An ultra-high-precision deformation measurement method based on industrial photogrammetry

Abstract

The present invention relates to an ultra-high-precision deformation measurement method based on industrial photogrammetry, which can effectively solve the problem in the prior art that when manually holding a camera for multiple groups of repeated shootings, the difference in the shooting positions and postures is large, that is, the consistency of the measurement network is poor, resulting in a reduction in the accuracy of industrial photogrammetry deformation measurement. The technical solution it adopts is that the measurement method includes the following steps: 1) arranging marking points on the object to be measured; 2) calculating the consistency of the measurement network; 3) ultra-high-precision deformation measurement; The present invention uses a mechanical device to control the camera for shooting, so that when each group of cameras shoots, it reaches a high degree of consistency in the same position and the same posture, improves the accuracy of the network consistency, and thus achieves the effect of ultra-high-precision deformation measurement in industrial photogrammetry. Using the method of the present invention, the influence of the network shape on the measurement accuracy is significant, which is an innovation in the high-precision deformation measurement method.

Description

Technical Field

[0001] The present invention relates to the technical field of digital close-range industrial photogrammetry, and particularly to an ultra-high-precision deformation measurement method based on industrial photogrammetry. Background Art

[0002] Generally, the measurement accuracy of domestic space telescope trusses or large-sized spacecraft structural components within a space range of (6m×5m×5m) reaches within 5μm. At present, the measurement repeatability accuracy (RMS) of industrial photogrammetry systems at home and abroad within a large-sized space range is about 15μm or even lower. Therefore, in this context, it is urgent to improve the accuracy of industrial photogrammetry systems. To complete high-precision deformation measurement projects for space telescope trusses or large-sized spacecraft structural components, research and improvement need to be carried out in aspects such as the hardware equipment, software algorithms, and measurement methods of industrial photogrammetry systems.

[0003] In previous studies on industrial photogrammetry network patterns, many scholars have conducted a large number of studies and drawn many conclusions. For example, when the accuracy of image point coordinates is the same, different layouts of the measurement network pattern can result in a difference in measurement accuracy of even 10 times. These are all to improve the measurement accuracy by improving the number of camera stations and photo overlap, photography distance and intersection angle, and the size and distribution of fiducial points in the measurement network pattern. The problems of the above-mentioned factors affecting the accuracy of the final measurement result by changing the measurement network pattern are attributed to the quality of the measurement network pattern, which is measured by the standard deviation of the coordinates of the measured target points. According to its ability to resist errors, the quality of the measurement network pattern is called the robustness of the measurement network pattern. The better the robustness of the measurement network pattern, the higher the quality of the measurement network pattern, and the better the accuracy of the final measurement result. Since deformation measurement mainly measures the precision between multiple shooting results of a single project, the measurement repeatability accuracy in industrial photogrammetry is generally selected as the accuracy evaluation index. The quality of the measurement repeatability accuracy is not only related to the robustness of the measurement network pattern but also greatly related to the characterization quantity of the difference degree between measurement network patterns during multiple measurements. The characterization quantity of the difference between two measurement network patterns is called the consistency of the network pattern.

[0004] The measurement network shape of industrial photogrammetry has a significant impact on the measurement accuracy, and the measurement network shape can be described from two aspects: the robustness and consistency of the network shape. As an essential step in industrial photogrammetry, the consistency of the measurement network shape is often easily overlooked in actual engineering. In the measurement practice, when personnel hold the camera to take measurements, it is generally impossible to ensure that the exterior orientation element parameters are exactly the same between two measurement processes. Only by trying to ensure that they are within a certain acceptable range of variation can the accuracy be reduced, resulting in a loss of necessary precision. Although many scholars have conducted a large number of studies on the measurement network shape of industrial photogrammetry systems, there is still no attention paid to the research on the consistency of the measurement network shape. Therefore, when the network shape is robust, maintaining the highest possible network shape consistency can significantly improve the measurement repeatability accuracy, thereby improving the resolution of deformation measurement. Achieving the goal of ultra-high-precision deformation measurement is a technical problem that urgently needs to be solved at present. Summary of the Invention

[0005] In view of the above situation, to solve the defects of the prior art, the purpose of the present invention is to provide an ultra-high-precision deformation measurement method based on industrial photogrammetry, which can effectively solve the problem in the prior art that when manually holding a camera for multiple groups of repeated shootings, the pose difference of the shooting positions is large, that is, the consistency of the measurement network shape is poor, resulting in a reduction in the deformation measurement accuracy of industrial photogrammetry.

