Three-dimensional measurement method and system for key appearance characteristics of aircraft surface, and usage method

Abstract

A three-dimensional measurement method for the key appearance characteristics of an aircraft surface. In the method, the distribution characteristics of point clouds are fully utilized, and an included angle is formed between a direction vector of each measurement point position and a seam direction, so that it is ensured that the point clouds can gradually approach the edges of actual seams, and the impact of randomness is eliminated. The point nearest to the seams in the point clouds on two sides of the seams is selected as the nearest point, so that the limitation of the point cloud density is overcome, and the distance between the selected nearest point and the edges of the actual seams is greatly reduced, thereby greatly reducing the error of gap measurement, and greatly reducing errors caused by insufficient point cloud density. Further provided are a three-dimensional measurement system for the key appearance characteristics of an aircraft surface, and a usage method for the three-dimensional measurement system.

Description

Three-dimensional measurement method, system and use method of key aircraft surface topographic features Technical Field

[0001] The present invention relates to the field of digital measurement technology, and in particular to a three-dimensional measurement method, system and use method of key surface morphological features of an aircraft. Background Art

[0002] For advanced aircraft manufacturing, surface quality is crucial for achieving key performance indicators. This quality is ensured by measuring key surface features, including nail head concavity and convexity, as well as gap height and gap height. Currently, this measurement is primarily done manually, using micrometer pads, feeler gauges, visual inspection, and touch. This results are highly subjective and uncertain, and cannot guarantee the high surface quality requirements of advanced aircraft. Furthermore, manual testing is inefficient and cannot meet the demands of mass production.

[0003] In addition, although structured light can be used to automatically obtain three-dimensional point clouds of aircraft surfaces, there is still a lack of methods to extract and calculate key morphological features, which hinders the widespread application of automated measurement.

[0004] The existing technology, including a Chinese invention patent with publication number CN114626470A and publication date of June 14, 2022, discloses a technical solution that uses the directed distance D from each point on one of the two curves of the seam contour to the other to calculate the corresponding seam gap. This technical solution fails to reduce the error caused by insufficient point cloud density.

[0005] In the prior art, a Chinese invention patent document with publication number CN111028221A, published on April 17, 2020, discloses the following technical solution: Using joint feature points to fit characteristic lines, the gap and step difference between the joints are calculated based on the spatial positional relationship of the joint feature lines. However, due to the discrete nature of the point cloud, the joint feature points used to fit the characteristic lines are always some distance away from the actual joint edges, resulting in an inflated gap measurement.

[0006] A Chinese invention patent, published on October 23, 2020, also mentions a technique using T-Scan to scan the seams and calculate the gap step difference using edge critical points. However, the distance between the edge critical points and the actual seam edge is random and often less than or equal to the distance between adjacent points in the point cloud.

[0007] A Chinese invention patent, published on December 8, 2020, with publication number CN112053361A, has been proposed. This patent describes a technical solution that defines the single-sided gap as the distance from a boundary point on one side to an auxiliary line on the opposite side. However, due to the density of the point cloud, this boundary point is somewhat distant from the actual edge of the joint, leading to errors in the gap measurement.

[0008] In the prior art, a Chinese invention patent document with publication number CN114627177A and announcement date of June 14, 2022 has also been proposed. The technical solution disclosed in this patent document is as follows: the step height and gap width are calculated using the segment endpoints, but since the segment endpoints are subject to the density of the point cloud, it is difficult to ensure their distance from the actual seam edge.

[0009] None of the above technical solutions can overcome the limitation of point cloud density and reduce the error caused by insufficient point cloud density, resulting in large errors in gap measurement.

[0010] Furthermore, with the development of automated measurement technology, three-dimensional measurement technologies such as surface structured light have gradually entered the aviation manufacturing field and are being applied to measure aircraft surface quality. An aircraft's surface is divided into exterior and interior surfaces. The exterior surface is larger, and to improve measurement efficiency, a larger measurement area is required. Therefore, the structured light measurement system requires a longer measurement distance. However, for interior surfaces with narrow internal spaces, the structured light measurement system must have a shorter measurement distance to smoothly access internal surfaces such as air intakes for measurement. However, the measurement distance of existing structured light measurement systems is fixed and cannot simultaneously meet the different measurement distance requirements for both the exterior and interior surfaces of an aircraft. Therefore, there is an urgent need to develop a structured light three-dimensional measurement system with a variable measurement distance.

[0011] Summary of the Invention

[0012] In order to solve the above technical problems, the present invention proposes a three-dimensional measurement method, system and method of use for key morphological features of aircraft surfaces. This measurement method makes full use of the distribution characteristics of point clouds, forms an angle between the direction vector of the measurement point and the direction of the seam, ensures that the point cloud can gradually approach the edge of the actual seam, eliminates the influence of randomness, and enables the selection of the closest point to the actual seam edge in the point cloud on both sides of the seam, overcomes the limitation of point cloud density, and greatly reduces the distance from the selected closest point to the actual seam edge, thereby greatly reducing the error of gap measurement and greatly reducing the error caused by insufficient point cloud density. The measurement distance of this measurement system is variable, which can meet different requirements for measurement distance when three-dimensionally measuring the internal and external surfaces of an aircraft.

[0013] The present invention is achieved by adopting the following technical solutions:

[0014] The three-dimensional measurement method of key morphological features of an aircraft surface includes the following steps:

[0015] Step S1. Plan three-dimensional measurement points based on the nail head and seam information in the aircraft digital model, and obtain a two-dimensional image and three-dimensional point cloud information of the aircraft surface; wherein the direction vector of the measurement point forms an angle β with the seam direction;

[0016] Step S2. Automatically identify and extract the location information of the rivet and the seam in the 2D image. Utilize the correspondence between the 2D image and the 3D point cloud to obtain the point cloud corresponding to the rivet and the seam, and then calculate the rivet concave-convex amount, the seam step difference, and the seam gap.

[0017] The calculation method of the seam gap is as follows: the seam gap is obtained by finding the closest point in the point cloud on both sides of the seam in the direction perpendicular to the seam.

[0018] The method for calculating the gap in step S2 specifically includes the following steps:

[0019] Step S 221 Based on the acquired two-dimensional image, obtain two edge lines of the seam, and extend the two edge lines outward by a distance l3 to obtain two image sub-regions of the seam;

[0020] Step S 222 According to the correspondence between the two-dimensional image and the three-dimensional point cloud, the point cloud set Ω3 and the point cloud set Ω4 corresponding to the two image sub-regions of the seam are obtained;

[0021] Step S 223 . Calculate the shortest distance between the point clouds of the point cloud set Ω3 and the point cloud set Ω4 in the x direction, and calculate the gap between the seams, where the x direction is the direction perpendicular to the seam.

