Aircraft crash test machine body full-field deformation non-contact measurement system and method

Abstract

The application discloses a kind of aircraft crash test machine body full-field deformation non-contact measurement system and method, belong to aircraft structure strength test technical field, comprising: high-quality speckle pattern is made on the surface of fuselage and is laid cooperation mark point;Using binocular camera flexible self-calibration method completes stereoscopic measurement system calibration;Through unmanned aerial vehicle photogrammetry auxiliary multi-system global coordinate unification;Synchronous controller triggers multiple systems synchronous acquisition crash process image;Based on mark point positioning tracking and stereovision principle obtains key measuring point motion trajectory and speed;Based on control point guided digital image correlation method and stereovision principle obtain full-field three-dimensional displacement field and strain field;Realize deformation visual representation by image stitching and data fusion.The application realizes the non-contact, high-precision, full-field dynamic measurement of three-dimensional deformation field in the whole machine crash process of large aircraft, provides technical support for aircraft structure crashworthiness analysis and evaluation and anti-crash design verification.

Description

Technical Field

[0001] This invention belongs to the field of aircraft structural strength testing technology, and in particular relates to a non-contact measurement system and method for full-field deformation of aircraft fuselage in crash tests. Background Technology

[0002] The crashworthiness of an aircraft's structure is a crucial indicator of its safety. Whole-aircraft crash testing is the most direct method for assessing aircraft crashworthiness and also a global technical challenge in the field of civil aircraft crashworthiness. In whole-aircraft crash tests, accurately measuring the full-field dynamic deformation response of the fuselage structure is essential for evaluating crashworthiness. This deformation data helps analyze the dynamic behavior of different fuselage components and how they absorb and dissipate impact energy during impact, providing core data for calibrating numerical simulation models and improving structural design.

[0003] Currently, structural deformation measurement in aircraft fuselage crash tests primarily relies on traditional contact sensors, including strain gauges and accelerometers. These contact-based measurement systems are cumbersome to set up, have limited measurement points, and struggle to obtain full-field deformation information of the fuselage. Furthermore, during impact, when the structure undergoes large deformation or failure, these contact sensors may detach, resulting in unreliable displacement or acceleration results. Non-contact video measurement technology, due to its advantages such as simple equipment, ease of application, non-contact operation, large range, high precision, dynamic measurement, and full-field three-dimensional measurement, is widely used for measuring the morphology and deformation of large structures such as aircraft, rockets, ships, and civilian infrastructure. However, existing video measurement technology faces the following challenges for high-precision measurement of full-field deformation in large aircraft crash tests: First, there is the problem of large-scale full-field dynamic measurement, as the measurement range of a large aircraft fuselage can reach tens of meters, and a single high-speed stereo vision measurement system cannot meet the requirements; second, there is the problem of large-scale speckle field fabrication, as high-quality speckle fields need to be fabricated over a large area of ​​the structure to achieve high-precision deformation measurement of the fuselage surface; and third, there is the calibration of a large field-of-view video measurement network, including high-precision calibration of the stereo vision measurement system and global calibration of multiple systems. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention proposes a non-contact measurement system and method for full-field deformation of aircraft fuselage in crash tests, thereby resolving the issues present in the prior art.

[0005] To achieve the above objectives, the present invention provides a non-contact measurement method for the full-field deformation of an aircraft fuselage in a crash test, comprising:

[0006] Create speckled patterns on the surface of the aircraft fuselage and place cooperation logos in key locations on the fuselage;

[0007] The internal and relative external parameters of a stereo measurement system composed of multiple pairs of high-speed cameras are calibrated using a flexible self-calibration method with binocular cameras.

[0008] A global calibration method for a multi-camera video measurement network assisted by UAV photogrammetry is used to obtain the absolute extrinsic parameters from the local measurement coordinate system to the world coordinate system of each stereo measurement system based on the intrinsic parameters and relative extrinsic parameters of the stereo measurement system.

[0009] The three-dimensional measurement systems described above are used to simultaneously capture time-series dynamic images of the aircraft whole test component during the crash process;

[0010] Based on the aforementioned time-series dynamic images, the motion trajectory and velocity of key measuring points on the fuselage during the crash are obtained through marker positioning and tracking methods and stereo vision principles.

