CN113379844B - Method for detecting large-range surface quality of airplane - Google Patents

Method for detecting large-range surface quality of airplane Download PDF

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CN113379844B
CN113379844B CN202110570721.6A CN202110570721A CN113379844B CN 113379844 B CN113379844 B CN 113379844B CN 202110570721 A CN202110570721 A CN 202110570721A CN 113379844 B CN113379844 B CN 113379844B
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韩利亚
周力
陈代鑫
蒋德成
缑建杰
蔡怀阳
陈俊佑
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Chengdu Aircraft Industrial Group Co Ltd
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Abstract

The invention relates to the technical field of aeronautical manufacturing surface quality detection, in particular to a method for detecting the large-range surface quality of an airplane, which comprises the steps of building a system, enabling a line laser to move, simultaneously calculating the lengths of visible laser lines of all cameras, carrying out real-time three-dimensional reconstruction on the laser lines according to the internal and external parameters of the two cameras with the longest common visible laser line and a shot laser line image, converting the laser lines into a unified coordinate system, comparing the obtained three-dimensional data with a three-dimensional model of a detected object, finding out an area with data missing, moving the line laser to scan the area, and repeating the three-dimensional reconstruction steps until complete data is obtained. By the method, the problems of influence of the precision of the movement mechanism and poor overall precision can be effectively solved.

Description

Method for detecting large-range surface quality of airplane
Technical Field
The invention relates to the technical field of aeronautical manufacturing surface quality detection, in particular to a method for detecting the large-range surface quality of an airplane.
Background
The aerial parts and the whole airplane are large in size, and in order to detect the surface quality of the aerial parts or the whole airplane based on images, a movable image acquisition device or a fixed image acquisition device consisting of a large number of cameras is needed. The overall accuracy of the mobile image acquisition device is influenced by the accuracy of the movement mechanism.
The two cameras shoot the same laser line to reconstruct three-dimensional data of the laser line, and three-dimensional data of one shape surface can be generated through sweeping, namely a laser scanning three-dimensional measuring method. When the line laser three-dimensional measurement is carried out by using the double cameras, the laser plane does not need to be calibrated, so that the position of the laser does not have an accurate requirement. Therefore, the fixed image acquisition device composed of a large number of cameras has better adaptability compared with the movable image acquisition device.
However, when a large area of a surface is scanned, for example, when an aircraft complete machine is scanned, due to the visual field limitation of a single camera, a large number of cameras need to be arranged to cover the whole area, and when the number of cameras is increased greatly, the bandwidth requirement of data transmission is also increased greatly, for example, for a gray scale camera with ten million pixel levels, the data volume of each picture is as high as 10MB, if the data is collected at the rate of 30 frames per second, the bandwidth is 300MB/s, a system formed by only 30 cameras needs the support of a ten-trillion network, and if the number of cameras is continuously increased, the bandwidth requirement is difficult to meet.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method for detecting the large-scale surface quality of an airplane, which can effectively solve the problems of poor overall precision due to the influence of the precision of a motion mechanism and effectively reduce the requirement of the data transmission bandwidth of the whole system.
The invention is realized by adopting the following technical scheme:
a method for detecting the quality of a large-scale surface of an airplane is characterized by comprising the following steps: the method comprises the following steps:
step 1, building a large-range multi-camera surface quality detection system, wherein the system comprises a plurality of cameras with fixed positions, a set of visual fields of all the cameras can cover the surface of a detected object, and any point on the surface of the detected object can be visible to at least two cameras;
step 2, sequencing the multiple cameras to ensure that a sufficiently large public view field exists between the cameras with adjacent serial numbers, and a sufficiently large public view field exists between the camera with the last serial number and the camera with the first serial number;
step 3, calibrating internal and external parameters of all cameras;
step 4, driving the line laser to move around the measured object by the moving mechanism, projecting laser to the surface of the measured object, and traversing the whole surface of the measured object;
step 5, in the moving process, all cameras simultaneously calculate the lengths of the visible laser lines, and two cameras with the longest common visible laser line perform real-time three-dimensional reconstruction on the laser line according to internal and external parameters and the shot laser line image, and convert the three-dimensional data into a unified coordinate system according to the internal and external parameters of all the cameras;
step 6, when the two cameras with the longest common visible laser lines change, the two cameras with the longest common visible laser lines are replaced by a new group of cameras for calculation, and the three-dimensional data are converted into a unified coordinate system in the same way;
and 7, comparing the obtained three-dimensional data with the three-dimensional model of the measured object, finding out the area with data missing, moving the line laser to scan the area, and repeating the three-dimensional reconstruction step until complete data is obtained.