[0022] The step S 223 Specifically, take the x coordinate of the point with the largest x coordinate in the point cloud set Ω3 on the left side of the seam and the x coordinate of the point with the smallest x coordinate in the point cloud set Ω4 on the right side of the seam, and the calculation method of the seam gap is: i =x2-x1;

[0023] Among them, d i is the gap between the ith sampling point.

[0024] The step S 223 Specifically refers to:

[0025] The point cloud set Ω3 and the point cloud set Ω4 are split at every distance to generate point cloud subsets and point cloud subsets m is the number of sub-sets contained in the point cloud set Ω3 and the point cloud set Ω4;

[0026] Compute point cloud subsets and point cloud subsets The shortest distance between the point clouds in the x direction, that is, the subset of point clouds on the left side of the seam The x-coordinate x1 of the point with the largest x-coordinate and the point cloud subset on the right side of the seam The x-coordinate of the point with the smallest x-coordinate is x2, and the calculation method of the gap is:

[0027] d i =x2-x1; where d i is the gap between the two seams at the i-th sampling point;

[0028] Repeat the above steps for all subsets of point cloud set Ω3 and point cloud set Ω4 to obtain m gaps d i , i=1,2,...,m。

[0029] The calculation method of the gap step difference is:

[0030] Step S 231 Based on the acquired two-dimensional image, obtain two edge lines of the seam, and extend the two edge lines outward by a distance l3 to obtain two image sub-regions of the seam;

[0031] Step S 232 According to the correspondence between the two-dimensional image and the three-dimensional point cloud, the point cloud set Ω3 and the point cloud set Ω4 corresponding to the two image sub-regions of the seam are obtained;

[0032] Step S 233 Perform plane fitting on all points in the point cloud set Ω3 to obtain the plane, calculate the distance from all points in the point cloud set Ω4 to the plane and average it to obtain the gap step difference ε i , where ε i is the gap step difference at the i-th sampling point.

[0033] The step S 233 Specifically include:

[0034] The point cloud set Ω3 and the point cloud set Ω4 are split every distance l4 to generate point cloud subsets and point cloud subsets m is the number of sub-sets contained in the point cloud set Ω3 and the point cloud set Ω4;

[0035] Point cloud subset Perform plane fitting on all points in the point cloud to obtain plane P2. The equation of plane P2 is A2x+B2y+C2z+D2=0. Calculate the point cloud subset. The distance from all points to plane P2 is averaged to obtain the gap step difference εi ;

[0036] Among them, ε i is the step difference of the seam at the i-th sampling point; A2, B2, C2 and D2 are the coefficients of the plane equation respectively;

[0037] Repeat the above steps for all subsets of point cloud set Ω3 and point cloud set Ω4 to obtain m gap step differences ε i , i=1,2,...,m。

[0038] The distance Among them, d0 is the distance between adjacent points of the measurement point cloud, and β is the angle formed by the direction vector of the measurement point and the seam direction.

[0039] The step S2 further includes pre-processing the two-dimensional image, that is, performing pixel-by-pixel averaging on the collected two-dimensional image.

[0040] Obtaining the two edge lines of the seam specifically includes: performing edge detection using the Canny operator to obtain edge information of the seam; then screening using length and continuity, and performing straight line fitting to obtain the two edge lines of the seam.

[0041] The step S1 specifically includes the following steps:

[0042] Step S 11 Extract the normal vector information of each nail head in the measurement area and calculate the normal vector of the measurement point after averaging;

[0043] Step S 12 Extract the position information of each nail head in the measurement area, average it and offset the measurement distance l0 in the direction of the average normal vector to obtain the position of the measurement point;

[0044] Step S 13 Extract the direction information of the seam in the measurement area so that the direction vector of the measurement point forms an angle β with it;

[0045] Step S 14 .Based on the position and direction vector of the measurement point, measurement is performed to obtain two-dimensional images and three-dimensional point cloud information of the aircraft surface.

[0046] Calculating the rivet concave-convex amount in step S2 specifically includes the following steps:

[0047] Step S 211 Perform circle recognition in the captured 2D image to obtain rivet edge information; perform ellipse fitting on the rivet edge and extend it inward by a distance l1 to obtain the rivet image subregion; then extend the ellipse fitting result of the rivet edge outward by a distance l2 to obtain the skin image subregion;

[0048] Step S 212 According to the correspondence between the two-dimensional image and the three-dimensional point cloud, obtain the rivet point cloud set Ω1 and the skin point cloud set Ω2 corresponding to the rivet image sub-region and the skin image sub-region;

[0049] Step S 213 Perform plane fitting on the skin point cloud set Ω2 to obtain the skin plane P1. The equation of the skin plane is A1x+B1y+C1z+D1=0. The calculation method of the rivet concave and convex amount is:

[0050] Among them, (x i ,y i , z i ), i = 1, 2, ..., n is the point cloud coordinate, n is the total number of point clouds in the rivet point cloud set, A1, B1, C1 and D1 are the coefficients of the plane equation respectively, and δ is the rivet concave-convex amount.

[0051] A three-dimensional measurement system for key morphological features of an aircraft surface is used in the above-mentioned three-dimensional measurement method for key morphological features of an aircraft surface to obtain two-dimensional images and three-dimensional point cloud information of the aircraft surface; the measurement system includes a camera, a projector, and a drive assembly; the drive assembly is used to drive the camera and projector to rotate simultaneously in opposite directions by the same angle to increase or decrease the measurement distance, and the center of the measurement range is always located on the perpendicular bisector of the line connecting the optical centers of the camera and projector.

[0052] The driving assembly includes a camera gear, a projector gear, a camera rack, a projector rack and a driving gear; the camera and projector are respectively arranged on the camera gear and the projector gear; the radius of the camera gear, the projector gear and the driving gear are the same; the camera rack includes a first rack for engaging with the camera gear and a second rack for engaging with the driving gear; the projector rack includes a third rack for engaging with the projector gear and a fourth rack for engaging with the driving gear; the driving gear rotates to simultaneously drive the second rack and the fourth rack to move in opposite directions, further driving the camera gear and the projector gear to rotate in opposite directions at the same angle, thereby driving the camera and the projector to rotate in opposite directions at the same angle, for adjusting the measuring distance.

[0053] Initially, the camera and projector optical axes have the same angle with the horizontal direction.

[0054] Angle encoders are installed on the camera gear and the projector gear.

[0055] The lenses installed on the camera and the projector are both mechanical zoom lenses.