[0006] The technical solution solved by the present invention is that the measurement method includes the following steps:

[0007] 1) Layout of fiducial points on the object to be measured: Ensure that each set fiducial point is photographed by at least two or more camera stations during measurement. All camera stations, fiducial points, and photographic rays form a reticular structure of several triangles, constituting the industrial photogrammetry network shape;

[0008] 2) Calculate the consistency of the measurement network shape: Preset the position and attitude of the camera, and input the position and attitude of the preset camera into the controller of the high-precision repetitive positioning and orientation shooting device through instructions, so that the high-precision repetitive positioning and orientation shooting device controls the camera to move and rotate for shooting according to the preset position and attitude. Among them, the camera attitude has a total of 6 degrees of freedom (6DOF), that is, the displacement parameters X, Y, Z of three degrees of freedom and the spatial rotation parameters ω, κ (in industrial photogrammetry, the consistency of the measurement network shape is mainly reflected by the attitudes of the cameras at the same positions between groups. The better the consistency of the network shape, the more consistent the attitude parameters of the cameras at the same positions between groups, and its statistical results directly reflect the repeatability and stability of the measurement network shape consistency). Through multiple groups of shooting operations, the consistency of the measurement network shape can be calculated. The smaller the value of the 6-degree-of-freedom parameter obtained, the better the consistency of the measurement network shape; conversely, the worse the consistency of the measurement network shape.

[0009] 3) Ultra-high-precision deformation measurement: Select the optimal measurement network pattern in step 2), and control the position and degrees of freedom attitude of the measurement camera through the moving track, lead screw guide, and rotary table of the high-precision repetitive positioning and orientation shooting device. Input the position and attitude of the camera into the controller of the high-precision repetitive positioning and orientation shooting device in the form of instructions, so that the controller controls the camera to move and rotate for shooting according to the preset position and attitude. Since the high-precision repetitive positioning and orientation shooting device has high repetitive positioning and orientation accuracy, a high network pattern consistency accuracy can be achieved, thus realizing the purpose of ultra-high-precision deformation measurement in industrial photogrammetry.

[0010] The present invention controls the camera to take pictures by a mechanical device, enabling it to achieve a high degree of consistency in the same position and the same attitude during the shooting of each group of cameras, improving the network pattern consistency accuracy, and thus achieving the effect of ultra-high-precision deformation measurement in industrial photogrammetry. Using the method of the present invention to measure the network pattern has a significant impact on the measurement accuracy, which is an innovation in high-precision deformation measurement methods and measurement devices. Brief Description of the Drawings

[0011] Figure 1 It is a flowchart of the operation of the present invention.

[0012] Figure 2 It is a schematic diagram of the industrial photogrammetry network pattern of the present invention.

[0013] Figure 3 It is a diagram showing the difference in the measurement network pattern of the present invention.

[0014] Figure 4 It is a front view of the structure of the high-precision repetitive positioning and orientation shooting device of the present invention.

[0015] Figure 5 It is a side view of the structure of the high-precision repetitive positioning and orientation shooting device of the present invention.

[0016] Figure 6 It is a top view of the structure of the high-precision repetitive positioning and orientation shooting device of the present invention.

[0017] Figure 7 It is a schematic diagram of the bracket structure of the high-precision repetitive positioning and orientation shooting device of the present invention.

[0018] Figure 8 It is a schematic diagram of the support frame structure of the high-precision repetitive positioning and orientation shooting device of the present invention.

[0019] Figure 9 It is a diagram showing the network pattern shooting controlled by the high-precision repetitive positioning and orientation shooting device of the present invention.