In the step 5, all the cameras simultaneously calculate the lengths of the visible laser lines, specifically: setting a brightness threshold value for a camera i, carrying out binarization on an image, enabling pixels at the image position of a laser line to be 1, enabling pixels at other positions to be 0, and calculating the longest diameter L of a pixel connected domain of which the diameter is 1iAnd mixing LiAnd feeding back to the control system.
The longest diameter LiThe calculating method of (2) further includes: drawing a circumscribed rectangle of the connected domain, wherein four sides of the rectangle are tangent to the most prominent points in four directions of the connected domain, rotating the rectangle by taking the center of the rectangle as a rotation center, keeping the constraint of tangency of the four sides in the rotating process, continuously calculating the length of the long side of the rectangle in the rotating process, and the length of the longest long side of the rectangle is Li。
The two cameras with the longest common visible laser line in the step 5 are specifically: to LiSorting, selecting the largest and next largest LiTwo corresponding cameras.
The real-time three-dimensional reconstruction of the laser line in the step 5 specifically includes:
step 5.1, aligning the base line of the camera according to the internal and external parameters of the camera, and aligning the base line of the camera
Figure BDA0003082570060000021
Of (2)
Figure BDA0003082570060000022
Extracted, the coordinate system of camera i is multiplied by
Figure BDA0003082570060000023
Coordinate system multiplication of camera j
Figure BDA0003082570060000024
Wherein camera i and camera j are LiTwo cameras corresponding to the largest and the next largest,
Figure BDA0003082570060000025
converting the coordinate of the camera i and the camera j;
step 5.2, horizontally arranging the converted images of the cameras i and j left and right, wherein the corresponding point of a point P in the three-dimensional space in the images of the cameras i and j is positioned on the same horizontal line;
step 5.3, the center line of the laser line in the image is extracted, and a point P is selected on the center line of the laser line in the image of the camera iiFinding out the corresponding point P on the central line of the laser line in the image of the camera j by making a horizontal linej；
Step 5.4, setting the world coordinate system coordinate of the point P as PWThe world coordinate system is established under the coordinate system of the camera 1, having
Figure BDA0003082570060000031
Simultaneous solvation of PWIn the same way, all points on the central line of the laser line can be reconstructed in three dimensions; wherein, KiIs an internal parameter matrix, K, of camera ijIs the internal parameter matrix of camera j.
The step 7 specifically refers to: let three-dimensional data be P ═ P1,p2,p3,…,pnDispersing the three-dimensional model of the measured object into a point cloud form Q (Q)1,q2,q3,…,qnIn which q isiIs piAnd (3) setting a rotation translation matrix T at the closest point in Q, decomposing the rotation translation matrix T into a rotation matrix R and a translation matrix T, and solving R and T which enable the following objective functions to be minimum:
Figure BDA0003082570060000032
converting P to PT＝P·R+t，PTDeleting the point cloud with P in Q for the point cloud with P and Q alignedTThe distance between the points in the three-dimensional reconstruction method is smaller than a threshold value delta, the remaining points are missing areas, the positions of the points are displayed by coordinates of the points, the line laser is moved to the positions of the points, the areas are scanned, and the three-dimensional reconstruction step is repeated until complete data are obtained.
And the camera lens is provided with an optical filter with the same luminous frequency as the line laser.