[0056] The method for using the three-dimensional measurement system for key morphological features of an aircraft surface is to drive the camera and projector to rotate away from each other when measuring the exterior of the aircraft to increase the measurement distance; when measuring the narrow space inside the aircraft, drive the camera and projector to rotate towards each other at the same time to reduce the measurement distance.

[0057] Compared with the prior art, the present invention has the following beneficial effects:

[0058] 1. This invention proposes an automated identification and extraction method for key aircraft surface topographic features that combines two- and three-dimensional information. This method can automatically identify and extract the location information of rivets and seams in a two-dimensional image. By utilizing the correspondence between two-dimensional images and three-dimensional point clouds, the corresponding point clouds of the rivets and seams are obtained. The rivet head concavity, seam step difference, and seam gap are then calculated, enabling automated inspection of aircraft surface quality. The innovative method for extracting rivets and seams that combines two- and three-dimensional information makes the identification and extraction process highly efficient and robust.

[0059] 2. The present invention proposes a small-angle super-resolution method to improve the accuracy of gap measurement. When measuring the point cloud, the measurement direction is offset from the gap direction by a small angle, and then the closest point perpendicular to the gap in the point cloud on both sides is found to obtain the gap. This angle ensures that the point cloud can gradually approach the edge of the actual gap, eliminating the influence of randomness, greatly reducing the distance from the closest point to the actual gap edge, and thus greatly reducing the error in gap measurement. In the prior art, the distance from the boundary point to the gap edge is highly random, and its fluctuation range is equal to the distance between adjacent points in the point cloud.

[0060] Through this method, the present invention enables the measurement accuracy of the gap to be freed from the limitation of point cloud resolution for the first time, thereby greatly improving the measurement accuracy of the gap.

[0061] 3. In the present invention, an ellipse is fitted to the edge of the rivet, and a distance l1 is extended inward as the range of the rivet, which can avoid the influence of the pit and avoid causing large errors.

[0062] 4. In the present invention, the collected two-dimensional image is averaged pixel by pixel, which can eliminate the stripe characteristics, make the pixel value of the image more accurate, obtain the image of the real scene, and extract more accurate rivet edges and seam edges.

[0063] 5. This measurement system utilizes a rack-and-pinion structure to adjust the angle between the camera and projector, thereby varying the measurement distance, to meet the varying measurement distance requirements for both interior and exterior aircraft surfaces. Furthermore, by rotating the camera and projector in opposite directions at the same angle, the center of the measurement range is always located on the perpendicular bisector connecting the optical centers of the camera and projector. This allows the system to adapt to changing measurement distances without requiring changes in the measurement range in practical applications.

[0064] 6. Angle encoders are installed on the camera and projector gears to accurately record the rotation angle. This angle information can be used to calculate the extrinsic parameter matrices of the camera and projector, avoiding repeated calibration after each rotation.

[0065] 7. The measurement system of the present invention, combined with a mechanical zoom lens, can automatically adjust the measurement distance to achieve automated measurement of the interior and exterior surfaces of an aircraft.

[0066] 8. The present invention innovatively proposes a three-dimensional measurement method that changes the measured distance by changing the angle between the camera and the projector. Using this measurement system, it can adapt to the different needs of three-dimensional measurement of the internal and external surfaces of an aircraft and realize the acquisition of a complete point cloud of the aircraft surface. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments, wherein:

[0068] FIG1 is a schematic diagram of a point cloud for measuring a seam in the present invention;

[0069] FIG2 is a schematic diagram of a process of the present invention;

[0070] FIG3 is a schematic diagram of a process for calculating the gap between the seams in the present invention;

[0071] FIG4 is a schematic diagram of a process for calculating the step difference of the seams in the present invention;

[0072] FIG5 is a schematic diagram of the process of obtaining the average brightness of an image in the present invention;

[0073] FIG6 is a schematic diagram of rivet edge extraction results in the present invention;

[0074] FIG7 is a schematic diagram of the extraction results of the image sub-regions of the rivet and the image sub-regions of the skin in the present invention;

[0075] FIG8 is a schematic diagram of the seam edge extraction result in the present invention;

[0076] FIG9 is a schematic diagram of the results of seam sub-region extraction in the present invention;

[0077] FIG10 is a schematic structural diagram of the measurement system of the present invention;

[0078] Markings in the figure: 1. Camera, 2. Projector, 3. Camera gear, 4. Projector gear, 5. Camera rack, 6. Projector rack, 7. Drive gear, 8. Mounting flange. DETAILED DESCRIPTION

[0079] Example 1

[0080] As a basic embodiment of the present invention, the present invention includes a three-dimensional measurement method for key topographical features of an aircraft surface, comprising the following steps:

[0081] Step S1. Plan three-dimensional measurement points based on the nail head and seam information in the aircraft digital model, such that the direction vector at the measurement point forms an angle β with the seam direction. At these measurement points, a structured light measurement device is used to obtain a two-dimensional image and three-dimensional point cloud of the aircraft surface. The structured light measurement device can employ conventional structures in the art, including an industrial camera and a multi-line structured light emitter.

[0082] Step S2. Automatically identify and extract the position information of the rivets and the seams in the two-dimensional image, and use the correspondence between the two-dimensional image and the three-dimensional point cloud to obtain the point cloud corresponding to the rivets and the seams, and then calculate the rivet concave-convex amount, the seam step difference, and the seam gap.

[0083] Automatically identifying and extracting the position information of rivets and seams, calculating the rivet convexity and concaveness, and calculating the seam step difference can all be accomplished using conventional technical means in this field. For example, a multi-level model fitting algorithm is used to extract the rivet contour features and the seam contour features, and then the rivet convexity is calculated based on the extracted rivet contour features, and the seam step difference is calculated based on the seam contour features.

[0084] The method for calculating the gap between the two seams is to find the closest point in the point cloud on both sides of the seam in the perpendicular direction to the seam, thereby obtaining the gap between the two seams. The method for finding the closest point can adopt conventional technical means in the art.

[0085] Example 2

[0086] As a preferred embodiment of the present invention, this embodiment is based on the above-mentioned embodiment 1 and describes a specific implementation method for calculating the gap in step S2.

[0087] In this embodiment, based on the two-dimensional image and three-dimensional point cloud information of the aircraft surface obtained in step S1 above, the method for calculating the seam gap specifically includes the following steps:

[0088] Step S 221 .According to the collected two-dimensional image, two edge lines of the seam are obtained, and the two edge lines are extended outward by a distance l3 to obtain two image sub-regions of the seam.

[0089] Step S 222 According to the correspondence between the two-dimensional image and the three-dimensional point cloud, the point cloud set Ω3 and the point cloud set Ω4 corresponding to the two image sub-regions of the seam are obtained.