[0020] Figure 10 It is a diagram of manual shooting with a strictly fixed position of the present invention.

[0021] Figure 11This is the result graph of the measurement repeatability accuracy of the present invention. Detailed implementation manners

[0022] The following further elaborates in detail on the specific implementation manners of the present invention in conjunction with the accompanying drawings and embodiments.

[0023] Embodiment 1

[0024] When the present invention is specifically implemented, it includes the following steps:

[0025] 1) Layout fiducial points on the object to be measured: Ensure that each fiducial point set is photographed by at least two or more cameras during measurement. All cameras, fiducial points, and photographic rays form a reticular structure of several triangles, constituting an industrial photogrammetry network pattern;

[0026] 2) Calculate the consistency of the measurement network pattern: Preset the position and attitude of the camera, and input the preset position and attitude of the camera into the controller of the high-precision repeat positioning and orientation shooting device in the form of instructions, so that the high-precision repeat positioning and orientation shooting device controls the camera to move and rotate for shooting according to the preset position and attitude;

[0027] Among them, the camera attitude has a total of 6 degrees of freedom (6DOF), that is, three displacement parameters X, Y, Z of the degrees of freedom and three spatial rotation parameters ω, κ. In industrial photogrammetry, the consistency of the measurement network pattern is mainly reflected by the attitudes of the cameras at the same position among groups. The better the consistency of the network pattern, the more consistent the attitude parameters of the cameras at the same position among groups, and its statistical results directly reflect the repeatability and stability of the measurement network pattern consistency. Through multiple groups of shooting operations, the consistency of the measurement network pattern can be calculated, and the calculation is as follows: First, perform m groups of repeated measurements on the same target under the same measurement network pattern, and collect n images each time. The exterior orientation elements of each image are respectively represented as X ij 、Y ij 、Z ij 、 ω ij 、κ ij , where i = 1, 2,..., m; j = 1, 2,..., n.

[0028] Secondly, find the absolute values of the differences in exterior orientation elements among the m groups, a total of data, which are respectively represented as ΔX uj 、ΔY uj 、ΔZ uj 、 Δω uj 、Δκ uj , where

[0029] Then, calculate the standard deviation of the absolute value of the difference in exterior orientation elements among n photos:

[0030]

[0031]

[0032]

[0033]

[0034]

[0035]

[0036] Among them, RMS represents the standard deviation.

[0037] Finally, calculate the average value of the standard deviations of the exterior orientation elements of u groups according to Formulas (2-1) to (2-6):

[0038]

[0039]

[0040]

[0041]

[0042]

[0043]

[0044] Among them,

[0045] The data obtained from Formulas (2-7) to (2-12) reflects the degree of consistency of the measurement network in industrial photogrammetry. Similar to the evaluation of measurement repeatability accuracy, the smaller the value of the 6-degree-of-freedom parameter obtained, the better the consistency of the measurement network. Conversely, the worse the consistency of the measurement network.

[0046] 3) Ultra-high-precision deformation measurement: Select the optimal measurement network in step 2), and control the position and degrees-of-freedom attitude of the measurement camera by moving the track, lead screw guide, and rotating turntable of the high-precision repetitive positioning and orientation shooting device. Input the position and attitude of the camera into the controller of the high-precision repetitive positioning and orientation shooting device by means of instructions, so that the controller controls the camera to move and rotate for shooting according to the preset position and attitude. Since the high-precision repetitive positioning and orientation shooting device has relatively high repetitive positioning and orientation accuracy, a relatively high network consistency accuracy can be achieved, thus realizing the purpose of ultra-high-precision deformation measurement in industrial photogrammetry.

[0047] To ensure the use effect, the measurement camera performs photogrammetry on the calibration field according to a 5×5 measurement grid with a total of 25 camera stations.