[0011] Based on the aforementioned time-series dynamic images, the three-dimensional displacement field and three-dimensional strain field of the fuselage throughout the crash process are obtained through the digital image correlation method guided by control points and the principle of stereo vision.

[0012] Based on the matching of absolute external parameters and image features, the time-series dynamic images captured by each of the stereo measurement systems are stitched together, and the motion trajectory, velocity, three-dimensional displacement field and three-dimensional strain field data are mapped to the stitched panoramic image of the fuselage to realize the visualization of the deformation across the entire field.

[0013] Optionally, a speckled pattern may be created on the surface of the aircraft fuselage, including:

[0014] Calculate the speckle particle size based on the measurement conditions and imaging configuration parameters;

[0015] Generate a speckle field pattern having the stated speckle particle size;

[0016] After cleaning and sanding the surface of the aircraft fuselage, a primer is applied.

[0017] On the surface of the primer, a speckle sticker is transferred by water transfer printing or black paint is sprayed onto a PET speckle mask and then the mask is removed to form the speckle pattern.

[0018] Optionally, cooperation logos may be placed in key locations on the fuselage, including:

[0019] Calculate the dimensions of the cooperation mark based on the measurement conditions and imaging configuration parameters;

[0020] Generate a cooperation logo pattern with the stated dimensions;

[0021] Cut out the cooperation logo printed on the self-adhesive sticker and affix it to the key position on the body.

[0022] Optionally, the intrinsic and relative extrinsic parameters of the stereo measurement system composed of multiple pairs of high-speed cameras are calibrated, including:

[0023] The cooperative markers are placed as control points around the aircraft fuselage measurement area and at the key locations to construct a calibration field;

[0024] The stereo measurement system captures images of the control points in the calibration field and obtains the coded ID and coordinates of the central two-dimensional image point of each control point through image processing and cooperative marker positioning and recognition algorithms.

[0025] The initial intrinsic parameters of the camera are solved based on the Kruppa equations. The extrinsic parameters of the linear camera model are solved using epipolar geometry constraints. The intrinsic and extrinsic parameters are then nonlinearly optimized using a bundle adjustment algorithm to obtain the calibrated intrinsic and extrinsic parameters of the stereo measurement system.

[0026] Optionally, obtain the absolute extrinsic parameters from the local measurement coordinate system to the world coordinate system for each stereo measurement system, including:

[0027] A rotary-wing UAV was used to reconstruct the three-dimensional coordinates of all control points in the calibration field in the world coordinate system using photogrammetry.

[0028] Each of the stereo measurement systems acquires images of different control points within its respective field of view;

[0029] Based on the internal parameters and relative external parameters of the calibrated stereo measurement system, the three-dimensional coordinates of the control points in their respective local measurement coordinate systems are reconstructed.

[0030] Using the three-dimensional coordinates of the control points in the world coordinate system and the three-dimensional coordinates in the local measurement coordinate system, the pose transformation relationship from the local measurement coordinate system to the world coordinate system of each stereo measurement system is calculated and used as an absolute external parameter.

[0031] Optionally, time-series dynamic images can be captured simultaneously using various stereo measurement systems, including:

[0032] A synchronization controller is used to control all high-speed cameras in the stereo measurement system to acquire images synchronously, with a synchronization accuracy of less than or equal to 1 microsecond.

[0033] Optionally, obtain the motion trajectory and velocity of key measuring points on the fuselage during the crash, including:

[0034] Based on the marker localization and tracking method, the cooperative marker is identified from the temporal dynamic images captured by the left and right cameras of each stereo measurement system;

[0035] Based on the principle of stereo vision and the intrinsic and relative extrinsic parameters of the calibrated stereo measurement system, the three-dimensional spatial coordinates of each cooperative symbol in each frame of the image are calculated.

[0036] Arrange the three-dimensional spatial coordinates in chronological order to form the motion trajectory of the key measuring points on the fuselage;

[0037] The time series of the three-dimensional spatial coordinates is subjected to mean filtering, and the motion velocity at each moment is calculated using the central difference method.

[0038] Optionally, obtain the three-dimensional displacement field and three-dimensional strain field of the fuselage throughout the impact process, including:

[0039] Based on the digital image correlation method guided by control points, temporal deformation analysis and stereo matching are performed on the speckle images captured by the left and right cameras of each stereo measurement system to achieve sub-pixel fine matching of speckle.