[0090] Step S 223 . Calculate the shortest distance in the x direction between the point cloud set Ω3 and the point cloud set Ω3. Take the x coordinate x1 of the point with the largest x coordinate in the point cloud set Ω3 on the left side of the seam and the x coordinate x2 of the point with the smallest x coordinate in the point cloud set Ω4 on the right side of the seam. The calculation method of the seam gap is: d i =x2-x1.

[0091] Among them, d i is the gap between the two slits at the i-th sampling point, and the x direction is the direction perpendicular to the slit.

[0092] In this embodiment, since the direction vector of the measurement point is deflected at an angle to the seam direction, it is ensured that the point cloud can gradually approach the edge of the actual seam. Then, the point closest to the seam in the point cloud on both sides of the seam is selected as the nearest point, and the difference between its coordinates perpendicular to the seam direction is taken, which can greatly reduce the error caused by insufficient point cloud density.

[0093] Example 3

[0094] As a preferred embodiment of the present invention, this embodiment is a further detailed supplement and explanation of the seam gap calculation of the present invention based on the above-mentioned embodiment 1 or embodiment 2. In this embodiment, after obtaining the point cloud set Ω3 and the point cloud set Ω4 corresponding to the two image sub-regions of the seam, it is necessary to split the point cloud set Ω3 and the point cloud set Ω4 at a distance l4 to generate point cloud subsets. and point cloud subsets m is the number of subsets contained in the point cloud set Ω3 and the point cloud set Ω4, and is also the number of sampling points

[0095] By calculating the point cloud subset and point cloud subsets The shortest distance between point clouds in the x direction, that is, taking the point cloud subset on the left side of the seam The x-coordinate x1 of the point with the largest x-coordinate and the point cloud subset on the right side of the seam The x-coordinate of the point with the smallest x-coordinate is x2, so the calculation method of the gap is: i =x2-x1;

[0096] Among them, d i is the gap between the ith sampling point.

[0097] Repeat the above steps for all subsets of point cloud set Ω3 and point cloud set Ω4 to obtain m gaps di , i=1,2,...,m。

[0098] Since the length of the seam is long and the gaps at different locations vary greatly, this embodiment divides the point cloud set on both sides of the seam, and can calculate the seam gaps at various locations, making the seam gap calculation more accurate.

[0099] Example 4

[0100] As a preferred embodiment of the present invention, this embodiment further supplements and elaborates on the calculation of the seam step difference based on the above-mentioned embodiment 1, embodiment 2 or embodiment 3.

[0101] Specifically, in this embodiment, the method for calculating the seam step difference includes:

[0102] Step S 231 .According to the collected two-dimensional image, two edge lines of the seam are obtained, and the two edge lines are extended outward by a distance l3 to obtain two image sub-regions of the seam.

[0103] Step S 232 According to the correspondence between the two-dimensional image and the three-dimensional point cloud, the point cloud set Ω3 and the point cloud set Ω4 corresponding to the two image sub-regions of the seam are obtained.

[0104] Step S 233 Perform plane fitting on all points in the point cloud set Ω3 to obtain the plane, calculate the distance from all points in the point cloud set Ω4 to the plane and average it to obtain the gap step difference ε i Among them, ε i The plane fitting algorithm is a conventional technical means in this field and will not be described in detail in this embodiment.

[0105] Example 5

[0106] As a preferred embodiment of the present invention, this embodiment is based on the above embodiment 3 and further supplements and explains the calculation of the seam step difference. In this embodiment, after obtaining the point cloud set Ω3 and the point cloud set Ω4 corresponding to the two image sub-regions of the seam, the point cloud set Ω3 and the point cloud set Ω4 are split at a distance l4 to generate point cloud subsets. and point cloud subsets m is the number of subsets contained in the point cloud set Ω3 and the point cloud set Ω4, and is also the number of sampling points

[0107] Point cloud subset Perform plane fitting on all points in the point cloud to obtain plane P2. The equation of plane P2 is A2x+B2y+C2z+D2=0. Calculate the point cloud subset. The distance from all points to plane P2 is averaged to obtain the gap step difference ε i .

[0108] Among them, ε i is the gap step difference at the i-th sampling point; A2, B2, C2 and D2 are the coefficients of the plane equation respectively.

[0109] Repeat the above steps for all subsets of point cloud set Ω3 and point cloud set Ω4 to obtain m gap step differences ε i , i=1,2,...,m。

[0110] Example 6

[0111] As a preferred embodiment of the present invention, this embodiment further supplements and elaborates on the calculation method of the rivet concave-convex amount in the present invention on the basis of the above-mentioned embodiment 1 or embodiment 2 or embodiment 3 or embodiment 4 or embodiment 5.

[0112] The specific calculation method of the rivet concave-convex amount includes:

[0113] Step S 211 Circle recognition is performed in the captured 2D image to obtain rivet edge information. Since the captured 2D image has obvious stripe characteristics, to better obtain rivet edge information, the captured 2D image can be preprocessed. This involves taking a pixel-by-pixel average of the image to eliminate the stripe characteristics and obtain an image of the real scene.

[0114] On this basis, an ellipse fitting is performed on the edge of the rivet, and the distance l1 is extended inward to obtain the image sub-region of the rivet. The ellipse fitting result of the rivet edge is extended outward by a distance l2 to obtain the image sub-region of the skin.

[0115] Prior art proposes patent document CN113129445A, published on July 16, 2021. This document uses points within the cylinder corresponding to the rivet's outline as the initial rivet point cloud. However, in practice, rivets often have pits at their centers, which can introduce significant errors. Compared to this patent, this embodiment performs an ellipse fit on the rivet's edge and extends it inward by a distance l1 to obtain an image subregion of the rivet, thus avoiding the influence of pits.

[0116] Step S 212 According to the correspondence between the two-dimensional image and the three-dimensional point cloud, the rivet point cloud set Ω1 and the skin point cloud set Ω2 corresponding to the rivet image sub-region and the skin image sub-region are obtained.

[0117] Step S 213Perform plane fitting on the skin point cloud set Ω2 to obtain the skin plane P1. The equation of the skin plane is A1x+B1y+C1z+D1=0. The calculation method of the rivet concave and convex amount is:

[0118] Among them, (x i ,y i , z i ), i = 1, 2, ..., n is the point cloud coordinate, n is the total number of point clouds in the rivet point cloud set, A1, B1, C1 and D1 are the coefficients of the plane equation respectively, and δ is the rivet concave-convex amount.

[0119] Example 7

[0120] As another preferred embodiment of the present invention, this embodiment is based on any one of the above embodiments 1 to 6, and further supplements and elaborates on the technical solution of planning three-dimensional measurement points according to the nail head and seam information in the aircraft digital model in the present invention.