[0048] The high-precision repetitive positioning and pose shooting device includes a bracket. The bracket 1 is a square bracket formed by sequentially connecting four square frames. Moving tracks 2 are provided on both the top frame and the bottom frame of the square bracket. A hollow cuboid support frame 3 perpendicular to the top frame and the bottom frame is provided between the moving tracks 2 of the top frame and the bottom frame. A lead screw guide 10 is installed on the support frame 3. A pan / tilt adapter plate 4 is installed on the lead screw guide 10. A rotary turntable 5 is installed on the pan / tilt adapter plate 4. A camera 7 is fixed on the rotary turntable 5. The moving tracks 2 and the lead screw guide 10 are both connected to motors, and the motors and the rotary turntable 5 are both connected to a controller.

[0049] The camera is a CIM-3 camera.

[0050] The controller is a PLC programmable logic controller.

[0051] The controller is a TC55 programmable controller.

[0052] The exposure time of the camera is 600 / μs, the exposure intensity is 7, the resolution is 29 / Mb, and the nominal accuracy is 4μm + 4ppm·L.

[0053] The four square frames consist of two long and two short ones to form a rectangular bracket.

[0054] The rotary turntable is fixed to the camera via a mounting plate 6.

[0055] Connecting plates 9 are provided at the top and bottom of the support frame 3. Pulleys 8 are installed on the connecting plates 9, and the pulleys 8 are clamped in the slide rails of the moving tracks 2.

[0056] Both ends of the lead screw guide 10 are installed on the connecting plates 9 at the top and bottom of the support frame 3 and are perpendicular to the connecting plates 9.

[0057] During use, the camera is fixed on the rotary turntable through the mounting plate. The rotary turntable is connected to the longitudinal support frame through the pan-tilt adapter plate. The longitudinal support frame is connected to the moving tracks on the top frame and the bottom frame. A lead screw guide rail is installed on the support frame. The moving tracks, the lead screw guide rail, and the rotary turntable respectively control the position and attitude changes of the measurement camera. The control software set in the controller controls the moving tracks and the rotary turntable to make the camera perform high-precision repeated shooting at the positions arranged between groups according to the preset instructions. The specific steps are as follows: 1) Make the cameras on the rotary turntable and the moving tracks return to the initial position through the control software of the controller; 2) The controller controls the moving track to move the camera horizontally (vertically) to the preset position; 3) The controller rotates the camera in space by controlling the rotary turntable; 4) After the camera goes through the above steps, it takes pictures at each preset pose; 5) After each group of pictures is taken by the camera, the controller controls the rotary turntable and the moving track to make the camera return to the initial position.

[0058] The high-precision repeated positioning and pose shooting device of the present invention replaces manual hand-held camera shooting, realizing automatic shooting in the field of industrial photogrammetry; at the same time, it avoids the problem that the measurement repeatability accuracy is reduced due to the inconsistent positions and postures of the camera between multiple repeated shootings caused by manual shooting, controls the camera to perform high-precision repeated shooting at the same position and the same posture between multiple groups, effectively improves the repeatability accuracy of industrial photogrammetry, has good use effect and strong practicability.

[0059] Through experiments, the present invention finds that the quality of the industrial photogrammetry network has a direct impact on the measurement accuracy. On the premise of ensuring excellent robustness of the measurement network, maintaining high consistency of the measurement network can greatly improve the measurement accuracy, and using mechanical devices can improve the repeat accuracy of the camera pose more than manual shooting, so as to achieve ultra-high-precision deformation measurement in industrial photogrammetry. To verify this conclusion, taking the measurement repeatability accuracy as the evaluation index, the consistency of the measurement network was tested under laboratory conditions. The test results show that the high consistency of the measurement network improves the measurement accuracy by at least more than 2 times compared with the random network, and the measurement repeatability accuracy (RMS) in the large-size space range is between 3-5 μm, providing data support for improving the deformation measurement accuracy of space telescopes or large-size spacecraft structural components. The relevant test data are as follows:

[0060] I. Robustness and Consistency of the Measurement Network of the Present Invention

[0061] In terms of geometry, for the industrial photogrammetry network, each camera station position and the fiducial points (object points) on the object to be measured can be regarded as a point. During measurement, each fiducial point should be photographed by at least two or more camera stations. If all the photographic rays are drawn on the drawing paper, then all the camera stations, fiducial points, and photographic rays form a reticular structure composed of several triangles, as Figure 1As shown in the figure, it is called the industrial photogrammetry network configuration in surveying and mapping science.