The fact that a sufficiently large public view field exists between cameras with adjacent serial numbers in the step 2 specifically means that: the size of the common field of view should exceed 1/3 for the single camera field of view, i.e., the region 1/3 within one camera field of view can be seen by its neighboring cameras; there is enough big public view between the camera of last serial number and the camera of first serial number, specifically: the ordering of the cameras is done in a loop back manner.
Compared with the prior art, the invention has the beneficial effects that:
1. the method is simple and reliable, and has high accuracy and good stability. The method is suitable for acquiring the three-dimensional data of the surface of a large-size measured object to carry out comprehensive detection, and the detection method ensures that the overall measurement precision is independent of the precision of the motion mechanism, only depends on the precision of the calibration of the internal and external parameters of the camera, and has higher precision stability. The requirement on the motion mechanism is low, an open-loop motion mechanism can be adopted, and the difficulty in system construction is low.
2. The form of a motion mechanism carrying the line laser is not required, a three-coordinate gantry mechanism and a six-degree-of-freedom robot can be adopted, the robot can also be held by hands, different motion modes can also be combined for use, and the usability of the system is enhanced;
3. the coordinate system of the measured data is determined by the fixed camera coordinate system, and the data in different measurement examples are located in the same fixed coordinate system, so that the difficulty of data processing is reduced.
4. The camera lens is fitted with a filter having the same frequency as the line laser light to ensure that only the laser light enters the camera lens.
Drawings
The invention will be described in further detail with reference to the following description taken in conjunction with the accompanying drawings and detailed description, in which:
FIG. 1 is a schematic flow diagram of the present invention;
FIG. 2 is a schematic view of the detection system of the present invention.
Detailed Description
Example 1
Referring to the attached drawing 1 of the specification as a basic embodiment of the invention, the invention comprises a method for detecting the quality of a large-scale surface of an airplane, which comprises the following steps:
step 1, a large-range multi-camera surface quality detection system is built and comprises a plurality of cameras with fixed positions, the set of the visual fields of all the cameras can cover the surface of a measured object, and any point on the surface of the measured object can be visible to at least two cameras.
And 2, sequencing the multiple cameras, wherein the serial numbers of the cameras are 1,2,3, … … i, i +1 and … … N in sequence, so that a sufficiently large public view is ensured between the cameras with adjacent serial numbers, and a sufficiently large public view is ensured between the camera with the last serial number and the camera with the first serial number.
And step 3, calibrating internal and external parameters of all cameras.
And 4, driving the line laser to move around the measured object by the moving mechanism, projecting laser to the surface of the measured object, and traversing the whole surface of the measured object.
And 5, in the moving process, simultaneously calculating the lengths of the visible laser lines by all the cameras, carrying out real-time three-dimensional reconstruction on the laser lines by two cameras with the longest common visible laser line according to internal and external parameters and shot laser line images, and converting the three-dimensional data into a unified coordinate system according to the internal and external parameters of all the cameras.
And 6, when the two cameras with the longest common visible laser lines change, replacing the two cameras with the longest common visible laser lines by a new group of cameras for calculation, and converting the three-dimensional data into a unified coordinate system.
And 7, comparing the acquired three-dimensional data with the three-dimensional model of the measured object, finding out the area with data missing, moving the line laser to scan the area, and repeating the three-dimensional reconstruction step until complete data is acquired.
Example 2
As a best mode for implementing the invention, the invention comprises a method for detecting the quality of the wide-range surface of the airplane, which comprises the following steps:
step 1, building a large-range multi-camera surface quality detection system, referring to the attached figure 2 of the specification, wherein the system comprises a plurality of cameras with fixed positions and a line laser driven by a motion mechanism. The set of all camera fields of vision can cover the measured object surface, and just arbitrary point on measured object surface all is visible to two at least cameras. Each camera is respectively provided with a data line and a synchronous signal line which are connected with the control system, the data line is used for transmitting the shot pictures, and the synchronous line is used for transmitting the trigger signals, so that all the cameras can shoot synchronously. Each camera has a simple calculation function, and can perform simple image processing. The camera lens is fitted with a filter having the same frequency as the line laser light to ensure that only light from the laser enters the camera lens.