[0040] For successfully matched speckle image points, their three-dimensional coordinates in the object space are reconstructed using the intrinsic and relative extrinsic parameters of the calibrated stereo measurement system based on the principle of stereo vision triangulation.

[0041] The three-dimensional displacement field is obtained by calculating the difference in three-dimensional coordinates of the corresponding speckle before and after deformation.

[0042] The three-dimensional displacement field is subjected to noise reduction and smoothing to obtain a fine displacement field on the fuselage surface.

[0043] The three-dimensional strain field is obtained by spatially differentiating the fine displacement field on the fuselage surface.

[0044] Optionally, the process of achieving a visual representation of the full-field deformation includes:

[0045] Based on the absolute external parameters, the measurement data obtained by each of the three-dimensional measurement systems are uniformly converted to the world coordinate system;

[0046] The SIFT method based on a multi-scale spatial model is used to detect and locate image feature points within the common field of view of adjacent stereo measurement systems;

[0047] Based on the principle that feature points with the same name have the same world coordinates, feature matching between adjacent stereo measurement system images is completed.

[0048] A baseline image is selected, and the images with completed feature matching are stitched and fused to generate a panoramic image of the aircraft fuselage.

[0049] The motion trajectory, velocity, three-dimensional displacement field, and three-dimensional strain field data are mapped onto the panoramic image of the fuselage to generate a comprehensive visualization result that includes the motion trajectory, velocity vector, full-field displacement cloud map, and full-field strain cloud map.

[0050] This invention provides a non-contact measurement system for the full-field deformation of an aircraft fuselage in a crash test, used to perform the aforementioned non-contact measurement method for the full-field deformation of an aircraft fuselage in a crash test, comprising:

[0051] A stereo measurement network consisting of multiple sets of binocular high-speed cameras, a synchronization controller, cooperative markings and speckle patterns arranged on the surface of the aircraft fuselage, a rotary-wing UAV for assisting global calibration, and an image workstation for image processing and data analysis.

[0052] The synchronization controller is used to control all high-speed cameras in the stereo measurement network to acquire data synchronously.

[0053] The stereoscopic measurement network is used to capture time-series dynamic images of the aircraft whole-body test component during the crash process;

[0054] The rotary-wing UAV is used to reconstruct the coordinates of control points in the world coordinate system using photogrammetry.

[0055] The image workstation is used to process the time-series dynamic images and perform the analysis, calculation, and characterization in the measurement method.

[0056] Compared with the prior art, the present invention has the following advantages and technical effects:

[0057] This invention discloses a non-contact measurement system and method for the full-field deformation of an aircraft fuselage in a crash test. The method includes: creating a speckle pattern on the surface of the aircraft fuselage and arranging cooperative markers at key locations on the fuselage; using a flexible self-calibration method with binocular cameras to quickly calibrate the intrinsic and relative extrinsic parameters of each group of stereo measurement systems; using a global calibration method with a multi-camera video measurement network assisted by UAV photogrammetry to obtain the absolute extrinsic parameters from the local measurement coordinate system to the global coordinate system of each group of stereo systems; using a high-speed camera to capture time-series dynamic images of the aircraft test component during the crash test; analyzing and calculating the time-series images based on marker positioning and tracking methods and stereo vision principles to obtain the motion trajectory and velocity of key measurement points on the fuselage during the crash test; analyzing and calculating the time-series images based on control point-guided digital image correlation methods and stereo vision principles to obtain the displacement and strain field of the fuselage during the crash test; and finally, based on global calibration and feature matching, realizing panoramic image stitching of the aircraft fuselage and intuitive representation of the full-field deformation.