[0062] The present invention is measured by the quality of the measurement network configuration and the standard deviation of the coordinates of the measured target points. Because of its ability to resist errors, the present invention refers to the quality of the measurement network configuration as the robustness of the measurement network configuration. The better the robustness of the measurement network configuration, the higher the quality of the measurement network configuration, and the better the accuracy of the final measurement result (the standard deviation of the coordinates of the measured target).

[0063] Since deformation measurement mainly measures the precision between the multiple shooting results of a single project, the present invention selects the measurement repeatability accuracy in industrial photogrammetry as the accuracy evaluation index. The quality of the measurement repeatability accuracy is not only related to the robustness of the measurement network configuration, but also has a great relationship with the characterization quantity of the difference degree of the measurement network configuration between multiple measurements. Therefore, the characterization quantity of the difference between the two measurement network configurations is called the consistency of the network configuration.

[0064] The measurement repeatability accuracy requires measurement under the same measurement network configuration. However, in actual measurement work, when a person holds an industrial camera for measurement, it is impossible to ensure that the external orientation element parameters (X, Y, Z, ω, κ) are exactly the same between the two measurement processes, and only try to ensure that they are within a certain acceptable range of variation. As Figure 2 shown, in actual engineering, the camera stations A1, A2, A3, A4 and the camera stations all perform the same measurement operation on the measured target to obtain its measurement repeatability accuracy. However, strictly speaking, these measurement results no longer meet the requirements of the same measurement network configuration required by the repeatability accuracy. Therefore, the measurement results obtained will deteriorate to a certain extent.

[0065] Since the measurement network configuration will affect the value of the final measurement result, which indicates that the measurement method will affect the measured result, it is more scientific to ensure the consistency of the measurement network configuration when measuring the repeatability accuracy. In this case, the measured repeatability accuracy will also be significantly improved. Therefore, the present invention adopts mechanical control of the camera attitude.

[0066] II. Index for evaluating the consistency accuracy of the network configuration of the present invention

[0067] The camera attitude has a total of 6 degrees of freedom (6DOF), that is, three degrees of freedom of displacement parameters (X, Y, Z) and three degrees of freedom of spatial rotation parameters ( ω, κ). In industrial photogrammetry, the consistency of the measurement network is mainly reflected by the poses of the cameras at the same positions among different groups. The better the consistency of the network, the more consistent the pose parameters of the cameras at the same positions among different groups, and its statistical result directly reflects the repeatability and stability of the measurement network consistency. The calculation is as follows: First, under the same measurement network, the same target is measured repeatedly for m groups, and n images are collected each time. The exterior orientation elements of each image are respectively represented as X ij 、Y ij 、Z ij 、 ω ij 、κ ij , where (i = 1, 2, …, m; j = 1, 2, …, n).

[0068] Secondly, find the absolute values of the differences in exterior orientation elements among the m groups, a total of data, which are respectively represented as ΔX uj 、ΔY uj 、ΔZ uj 、 Δω uj 、Δκ uj , where

[0069] Then, find the standard deviation of the absolute values of the differences in exterior orientation elements among the n images:

[0070]

[0071]

[0072]

[0073]

[0074]

[0075]

[0076] Among them, RMS represents the standard deviation,

[0077] Finally, according to formulas (2-1) to (2-6), find the average value of the standard deviations of the exterior orientation elements of the u groups:

[0078]

[0079]

[0080]

[0081]

[0082]

[0083]

[0084] Among them,

[0085] The data obtained from formulas (2-7) to (2-12) reflect the degree of consistency of the measurement network in industrial photogrammetry. Similar to the evaluation of measurement repeatability accuracy, the smaller the value of the 6-degree-of-freedom parameters obtained, the better the consistency of the measurement network; conversely, the worse the consistency of the measurement network.