And 2, sequencing the multiple cameras, wherein the serial numbers of the cameras are 1,2,3, … … i, i +1 and … … N in sequence, so that a sufficiently large public view field is ensured between the cameras with the adjacent serial numbers, and the size of the public view field is more than 1/3 of the view field of a single camera, namely, a region 1/3 in the view field of one camera can be seen by the adjacent cameras. There is a sufficiently large common view between the cameras of the last sequence number and the cameras of the first sequence number, i.e. the sorting is done in a loop-back manner. Wherein the requirements of steps 1 and 2 can be surely fulfilled by increasing the number of cameras.
And step 3, calibrating internal and external parameters of all cameras. The internal parameters are the properties of the lens and the imaging element of the camera to form an internal parameter matrix KiThe external parameters are coordinate system conversion relations between the cameras, and the external parameters of two adjacent cameras are
Figure BDA0003082570060000051
And by changing over the chains
Figure BDA0003082570060000052
And (6) converting. Wherein the external parameters take the camera 1 as a reference, and the conversion relation from the coordinate system of other cameras to the coordinate system of the camera 1 is calculated, and sequentially
Figure BDA0003082570060000053
i is 1,2,3, …, N. The conversion relationship between the camera i and the camera j is
Figure BDA0003082570060000054
And 4, driving the line laser to move around the measured object by the moving mechanism, projecting laser to the surface of the measured object, and traversing the whole surface of the measured object. The movement mechanism is mainly a gantry mechanism and a robot, and can also be held by a hand to perform supplementary scanning at the position which cannot be covered by the movement mechanism.
Step 5, in the motion process, all cameras simultaneously calculate the lengths of the visible laser lines, and the calculation method comprises the following steps: setting a brightness threshold value for a camera i, carrying out binarization on an image to enable the pixel of the image position of a laser line to be 1, enabling the pixels at the other positions to be 0, and calculating the longest diameter L of the pixel connected domain of 1iThe specific calculation mode is that drawing a circumscribed rectangle of the connected domain, respectively making four sides of the rectangle tangent with the most prominent points in four directions of the connected domain, rotating the rectangle by taking the center of the rectangle as a rotation center, keeping the constraint of tangency of the four sides in the rotation process, continuously calculating the length of the long side of the rectangle in the process, wherein the length of the longest long side of the rectangle is LiAnd mixing LiAnd feeding back to the control system.
To LiSorting and selectingSelecting the largest and next largest LiCorresponding two cameras i and j. And receiving images of the two cameras, and performing real-time three-dimensional reconstruction on the laser line according to internal and external parameters and the shot images. The concrete mode is as follows:
step 5.1, aligning the base line of the camera according to the internal and external parameters of the camera, and performing the operation of aligning the base line of the camera
Figure BDA0003082570060000061
Of (2)
Figure BDA0003082570060000062
Extracted as the coordinate system of camera i multiplied by
Figure BDA0003082570060000063
Coordinate system multiplication of camera j
Figure BDA0003082570060000064
Wherein camera i and camera j are LiTwo cameras corresponding to the largest and the next largest,
Figure BDA0003082570060000065
converting the coordinate of the camera i and the camera j;
step 5.2, horizontally arranging the converted images of the cameras i and j left and right, wherein the corresponding point of one point P in the images of the cameras i and j in the three-dimensional space is positioned on the same horizontal line;
step 5.3, extracting the center line of the laser line in the image, and selecting a point P on the center line of the laser line in the image of the camera iiFinding out the corresponding point P on the central line of the laser line in the image of the camera j by means of making a horizontal linej；
Step 5.4, setting the world coordinate system coordinate of the point P as PWThe world coordinate system is established under the coordinate system of the camera 1, having
Figure BDA0003082570060000066
Simultaneous solution of PWAnd points on the central line of the laser line can be completely reconstructed in three dimensions in the same way. Wherein, KiIs an internal parameter matrix, K, of camera ijIs the internal parameter matrix of camera j.