[0121] In this embodiment, the three-dimensional measurement points are planned based on the nail head and seam information in the aircraft digital model to obtain a two-dimensional image and three-dimensional point cloud information of the aircraft surface. The following steps are specifically included:

[0122] Step S 11 .Extract the normal vector information of each nail head in the measurement area, and calculate the normal vector of the measurement point after averaging.

[0123] Step S 12 .Extract the position information of each nail head in the measurement area, average it and offset the measurement distance l0 in the direction of the average normal vector to obtain the position of the measurement point.

[0124] Step S 13 .Extract the direction information of the seam in the measurement area so that the direction vector of the measurement point forms an angle β with it.

[0125] Step S 14 .Based on the position and direction vector of the measurement point, measurement is performed to obtain two-dimensional images and three-dimensional point cloud information of the aircraft surface.

[0126] Example 8

[0127] As another preferred embodiment of the present invention, a three-dimensional measurement system for key aircraft surface topographical features is provided. This measurement system is a structured light measurement system comprising a camera 1, a projector 2, and a drive assembly. In this embodiment, the specific structure of the drive assembly is not limited; it is sufficient that the drive assembly can drive the camera 1 and projector 2 to rotate simultaneously in opposite directions and at the same angle to increase or decrease the measurement distance, with the center of the measurement range always located on the perpendicular bisector of the line connecting the optical centers of camera 1 and projector 2. For example, the drive assembly may be a motor that drives the rotation of camera 1 and projector 2, respectively.

[0128] The measurement system can be used in any of the above-described embodiments 1 to 7. By measuring the measurement points in step S1, a two-dimensional image and three-dimensional point cloud information of the aircraft surface can be obtained. Furthermore, the measurement system can also be used independently for other measurement methods to obtain two-dimensional images and three-dimensional point cloud information of the interior and exterior surfaces of an aircraft.

[0129] Example 9

[0130] As a preferred embodiment of the present invention, this embodiment further supplements and elaborates on the driving component based on the above-mentioned embodiment 8.

[0131] If the drive assembly is a motor, not only does it fail to further improve the performance, but it also increases costs. Therefore, this embodiment improves the drive assembly, which includes a camera gear 3, a projector gear 4, a camera rack 5, a projector rack 6, and a drive gear 7. The camera 1 and projector 2 are mounted on the camera gear 3 and projector gear 4, respectively. Initially, the optical axes of the camera 1 and projector 2 are at the same angle with the horizontal. The camera gear 3, projector gear 4, and drive gear 7 have the same radius. The camera rack 5 includes a first rack for meshing with the camera gear 3 and a second rack for meshing with the drive gear 7. The projector rack 6 includes a third rack for meshing with the projector gear 4 and a fourth rack for meshing with the drive gear 7. The second and fourth racks are located on either side of the drive gear 7, respectively. Driven by the drive gear 7, they drive the camera gear 3 and projector gear 4 to rotate in opposite directions by the same angle, thereby driving the camera 1 and projector 2 to rotate in opposite directions by the same angle, ensuring symmetry between the camera 1 and projector 2.

[0132] Example 10

[0133] At present, the surface structure of aircraft is mainly composed of skin, and the connection method is mostly rivets. In order to ensure the surface quality of the aircraft, it is crucial to measure key morphological features such as rivet convexity, seam gap and seam step difference. However, the measurement distance of the existing measurement system is fixed, and it is impossible to simultaneously meet the different requirements of the outer and inner surfaces of the aircraft for the measurement distance. Therefore, the existing detection methods can no longer meet the high requirements of advanced aircraft for surface quality. Therefore, this embodiment proposes a three-dimensional measurement method, system and use method of key morphological features of the aircraft surface. The measurement system can realize adjustable measurement distance and can obtain three-dimensional point cloud information of the inner and outer surfaces of the aircraft. On this basis, the measurement method can extract key morphological features such as nail head convexity, seam step difference and seam gap with high precision, and can be automated without human intervention.

[0134] This embodiment first explains the following professional terms.

[0135] Aircraft digital model: digital model of aircraft.

[0136] This embodiment provides a three-dimensional measurement system for key aircraft surface topographical features. Referring to Figure 10 of the specification, the system comprises a camera 1, a projector 2, a drive assembly, and a mounting flange 8. The drive assembly comprises a camera gear 3, a projector gear 4, a camera rack 5, a projector rack 6, and a drive gear 7. The camera 1 and projector 2 are mounted on the camera gear 3 and projector gear 4, respectively. Initially, the optical axes of the camera 1 and projector 2 are aligned at the same angle to the horizontal. The camera 1 is used to capture images of the fringe pattern projected by the projector 2 onto the aircraft surface.

[0137] The camera gear 3, projector gear 4, and drive gear 7 have the same radius. The camera rack 5 includes a first rack for engaging with the camera gear 3 and a second rack for engaging with the drive gear 7. The projector rack 6 includes a third rack for engaging with the projector gear 4 and a fourth rack for engaging with the drive gear 7. The second and fourth racks are located on either side of the drive gear 7, respectively. The first and third racks may be located on the same vertical line.

[0138] When the measurement distance changes, the camera gear 3 and projector gear 4, driven by their respective racks and drive gear 7, rotate in opposite directions by the same angle. This, in turn, causes the camera 1 and projector 2 to rotate in opposite directions by the same angle, maintaining their symmetry and maximizing the shared field of view. Furthermore, this uniform rotation ensures that the center of the measurement range remains on the perpendicular bisector of the line connecting the optical centers of camera 1 and projector 2. This allows the system to change the measurement distance without having to consider changes in the measurement range in practical applications.

[0139] After the measurement distance changes, the camera 1 and the projector 2 become defocused. At this time, the mechanically adjustable focus lenses installed on the camera 1 and the projector 2 are adjusted to adjust the focal length according to the measurement distance.

[0140] The angles of camera 1 and projector 2 after rotation are accurately obtained through the angle encoders installed on camera gear 3 and projector gear 4. This angle information can be used to calculate the extrinsic parameter matrices of camera 1 and projector 2 for point cloud acquisition.

[0141] When measuring the exterior of an aircraft, camera 1 and projector 2 are driven to rotate away from each other, that is, camera 1 rotates clockwise and projector 2 rotates counterclockwise, thereby increasing the measurement distance, increasing the measurement area, and improving measurement safety to avoid collision with the aircraft. When measuring the narrow space inside the aircraft, camera 1 and projector 2 are driven to rotate toward each other, that is, camera 1 rotates counterclockwise and projector 2 rotates clockwise, thereby decreasing the measurement distance and adapting to the narrow space inside the aircraft.