[0058] The non-contact measurement method for the full-field deformation of the fuselage in a whole-aircraft crash test provided by this invention solves the problem of non-contact, high-precision, full-field deformation measurement of the three-dimensional deformation of large aircraft, and provides much-needed technical support for the structural crashworthiness analysis, evaluation and crash-resistant design verification of civil aircraft to meet airworthiness requirements. Attached Figure Description

[0059] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0060] Figure 1 This is a schematic diagram of a non-contact measurement system for the full-field deformation of an aircraft fuselage in a crash test, according to an embodiment of the present invention. Detailed Implementation

[0061] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0062] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0063] Example 1

[0064] This embodiment provides a non-contact measurement system and method for the full-field deformation of an aircraft fuselage in a crash test, including:

[0065] S1. High-quality speckle patterns are created on the surface of the fuselage using water transfer printing, spraying, and other methods, and cooperation logos are placed in key positions;

[0066] S2. Achieve high-precision and rapid calibration of the intrinsic and relative extrinsic parameters of a stereo measurement system using a flexible self-calibration method with a binocular camera;

[0067] S3. Use the global calibration method of multi-camera video measurement network assisted by UAV photogrammetry to obtain the absolute external parameters of each group of stereo systems from the local measurement coordinate system to the global coordinate system;

[0068] S4. Use a high-speed camera to capture the time-series dynamic images of the aircraft test component crashing.

[0069] S5. Based on marker positioning and tracking methods and stereo vision principles, analyze and calculate time-series images to obtain the motion trajectory and velocity parameters of key measurement points on the fuselage during the crash.

[0070] S6. Based on control point-guided digital image correlation methods and stereo vision principles, time-series images are analyzed and calculated to obtain fuselage displacement and strain field during the crash.

[0071] S7. Based on global calibration and feature matching, it realizes intuitive representation of panoramic image stitching and full-field deformation of aircraft fuselage.

[0072] The method for producing high-quality speckle patterns and cooperation logos in step S1 includes:

[0073] S11. Calculate the speckle particle size and the dimensions of the cooperative markers (including but not limited to circular diagonals and crosshairs) based on the measurement conditions and imaging configuration parameters;

[0074] S12. Select appropriate parameters to generate the cooperation logo and speckle field pattern;

[0075] S13. Use sandpaper and alcohol test paper to clean the surface of the test aircraft fuselage, and use an automatic spray gun to spray matte white primer onto the fuselage surface.

[0076] S14. After the white primer has solidified and dried, the water transfer printing speckle sticker can be transferred to the surface of the machine body by cutting, splicing and other means, or a PET speckle mask can be covered on the surface of the machine body, black paint can be sprayed on, and the mask can be removed after it dries. Both methods can obtain a uniform and smooth speckle pattern.

[0077] S15. Print the cooperation logo on the self-adhesive sticker, cut it out and stick it to the key position on the body.

[0078] Practical applications show that the speckle patterns produced by this method are of suitable size, uniform density, and strong randomness. They are also convenient and efficient to produce, and can quickly cover all areas of the side of the aircraft fuselage. Clear and high-quality speckle images can be captured by a camera, which improves the reliability and accuracy of digital image correlation methods and fills the technical gap in the production of speckle patterns on the fuselage surface during aircraft crash tests.

[0079] The high-precision and rapid calibration method for the intrinsic and relative extrinsic parameters of the stereo camera in step S2 includes:

[0080] S21. Arrange a certain number of cooperative markers around the measurement area of ​​the aircraft fuselage, and together with the cooperative markers at key locations on the fuselage, use them as control points to establish a calibration field.

[0081] S22. Multiple pairs of high-resolution high-speed cameras are used to form multiple sets of stereo measurement systems, and the measurement area covers the area from the head to the tail of the camera.

[0082] S23. Each group of stereo measurement systems takes pictures of the control points in the calibration field, and obtains the code ID of the marker and the coordinates of the central two-dimensional image point through image processing and cooperative marker positioning and recognition algorithm;

[0083] S24. Solve for the initial values ​​of the camera's intrinsic parameters based on the Kruppa equation, solve for the extrinsic parameters of the linear camera model using epipolar geometry constraints, and perform nonlinear optimization of the intrinsic and extrinsic parameters using the bundle adjustment algorithm to obtain high-precision binocular camera parameters.

[0084] The specific steps of the UAV photogrammetry-assisted global calibration method for multi-camera video measurement networks in step S3 include:

[0085] S31. Reconstruct the global coordinates of all control points in the world coordinate system using UAV photogrammetry;

[0086] S32. Each group of stereo measurement subsystems acquires images of different control points under their respective fields of view;

[0087] S33. Based on the acquired camera intrinsic and extrinsic parameters of each group of stereo measurement subsystems, reconstruct the 3D coordinates of the control points in their respective local measurement coordinate systems;

[0088] S34. Use control points to establish the pose relationship between the local measurement coordinate system and the global coordinate system of each group of three-dimensional systems, so that the measurement data of each group of subsystems can be unified into the global coordinate system.