And 6, when the two cameras with the longest common visible laser lines change, replacing the two cameras with the longest common visible laser lines by a new group of cameras for calculation, and converting the three-dimensional data into a unified coordinate system.
Step 7, the obtained three-dimensional data P is set as { P ═ P1,p2,p3,…,pnRegistering the three-dimensional model of the measured object with the three-dimensional model of the measured object, wherein the registering mode is that the three-dimensional model of the measured object is dispersed into a point cloud form Q (Q) of point cloud1,q2,q3,…,qnWherein q isiIs piAnd (3) setting a rotation translation matrix T at the closest point in Q, decomposing the rotation translation matrix T into a rotation matrix R and a translation matrix T, and solving R and T which enable the following objective functions to be minimum:
Figure BDA0003082570060000067
converting P to PT＝P·R+t，PTDeleting the point cloud with P in Q for the point cloud with P and Q alignedTThe distance between the points in the three-dimensional reconstruction method is smaller than a threshold value delta, the remaining points are missing areas, the positions of the points are displayed by coordinates of the points, the line laser is moved to the positions of the points, the areas are scanned, and the three-dimensional reconstruction step is repeated until complete data are obtained.
In summary, after reading the present disclosure, those skilled in the art can make various other corresponding changes without creative efforts according to the technical solutions and technical concepts of the present disclosure, which all belong to the protection scope of the present disclosure.

Claims (7)

1. A method for detecting the quality of a large-range surface of an airplane is characterized by comprising the following steps: the method comprises the following steps:
step 1, building a large-range multi-camera surface quality detection system, wherein the system comprises a plurality of cameras with fixed positions, a set of visual fields of all the cameras can cover the surface of a detected object, and any point on the surface of the detected object can be visible to at least two cameras;
step 2, sequencing the multiple cameras to ensure that a sufficiently large public view field exists between the cameras with adjacent serial numbers, and a sufficiently large public view field exists between the camera with the last serial number and the camera with the first serial number; wherein, having enough big public sight specifically indicates between the camera of adjacent serial number: the size of the common field of view should exceed 1/3 for the single camera field of view, i.e., the region 1/3 within one camera field of view can be seen by its neighboring cameras; there is enough big public view between the camera of last serial number and the camera of first serial number, specifically: the sorting of the cameras is performed in a loop-back manner;
step 3, calibrating internal and external parameters of all cameras;
step 4, driving the line laser to move around the measured object by the moving mechanism, projecting laser to the surface of the measured object, and traversing the whole surface of the measured object;
step 5, in the moving process, all cameras simultaneously calculate the lengths of the visible laser lines, and two cameras with the longest common visible laser line perform real-time three-dimensional reconstruction on the laser line according to internal and external parameters and the shot laser line image, and convert the three-dimensional data into a unified coordinate system according to the internal and external parameters of all the cameras;
step 6, when the two cameras with the longest common visible laser lines change, the two cameras with the longest common visible laser lines are replaced by a new group of cameras for calculation, and the three-dimensional data are converted into a unified coordinate system in the same way;
and 7, comparing the obtained three-dimensional data with the three-dimensional model of the measured object, finding out the area with data missing, moving the line laser to scan the area, and repeating the three-dimensional reconstruction step until complete data is obtained.
2. The method for detecting the quality of the large-scale surface of the airplane as claimed in claim 1, wherein the method comprises the following steps: in the step 5, all the cameras simultaneously calculate the lengths of the visible laser lines, specifically: setting a brightness threshold value for a camera i, carrying out binarization on an image to enable the pixel of the image position of a laser line to be 1, enabling the pixels of the rest positions to be 0, and connecting the pixels which are calculated to be 1Longest diameter L of through domainiAnd mixing LiAnd feeding back to the control system.