[0142] When the measuring distance needs to be reduced, the driving gear 7 rotates. Assuming the radius of the driving gear 7 is R (10 mm in this embodiment), when it rotates clockwise by an angle θ (5° in this embodiment), the upward displacement of the camera rack 5 is: The downward displacement of the projector rack 6 is: This drives the gears fixed to the camera 1 and the projector 2 to rotate. θ The unit is: mm.

[0143] Since the camera gear 3 and the projector gear 4 have the same radius R (10 mm) as the drive gear 7, the camera gear 3 rotates counterclockwise by an angle θ (5°), and the projector gear 4 rotates clockwise by an angle θ (5°). To maximize the measurement range, the measurement plane is located at the intersection of the optical axes of camera 1 and projector 2. Assuming that the initial angle between the optical axes of camera 1 and projector 2 and the horizontal direction is α (10° in this embodiment), and the distance between the optical centers of camera 1 and projector 2 is h (150 mm in this embodiment), the change in measured distance is:

[0144] in, is the initial measurement distance, The units of ΔL, L1, and L2 are all in mm for the reduced measurement distance. To increase the measurement distance, the drive gear 7 needs to be rotated counterclockwise in the same manner. Based on the above measurement system, this embodiment also proposes an automated three-dimensional measurement method for key aircraft surface features. Referring to FIG2 of the specification, the method primarily includes the following steps:

[0145] Step S1. Plan 3D measurement points based on the nail head and seam information in the aircraft digital model to obtain a 2D image and 3D point cloud information of the aircraft surface. This specifically includes the following steps:

[0146] Step S 11 .Extract the normal vector information of each nail head in the measurement area, and calculate the normal vector of the measurement point after averaging.

[0147] Step S 12 The position information of each nail head within the measurement area is extracted and averaged, and then offset by a measurement distance l0 in the direction of the average normal vector to obtain the position of the measurement point. The measurement distance l0 is set according to the requirements of the 3D measurement system and is generally between 200 mm and 1000 mm. In this embodiment, it is set to 425.3 mm.

[0148] Step S 13 Extract the direction information of the seam in the measurement area so that the direction vector of the measurement point forms an angle β with it. The value range of the angle β is 3°-20°, and in this embodiment, it is 10°.

[0149] Step S 14 .Based on the position and direction vector of the measurement point, the measurement system is used to perform measurements to obtain two-dimensional images and three-dimensional point cloud information of the aircraft surface.

[0150] Step S2. Automatically identify and extract the position information of rivets and seams in the two-dimensional image, and use the correspondence between the two-dimensional image and the three-dimensional point cloud to obtain the point cloud corresponding to the rivet and the seam, and then calculate the rivet concave-convex amount, seam step difference and seam gap.

[0151] The two-dimensional images acquired by the measurement system have obvious stripe features. All the acquired images are averaged and the stripe features are eliminated to obtain an image of the real scene, as shown in Figure 5 of the specification, which is used for identifying rivets and seams.

[0152] Calculating the rivet concave and convex amount specifically includes the following steps:

[0153] Step S 211 Because rivets have distinct circular features, circle identification is performed in the captured 2D image. Based on grayscale differences, Canny operator edge detection is performed to obtain rivet edge information, as shown in Figure 6 of the specification. Ellipse fitting is performed on the rivet edge and extended inward by a distance l1 to obtain a rivet image subregion. The ellipse fitting result of the rivet edge is extended outward by a distance l2 to obtain a skin image subregion, as shown in Figure 7 of the specification. Distance l1 must be less than the rivet radius; in this example, it is 2 mm. Distance l2 can range from 1.5 mm to 5 mm; in this example, it is 2 mm.

[0154] Step S212 According to the correspondence between the two-dimensional image and the three-dimensional point cloud, the rivet point cloud set Ω1 and the skin point cloud set Ω2 corresponding to the rivet image sub-region and the skin image sub-region are obtained.

[0155] Step S 213 Perform plane fitting on the skin point cloud Ω2 set to obtain the skin plane P1. The equation of the skin plane is A1x+B1y+C1z+D1=0. The calculation method of the rivet concave and convex amount is:

[0156] Among them, (x i ,y i , z i ), i = 1, 2, ..., n is the point cloud coordinate, n is the total number of point clouds in the rivet point cloud set, A1, B1, C1 and D1 are the coefficients of the plane equation respectively, and δ is the rivet concave-convex amount.

[0157] Referring to Figures 3 and 4 of the specification, the calculation method of the seam step difference and the seam gap specifically includes the following steps:

[0158] Step S 221 Because the seam is close to a straight line in the image, a straight line fitting is performed on the two-dimensional image acquired in step S1. Edge detection is performed using the Canny operator to obtain edge information for the seam. Length and continuity are then used to filter the edges, and straight line fitting is performed to obtain two edge lines for the seam. The results are shown in Figure 8 of the accompanying drawings. The two edge lines are then extended outward by a distance l3 to obtain two image subregions for the seam. The results are shown in Figure 9 of the accompanying drawings. The distance l3 ranges from 3 mm to 10 mm, and in this embodiment, is 5 mm.

[0159] Step S 222 According to the correspondence between the two-dimensional image and the three-dimensional point cloud, the point cloud set Ω3 and the point cloud set Ω4 corresponding to the two image sub-regions of the seam are obtained.

[0160] Step S 223 Since the length of the seam is usually long, and the seam step difference and the seam gap vary, in order to measure the seam step difference and the seam gap more precisely, the point cloud set Ω3 and the point cloud set Ω4 are split every distance l4 to generate point cloud subsets. and point cloud subsets m is the number of subsets contained in the point cloud set Ω3 and the point cloud set Ω4, and is also the number of sampling points

[0161] Among them, for the corresponding point cloud subset and point cloud subsets To find the gap between the two points, we need to directly find the subset of the point cloud due to the limited density of the three-dimensional point cloud. and point cloud subsets The distance between the point clouds is limited by the density of the point clouds. Here, a super-resolution method is used to improve the measurement accuracy of the seam: Since the measurement direction of the point cloud in step S1 is deflected by β compared to the seam direction, the positional relationship between the measured point cloud and the seam is shown in Figure 1 of the specification. Assume that the distance between adjacent points of the point cloud measured in step S1 is d0, and the segmentation distance is required here. Specifically, the range of the cutting distance l4 is 20 mm-50 mm, and in this embodiment, the value is 30 mm.

[0162] After the above processing, the seam step difference and the seam gap are calculated, wherein there is no requirement for the calculation order of the seam step difference and the seam gap.

