the translations of a point in space relative to the origin on the x, y, and z axes, respectively.

4. The method for measuring large complex curved surface parts based on the combined relay method as claimed in claim 3, characterized in that: The rotation matrix R 3×3 (αβγ) satisfies the following formula:

5. The method for measuring large complex curved surface parts based on the combined relay method as claimed in claim 4, characterized in that: Correction value Satisfies the following expression: In the above formula, Represents the Cartesian coordinates of the common reference point measured by the 3D scanner; A coordinate system representing the transformation between the laser tracker coordinates and the Cartesian coordinates measured by the 3D scanner; Indicates the coordinates of the common reference point measured by the 3D scanner in the laser tracker; Indicates the offset of the common reference point measured by the 3D scanner relative to the origin of the 3D scanner.

6. The method for measuring large complex curved surface parts based on the combined relay method according to claim 1, characterized in that: In step S7, the laser tracker obtains the homogeneous coordinates Q of any observation point gi The laser tracker measures the coordinate system O G -X G Y G Z G Indicated as P gi : Any observation point Q obtained by the 3D scanner si In the 3D scanner coordinate system O S -X S Y S Z S The homogeneous coordinates in are denoted as P si : The coordinate transformation formula of the same observation point obtained by the laser tracker and the 3D scanner in different coordinate systems is as follows: P gi = G H S P si In the above formula, G H S Represents the transformation matrix of the laser tracker and 3D scanner.

7. The method for measuring large complex curved surface parts based on the combined relay method as claimed in claim 6, characterized in that: In step S7, the homogeneous coordinates Q of the spherical reflector are ci In the laser tracker's coordinate system O G -X G Y G Z G Indicated as P ci : Then in the coordinate system O of the laser tracker G -X G Y G Z G In the figure, the coordinates of the spherical reflector are ci It can be calculated by the following formula: P ci = G H I Q ci , In the above formula, G H I Represents the transformation matrix between the measurements of the 3D scanner and the measurements of the laser tracker.

8. The method for measuring large complex curved surface parts based on the combined relay method as claimed in claim 7, characterized in that: In step S7, a transformation matrix is ​​used to transform the measurement value of the 3D scanner into the coordinate system of the laser tracker. I H S The expression is as follows: In the above formula, yes G H I The inverse matrix of .

9. A data processing module, comprising a memory, a processor and a computer program stored in the memory, characterized in that: When the processor executes the computer program, the steps in the method for measuring large complex curved surface parts based on the combined relay method as described in any one of claims 1 to 8 are used to achieve coordinate transformation of the point cloud data measured by the laser tracker and the three-dimensional scanner in their respective coordinate systems.

10. A measurement system for large complex curved surface parts, comprising: A laser tracker mounted on a base; A fixing mechanism, which is used to fix the large complex curved surface parts to be measured; A mobile multi-degree-of-freedom mechanical arm is fixedly installed between the laser tracker and the fixing mechanism and is located on a side close to the fixing mechanism; A three-dimensional scanner mounted on the end of a multi-degree-of-freedom robotic arm; A plurality of spherical reflectors, some of which are mounted on the base of the three-dimensional scanner to assist the laser tracker in measuring the relative position of the three-dimensional scanner; another portion of the spherical reflectors are placed on the large complex curved surface part to be measured to directly measure a portion of the large complex curved surface part to be measured; A host computer is electrically connected to the laser tracker, the mobile multi-degree-of-freedom robotic arm and the three-dimensional scanner; the host computer is used to control and record the operating status of the laser tracker, the mobile multi-degree-of-freedom robotic arm and the three-dimensional scanner, and to collect measurement data from the laser tracker and the three-dimensional scanner; and further implement the steps in the measurement method of large complex curved surface parts based on the combined relay method as described in any one of claims 1 to 8 to obtain the overall point cloud data of the large complex curved surface parts to be measured.

Images