3. The method for detecting the quality of the large-scale surface of the airplane as claimed in claim 2, wherein the method comprises the following steps: the longest diameter LiThe calculating method specifically further comprises: drawing a circumscribed rectangle of the connected domain, wherein four sides of the rectangle are tangent to the most prominent points in four directions of the connected domain, rotating the rectangle by taking the center of the rectangle as a rotation center, keeping the constraint of tangency of the four sides in the rotating process, continuously calculating the length of the long side of the rectangle in the rotating process, and the length of the longest long side of the rectangle is Li。
4. The method for detecting the quality of the wide-range surface of the aircraft as claimed in claim 2 or 3, wherein the method comprises the following steps: the two cameras with the longest common visible laser line in the step 5 are specifically: to LiSorting, selecting the largest and next largest LiTwo corresponding cameras.
5. The method for detecting the quality of the large-scale surface of the airplane as claimed in claim 1, wherein the method comprises the following steps: the real-time three-dimensional reconstruction of the laser line in the step 5 specifically includes:
step 5.1, aligning the base line of the camera according to the internal and external parameters of the camera, and performing the operation of aligning the base line of the camera
Figure FDA0003564769010000021
Of (2)
Figure FDA0003564769010000022
Extracted as the coordinate system of camera i multiplied by
Figure FDA0003564769010000023
Coordinate system multiplication of camera j
Figure FDA0003564769010000024
Wherein camera i and camera j are LiTwo of maximum and second maximum correspondenceA camera of the table camera is arranged on the table camera,
Figure FDA0003564769010000025
for the coordinate transformation relationship of camera i and camera j,
Figure FDA0003564769010000026
specifically, the coordinate conversion relation from the camera i to the camera j is obtained;
step 5.2, horizontally arranging the converted images of the cameras i and j left and right, wherein the corresponding point of a point P in the three-dimensional space in the images of the cameras i and j is positioned on the same horizontal line;
step 5.3, the center line of the laser line in the image is extracted, and a point P is selected on the center line of the laser line in the image of the camera iiFinding out the corresponding point P on the central line of the laser line in the image of the camera j by means of making a horizontal linej；
Step 5.4, setting the world coordinate system coordinate of the point P as PWThe world coordinate system is established under the coordinate system of the camera 1 and has Pi＝KiT1 iPw，Pj＝KjT1 jPwSimultaneous solution of PWIn the same way, all points on the central line of the laser line can be reconstructed in three dimensions; wherein, KiIs an internal parameter matrix, K, of camera ijIs the internal parameter matrix, T, of camera j1 iIs a coordinate transformation relationship from the coordinate system of camera i to the coordinate system of camera 1; t is a unit of1 jIs a coordinate conversion relationship from the coordinate system of the camera j to the coordinate system of the camera 1.
6. The method for detecting the quality of the large-scale surface of the airplane as claimed in claim 1, wherein the method comprises the following steps: the step 7 specifically refers to: let three-dimensional data be P ═ P1,p2,p3,…,pnDispersing the three-dimensional model of the measured object into a point cloud form Q ═ Q1,q2,q3,…,qnWherein q isiIs piAt the closest point in Q, a rotational-translation matrix T is set, decomposed intoRotating the matrix R and translating the matrix t, solving R and t that minimize the following objective function:
Figure FDA0003564769010000027
converting P to PT＝P·R+t，PTFor the point cloud after P and Q are aligned, deleting Q and PTThe distance between the points in the three-dimensional reconstruction method is smaller than a threshold value delta, the remaining points are missing areas, the positions of the points are displayed by coordinates of the points, the line laser is moved to the positions of the points, the area is scanned, and the three-dimensional reconstruction step is repeated until complete data are obtained.
7. The method for detecting the quality of the wide-range surface of the aircraft as claimed in claim 1, wherein the method comprises the following steps: and the camera lens is provided with an optical filter with the same luminous frequency as the line laser.
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