[0163] The calculation method of the gap step difference is:

[0164] For the corresponding point cloud subset and point cloud subsets Find the gap step difference: for the point cloud subset Perform plane fitting on all points in the point cloud to obtain plane P2. The equation of plane P2 is A2x+B2y+C2z+D2=0. Calculate the point cloud subset. The distance from all points to plane P2 is averaged to obtain the gap step difference ε i Among them, ε i is the gap step difference at the i-th sampling point; A2, B2, C2 and D2 are the coefficients of the plane equation respectively.

[0165] Repeat the above steps for all subsets of point cloud set Ω3 and point cloud set Ω4 to obtain m gap step differences ε i , i=1,2,...,m。

[0166] The calculation method of the gap is:

[0167] Compute point cloud subsets and point cloud subsets The shortest distance between point clouds in the x direction, that is, the direction perpendicular to the seam, is to take the subset of point clouds on the left side of the seam. The x-coordinate x1 of the point with the largest x-coordinate and the point cloud subset on the right side of the seam The x-coordinate of the point with the smallest x-coordinate is x2, so the calculation method of the gap is: i =x2-x1.

[0168] Among them, d i is the gap between the ith sampling point.

[0169] Repeat the above steps for all subsets of point cloud set Ω3 and point cloud set Ω4 to obtain m gaps d i , i=1,2,...,m。

[0170] In summary, the technical advancement of the present invention is reflected in the following points:

[0171] 1. Existing technologies, such as Chinese patents with publication numbers CN114626470A, CN111028221A, CN111814888A, CN112053361A, and CN114627177A, are unable to overcome the limitations of point cloud density and reduce the errors caused by insufficient point cloud density, resulting in large errors in gap measurement. However, the present application innovatively proposes that when measuring the point cloud, the measurement direction is offset from the seam direction by a small angle, and then the nearest point in the point cloud on both sides that is perpendicular to the seam is found to obtain the seam gap. This allows the present invention to break away from the limitations of point cloud resolution and greatly reduce the errors caused by insufficient point cloud density.

[0172] 2. In existing technologies, the relative positions of the camera and projector generally remain unchanged, but the two are moved as a whole; either the camera and projector are adjusted separately; or the camera or projector is adjusted. All of these solutions require readjustment of the measurement range, resulting in low measurement efficiency and complex operations.

[0173] On the contrary, in the present invention, by changing the angle between the camera and the projector, the camera and the projector are rotated in opposite directions by the same angle, which can ensure that the center of the measurement range is always located on the perpendicular bisector of the line connecting the optical centers of the camera and the projector. In practical applications, the measurement system can meet different requirements for measurement distances, and there is no need to consider changes in the measurement range when changing the measurement distance.

[0174] The technical solution of the present invention can realize the digital measurement of key morphological features of the aircraft surface, replacing the traditional manual measurement and paper transmission of measurement data, significantly improving measurement efficiency and accuracy, and providing technical support for improving the quality of nail heads and seams on the aircraft surface; at the same time, combined with industrial robots, it can complete the measurement of nail heads and seams on the surface of the entire machine, thus laying the foundation for the closed loop of key performance such as aircraft aerodynamic performance; in addition, this technology can be promoted and applied to the aerospace and automotive fields to improve the quality of related products.

[0175] In summary, after reading the present invention document, ordinary technicians in this field can make various other corresponding transformation schemes based on the technical solutions and technical concepts of the present invention without creative mental work, which all fall within the scope of protection of the present invention.

Claims

1. A three-dimensional measurement method for key morphological features of an aircraft surface, characterized by: The following steps are involved: Step S1. Plan three-dimensional measurement points according to the nail head and seam information in the aircraft digital model, and obtain a two-dimensional image and three-dimensional point cloud information of the aircraft surface; wherein the direction vector of the measurement point forms an angle β with the seam direction; Step S2. Automatically identify and extract the position information of the rivet and the seam in the two-dimensional image, obtain the point cloud corresponding to the rivet and the seam by using the correspondence between the two-dimensional image and the three-dimensional point cloud, and then calculate the rivet concave-convex amount, the seam step difference and the seam gap; The calculation method of the seam gap is as follows: the seam gap is obtained by finding the nearest point in the point cloud on both sides of the seam in a direction perpendicular to the seam.

2. The three-dimensional measurement method of key morphological features of an aircraft surface according to claim 1, characterized in that: The method for calculating the gap in step S2 specifically includes the following steps: Step S 221 .According to the collected two-dimensional image, two edge lines of the seam are obtained, and the two edge lines are extended outward by a distance l3 to obtain two image sub-regions of the seam; Step S 222 According to the correspondence between the two-dimensional image and the three-dimensional point cloud, the point cloud set Ω3 and the point cloud set Ω4 corresponding to the two image sub-regions of the seam are obtained; Step S 223 . Calculate the shortest distance between the point clouds of the point cloud set Ω3 and the point cloud set Ω4 in the x direction, and calculate the gap between the seams, where the x direction is a direction perpendicular to the seam.

3. The three-dimensional measurement method of key morphological features of an aircraft surface according to claim 2, characterized in that: The step S 223 Specifically, take the x-coordinate x1 of the point with the largest x-coordinate in the point cloud set Ω3 on the left side of the seam and the x-coordinate x2 of the point with the smallest x-coordinate in the point cloud set Ω4 on the right side of the seam, then the calculation method of the seam gap is: i =x2-x1; Among them, d i is the gap between the slits at the i-th sampling point.

4. The three-dimensional measurement method of key morphological features of an aircraft surface according to claim 2, characterized in that: The step S 223 Specifically refers to: The point cloud set Ω3 and the point cloud set Ω4 are split every distance l4 to generate point cloud subsets and point cloud subsets m is the number of sub-sets contained in the point cloud set Ω3 and the point cloud set Ω4; Compute point cloud subsets and point cloud subsets The shortest distance between the point clouds in the x direction, that is, taking the point cloud subset on the left side of the seam The x-coordinate x1 of the point with the largest x-coordinate and the point cloud subset on the right side of the seam The x-coordinate x2 of the point with the smallest x-coordinate is used as the calculation method for the gap between the slits: d i =x2-x1; Among them, d i is the gap between the two seams at the i-th sampling point; Repeat the above steps for all subsets of point cloud set Ω3 and point cloud set Ω4 to obtain m gaps d i , i=1, 2, ..., m.