[0089] Step S4, which involves capturing time-series images of the aircraft crash using a high-speed camera, includes:

[0090] S41. A synchronous controller is used to control four cameras to synchronously acquire time-series images of the entire machine during the crash, with a synchronization accuracy of ≤1 microsecond.

[0091] The specific methods for analyzing the motion trajectory and velocity of key measuring points on the fuselage during the crash test of the aircraft whole-body test piece in step S5 include:

[0092] S51. Based on the marker positioning and tracking method and the principle of stereo vision, analyze and calculate the images of the aircraft fuselage before and after deformation captured by the left and right cameras in each group of stereo measurement systems to obtain the three-dimensional spatial coordinates of the key measurement points of the fuselage during the whole aircraft crash process.

[0093] S52. Arrange the three-dimensional coordinates of the markers in each frame of the image in chronological order to form time series data, and then the motion trajectory of the key measuring points can be reconstructed.

[0094] S53. Given the time-series dynamic three-dimensional coordinates of key fuselage measurement points during the crash process, first perform mean filtering, taking the average value of the data within the sliding window to remove outliers and fill in missing data, then use central difference to calculate the motion velocity of the measurement points at time k as follows:

[0095] (1)

[0096] in, and The coordinates of the measurement point at time k-1 and k+1 are represented, respectively. F represents the camera frame rate, and 1 / F represents the time interval between adjacent frames of the high-speed camera. The calculated velocity is further filtered to ensure smoothness and accuracy.

[0097] The specific methods for analyzing the fuselage displacement and strain field during the crash in step S6 include:

[0098] S61. For the speckle images of the aircraft fuselage before and after deformation captured by the left and right cameras in each group of stereo measurement systems, feature point temporal deformation images and stereo matching are performed based on the digital image correlation method guided by control points. First, the area contained in the circumscribed rectangle of the cooperative marker (control point) is approximated as a finite plane. Using the image point coordinates of the center of the marker and the four vertices of the circumscribed rectangle, the homography transformation matrix of the image grid region where it is located is calculated to provide accurate initial values ​​for speckle matching. Finally, the improved least squares template matching algorithm is used to achieve sub-pixel fine matching based on the correlation function in formula (2).

[0099] (2)

[0100] In the formula: The gray value of any point in the reference image sub-region; The gray value of any point in the reference sub-region corresponds to the gray value of the corresponding point in the target image; u and v represent the coordinate differences between the centers of the two sub-regions in the x and y directions, respectively.

[0101] S62. For successfully matched speckle points in a binocular stereo image, the object-space 3D coordinates of the speckle can be reconstructed using the calibrated intrinsic and extrinsic parameters of the stereo camera, based on the principle of stereo vision triangulation. Assume... and These are the projection matrices of the two cameras, respectively. and Then, the corresponding image coordinates are obtained. Then, using the least squares algorithm, the object coordinates X of the point are obtained, as shown in equation (3).

[0102] (3)

[0103] in:

[0104] (4)

[0105] (5)

[0106] S63. By subtracting the three-dimensional coordinates of the corresponding speckle points before and after deformation, the three-dimensional displacement can be obtained:

[0107] (6)

[0108] in, ( , , )and ( , , The numbers ) represent the time t0 at the initial stationary moment and t during the impact, respectively. i The three-dimensional coordinates at any given time in the global coordinate system.

[0109] S64. The original displacement field information obtained above is used to perform noise reduction processing by comprehensively utilizing methods such as finite element smoothing and thin plate splines to obtain detailed displacement field data of the wing surface.

[0110] S65. The displacement field is differentiated by a highly accurate local polynomial least squares fitting method to obtain a high-precision three-dimensional spatial strain field.

[0111] The specific steps of step S7 include:

[0112] S71. A global calibration method for multi-camera systems based on UAV photogrammetry assistance is used to obtain the transformation relationship between the local coordinate system of each single-station camera and the global world coordinate system, and to unify the coordinates of the deformation measurement data across the entire field.