5. The three-dimensional measurement method of key morphological features of an aircraft surface according to claim 1, characterized in that: The calculation method of the gap step difference is: Step S 231 .According to the collected two-dimensional image, two edge lines of the seam are obtained, and the two edge lines are extended outward by a distance l3 to obtain two image sub-regions of the seam; Step S 232 According to the correspondence between the two-dimensional image and the three-dimensional point cloud, the point cloud set Ω3 and the point cloud set Ω4 corresponding to the two image sub-regions of the seam are obtained; Step S 233 . Perform plane fitting on all points in the point cloud set Ω3, obtain the plane, calculate the distance from all points in the point cloud set Ω4 to the plane and average it to obtain the gap step difference ε i , where ε i is the gap step difference at the i-th sampling point.

6. The three-dimensional measurement method of key morphological features of an aircraft surface according to claim 5, characterized in that: The step S 233 Specifically include: The point cloud set Ω3 and the point cloud set Ω4 are split every distance l4 to generate point cloud subsets and point cloud subsets m is the number of sub-sets contained in the point cloud set Ω3 and the point cloud set Ω4; Point cloud sub-collection Perform plane fitting on all points in the point cloud to obtain plane P2. The equation of plane P2 is A2x+B2y+C2z+D2=0. Calculate the point cloud subset The distances from all points to plane P2 are averaged to obtain the gap step difference ε i ; Among them, ε i is the step difference of the seam at the i-th sampling point; A2, B2, C2 and D2 are the coefficients of the plane equation respectively; Repeat the above steps for all subsets of the point cloud set Ω3 and the point cloud set Ω4 to obtain m pairwise gap step differences ε i , i=1, 2, ..., m.

7. The three-dimensional measurement method of key morphological features of an aircraft surface according to claim 4, characterized in that: The distance Among them, d0 is the distance between adjacent points of the measurement point cloud, and β is the angle formed by the direction vector of the measurement point and the direction of the seam.

8. The three-dimensional measurement method of key morphological features of an aircraft surface according to claim 1, characterized in that: The step S2 also includes preprocessing the two-dimensional image, that is, performing pixel-by-pixel averaging on the collected two-dimensional image.

9. The three-dimensional measurement method of key morphological features of an aircraft surface according to claim 2, characterized in that: Obtaining two edge lines of the seam specifically refers to: using the Canny operator to perform edge detection to obtain edge information of the seam; then using length and continuity to perform screening, and performing straight line fitting to obtain two edge lines of the seam.

10. The three-dimensional measurement method of key morphological features of an aircraft surface according to claim 1, characterized in that: The step S1 specifically includes the following steps: Step S 11 .Extract the normal vector information of each nail head in the measurement area, and calculate the normal vector of the measurement point after averaging; Step S 12 . Extract the position information of each nail head in the measurement area, and after averaging, offset the measurement distance l0 in the direction of the average normal vector to obtain the position of the measurement point; Step S 13 . Extract the direction information of the joint in the measurement area, so that the direction vector of the measurement point forms an angle β with it; Step S 14 .Based on the position and direction vector of the measurement point, the measurement is performed to obtain the two-dimensional image and three-dimensional point cloud information of the aircraft surface.

11. The three-dimensional measurement method of key morphological features of an aircraft surface according to claim 1, characterized in that: The calculation of the rivet concave-convex amount in step S2 specifically includes the following steps: Step S 211 . Perform circle recognition in the collected two-dimensional image to obtain the edge information of the rivet; perform ellipse fitting on the edge of the rivet and extend it inward by a distance l1 to obtain the image sub-region of the rivet; extend the ellipse fitting result of the edge of the rivet outward by a distance l2 to obtain the image sub-region of the skin; Step S 212 According to the correspondence between the two-dimensional image and the three-dimensional point cloud, obtain the rivet point cloud set Ω1 and the skin point cloud set Ω2 corresponding to the image sub-region of the rivet and the image sub-region of the skin; Step S 213 . Perform plane fitting on the skin point cloud set Ω2 to obtain the skin plane P1. The equation of the skin plane is A1x+B1y+C1z+D1=0. The calculation method of the rivet concave-convex amount is: Among them, (x i ,y i , z i ), i = 1, 2, ..., n is the point cloud coordinate, n is the total number of point clouds in the rivet point cloud set, A1, B1, C1 and D1 are the coefficients of the plane equation respectively, and δ is the rivet concave and convex amount.

12. A three-dimensional measurement system for key morphological features of an aircraft surface, characterized by: Used in the three-dimensional measurement method of key morphological features of an aircraft surface as described in any one of claims 1 to 11 above, for obtaining a two-dimensional image and three-dimensional point cloud information of the aircraft surface; the measurement system comprises a camera (1), a projector (2) and a drive assembly; the drive assembly is used to drive the camera (1) and the projector (2) to rotate in opposite directions at the same angle at the same time, so as to increase or decrease the measurement distance, and the center of the measurement range is always located on the perpendicular bisector of the line connecting the optical centers of the camera (1) and the projector (2).

13. The three-dimensional measurement system for key morphological features of an aircraft surface according to claim 12, characterized in that: The driving assembly comprises a camera gear (3), a projector gear (4), a camera rack (5), a projector rack (6) and a driving gear (7); the camera (1) and the projector (2) are respectively arranged on the camera gear (3) and the projector gear (4); the radius of the camera gear (3), the projector gear (4) and the driving gear (7) is the same; the camera rack (5) comprises a first rack for meshing with the camera gear (3) and a second rack for meshing with the driving gear (7); the projector rack (6) comprises a third rack for meshing with the projector gear (4) and a fourth rack for meshing with the driving gear (7); the driving gear (7) rotates to simultaneously drive the second rack and the fourth rack to move in the opposite direction, further driving the camera gear (3) and the projector gear (4) to rotate in the opposite direction at the same angle, thereby driving the camera (1) and the projector (2) to rotate in the opposite direction at the same angle, so as to adjust the measuring distance.

14. The three-dimensional measurement system for key morphological features of an aircraft surface according to claim 13, characterized in that: Initially, the angles between the optical axes of the camera (1) and the projector (2) and the horizontal direction are the same.

15. The three-dimensional measurement system for key morphological features of an aircraft surface according to claim 13, characterized in that: Angle encoders are installed on the camera gear (3) and the projector gear (4).

16. The three-dimensional measurement system for key morphological features of an aircraft surface according to claim 12, characterized in that: The lenses installed on the camera (1) and the projector (2) are both mechanical zoom lenses.

17. The method for using the three-dimensional measurement system for key morphological features of an aircraft surface according to claim 12, characterized in that: When measuring the outside of an aircraft, the camera (1) and the projector (2) are driven to rotate in directions away from each other at the same time, thereby increasing the measurement distance; when measuring a narrow space inside an aircraft, the camera (1) and the projector (2) are driven to rotate in directions close to each other at the same time, thereby decreasing the measurement distance.

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