[0113] S72. The SIFT method based on a multi-scale spatial model is used to detect and locate features within the common field of view of adjacent binocular stations;

[0114] S73. Based on the principle that the world coordinates of the same feature points are the same, extract the same image points from the two images of adjacent stations to complete the matching;

[0115] S74. After feature point matching is completed for images collected from different stations, one image is selected as the reference image, and the other image is stitched together with it;

[0116] S75. Merge multiple images with overlapping areas into a single image with a larger field of view to obtain a panoramic image of the fuselage;

[0117] S76. Visualize the calculated displacement and strain field data to obtain the full-field displacement and strain cloud maps of the fuselage during the crash process.

[0118] like Figure 1 As shown, the non-contact measurement system for the full-field deformation of the fuselage in a whole-aircraft crash test provided in this embodiment includes: a distributed camera measurement network consisting of multiple sets of high-speed cameras, an image workstation, a network switch, a synchronization trigger, specific markers, and a rotary-wing UAV. This measurement device can perform the non-contact measurement method for the full-field motion and deformation of the fuselage in a whole-aircraft crash test as covered in this embodiment of the invention.

[0119] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A non-contact measurement method for the full-field deformation of an aircraft fuselage in a crash test, characterized in that, Includes the following steps: Create speckled patterns on the surface of the aircraft fuselage and place cooperation logos in key locations on the fuselage; The internal and relative external parameters of a stereo measurement system composed of multiple pairs of high-speed cameras are calibrated using a flexible self-calibration method with binocular cameras. The intrinsic and relative extrinsic parameters of a stereo measurement system consisting of multiple pairs of high-speed cameras are calibrated, including: The cooperative markers are placed as control points around the aircraft fuselage measurement area and at the key locations to construct a calibration field; The stereo measurement system captures images of the control points in the calibration field and obtains the coded ID and coordinates of the central two-dimensional image point of each control point through image processing and cooperative marker positioning and recognition algorithms. The initial values ​​of the camera's intrinsic parameters are obtained by solving the Kruppa equations, the extrinsic parameters of the linear camera model are obtained by using epipolar geometry constraints, and the intrinsic and extrinsic parameters are nonlinearly optimized by the bundle adjustment algorithm to obtain the calibrated intrinsic and extrinsic parameters of the stereo measurement system. A global calibration method for a multi-camera video measurement network assisted by UAV photogrammetry is used to obtain the absolute extrinsic parameters from the local measurement coordinate system to the world coordinate system of each stereo measurement system based on the intrinsic parameters and relative extrinsic parameters of the stereo measurement system. Obtain the absolute external parameters from the local measurement coordinate system to the world coordinate system for each stereo measurement system, including: A rotary-wing UAV was used to reconstruct the three-dimensional coordinates of all control points in the calibration field in the world coordinate system using photogrammetry. Each of the stereo measurement systems acquires images of different control points within its respective field of view; Based on the internal parameters and relative external parameters of the calibrated stereo measurement system, the three-dimensional coordinates of the control points in their respective local measurement coordinate systems are reconstructed. Using the three-dimensional coordinates of the control points in the world coordinate system and the three-dimensional coordinates in the local measurement coordinate system, the pose transformation relationship from the local measurement coordinate system to the world coordinate system of each stereo measurement system is calculated and used as an absolute external parameter. The three-dimensional measurement systems described above are used to simultaneously capture time-series dynamic images of the aircraft whole test component during the crash process; Simultaneous capture of time-series dynamic images using various stereo measurement systems, including: A synchronization controller is used to control all high-speed cameras in the stereo measurement system to acquire images synchronously, with a synchronization accuracy of less than or equal to 1 microsecond. Based on the aforementioned time-series dynamic images, the motion trajectory and velocity of key measuring points on the fuselage during the crash are obtained through the marker positioning and tracking method and the principle of stereo vision. Obtain the trajectory and velocity of key measuring points on the fuselage during the crash, including: Based on the marker localization and tracking method, the cooperative marker is identified from the temporal dynamic images captured by the left and right cameras of each stereo measurement system; Based on the principle of stereo vision and the intrinsic and relative extrinsic parameters of the calibrated stereo measurement system, the three-dimensional spatial coordinates of each cooperative symbol in each frame of the image are calculated. Arrange the three-dimensional spatial coordinates in chronological order to form the motion trajectory of the key measuring points on the fuselage; The time series of the three-dimensional spatial coordinates is subjected to mean filtering, and the motion velocity at each moment is calculated using the central difference method; Based on the aforementioned time-series dynamic images, the three-dimensional displacement field and three-dimensional strain field of the fuselage throughout the crash process are obtained through the digital image correlation method guided by control points and the principle of stereo vision. Based on the matching of absolute external parameters and image features, the time-series dynamic images captured by each of the stereo measurement systems are stitched together, and the motion trajectory, velocity, three-dimensional displacement field and three-dimensional strain field data are mapped to the stitched panoramic image of the fuselage to realize the visualization of the deformation in the whole field. The process of visualizing the full-field deformation includes: Based on the absolute external parameters, the measurement data obtained by each of the three-dimensional measurement systems are uniformly converted to the world coordinate system; The SIFT method based on a multi-scale spatial model is used to detect and locate image feature points within the common field of view of adjacent stereo measurement systems; Based on the principle that feature points with the same name have the same world coordinates, feature matching between adjacent stereo measurement system images is completed. A baseline image is selected, and the images with completed feature matching are stitched and fused to generate a panoramic image of the aircraft fuselage. The motion trajectory, velocity, three-dimensional displacement field, and three-dimensional strain field data are mapped onto the panoramic image of the fuselage to generate a comprehensive visualization result that includes the motion trajectory, velocity vector, full-field displacement cloud map, and full-field strain cloud map.

2. The non-contact measurement method for full-field deformation of aircraft fuselage in a crash test according to claim 1, characterized in that, Creating speckled patterns on the surface of the aircraft fuselage, including: Calculate the speckle particle size based on the measurement conditions and imaging configuration parameters; Generate a speckle field pattern having the stated speckle particle size; After cleaning and sanding the surface of the aircraft fuselage, a primer is applied. On the surface of the primer, a speckle sticker is transferred by water transfer printing or black paint is sprayed onto a PET speckle mask and then the mask is removed to form the speckle pattern.

3. The non-contact measurement method for full-field deformation of aircraft fuselage in a crash test according to claim 1, characterized in that, The cooperation logo will be placed in key locations on the fuselage, including: Calculate the dimensions of the cooperation marker based on the measurement conditions and imaging configuration parameters; Generate a cooperation logo pattern with the stated dimensions; Cut out the cooperation logo printed on the self-adhesive sticker and affix it to the key position on the body.

4. The non-contact measurement method for full-field deformation of aircraft fuselage in a crash test according to claim 1, characterized in that, Obtain the three-dimensional displacement field and three-dimensional strain field of the fuselage throughout the impact process, including: Based on the digital image correlation method guided by control points, temporal deformation analysis and stereo matching are performed on the speckle images captured by the left and right cameras of each stereo measurement system to achieve sub-pixel fine matching of speckle. For successfully matched speckle image points, their three-dimensional coordinates in the object space are reconstructed using the intrinsic and relative extrinsic parameters of the calibrated stereo measurement system based on the principle of stereo vision triangulation. The three-dimensional displacement field is obtained by calculating the difference in three-dimensional coordinates of the corresponding speckle before and after deformation. The three-dimensional displacement field is subjected to noise reduction and smoothing to obtain a fine displacement field on the fuselage surface. The three-dimensional strain field is obtained by spatially differentiating the fine displacement field on the fuselage surface.

5. A non-contact measurement system for the full-field deformation of an aircraft fuselage in a crash test, characterized in that, A method for performing a non-contact measurement of full-field deformation of an aircraft fuselage in a crash test as described in any one of claims 1 to 4, comprising: A stereo measurement network consisting of multiple sets of binocular high-speed cameras, a synchronization controller, cooperative markings and speckle patterns arranged on the surface of the aircraft fuselage, a rotary-wing UAV for assisting global calibration, and an image workstation for image processing and data analysis. The synchronization controller is used to control all high-speed cameras in the stereo measurement network to acquire data synchronously. The stereoscopic measurement network is used to capture time-series dynamic images of the aircraft whole-body test component during the crash process; The rotary-wing UAV is used to reconstruct the coordinates of control points in the world coordinate system using photogrammetry. The image workstation is used to process the time-series dynamic images and perform the analysis, calculation, and characterization in the measurement method.

Images