[0086] III. Experiments and Results

[0087] 3.1 Devices Used in the Experiments

[0088] To explore the influence of the variation degree between measurement networks on the repeatability accuracy of industrial photogrammetry, the following experiments were designed. Since the robustness of the measurement network corresponds to the accuracy of the measurement results, which is a sufficient condition for repeatability accuracy and has been verified by many experiments, this invention will not conduct tests on it, but only focus on studying the influence of the difference in measurement network consistency on repeatability accuracy under the premise of excellent robustness of the measurement network.

[0089] Due to its limitations, manual measurement cannot guarantee very high network consistency. To further explore the influence of network consistency factors on measurement repeatability accuracy, this invention uses the above-mentioned high-precision repeat positioning and orientation shooting device (as Figure 4 shown), which can control the 6-degree-of-freedom attitude of the measurement camera through the moving track and rotating turntable, and the controller controls the moving track and rotating turntable to make the camera perform high-precision repeated shooting at the positions arranged between groups according to preset instructions. The measurement accuracies of the moving track and rotating turntable are shown in Table 1.

[0090] Table 1 Accuracy of the High-Precision Repeat Positioning and Orientation Shooting Device

[0091]

[0092] The measurement camera uses the CIM-3 industrial measurement camera provided by Zhengzhou Chenwei Technology Co., Ltd. The camera parameters are shown in Table 2:

[0093] Table 2 Camera Setting Parameters

[0094]

[0095] Under laboratory conditions, the consistency of the measurement network is studied using the high-precision repeat positioning and orientation shooting device on the precision calibration field of the measurement camera (as Figure 9 shown).

[0096] 3.2 Test Plan

[0097] This invention uses a mechanically controlled high-precision repetitive positioning and pose-taking device and manual photography to conduct a comparative test on the network form consistency of the precise calibration field of the measurement camera in the laboratory.

[0098] 1. As Figure 9 shown, it is the precise calibration field of the measurement camera and the high-precision repetitive positioning and pose-taking device of this invention. The measurement camera is controlled mechanically to conduct photogrammetry on the calibration field according to the 5×5 measurement network pattern with a total of 25 camera stations in the figure. This measurement mode using the precise pose measurement system of the camera is named Measurement Method Ⅰ.

[0099] 2. As Figure 10 shown, it is the on-site manual photography diagram. Strict red position marks are made on the ground for placing ladders for photography. According to the camera shooting network pattern in the first step, the precise calibration field of the measurement camera is photographed manually in the same way. This measurement mode with strictly fixed positions is named Measurement Method Ⅱ.

[0100] 3. The precise calibration field of the measurement camera is measured according to the 5×5 measurement network pattern, and manual photography is carried out at random positions on the ground without position marks. This measurement mode is named Measurement Method Ⅲ.

[0101] 4. Statistically calculate the 6-degree-of-freedom values of the camera station poses of the three measurement methods, compare them, and obtain the quality of the network form consistency.

[0102] 5. Conduct data processing such as correlation algorithm matching and adjustment on the photos taken by these three measurement methods, obtain the measurement repeatability results, compare them with the 6-degree-of-freedom values of the camera station poses in step 4, and draw a conclusion.

[0103] 3.3 Test Results

[0104] The results of software processing of the photographed photos and statistical calculation of the 6-degree-of-freedom pose values of the measurement cameras among groups of each measurement method through mathematical calculations are shown in the following table:

[0105] Table 3 Comparison of 6-degree-of-freedom pose values of three measurement methods mm

[0106]

[0107] The measurement repeatability accuracy of the three measurement methods is as Figure 11 shown.

[0108] It can be seen from the 6-degree-of-freedom pose values of the measurement cameras statistically among groups in Table 3 that the measurement method of type Ⅰ controlled mechanically in this invention has significantly higher network form consistency accuracy than the measurement methods of types Ⅱ and Ⅲ controlled manually, and from Figure 11It can be seen from the measurement repeatability accuracy results that the higher the consistency of the measurement network shape, the higher its measurement repeatability accuracy. Moreover, the measurement repeatability accuracy of measurement method I is at least twice as high as that of types II and III, or even more. This also reflects from the side that the consistency of the measurement network shape has a significant impact on the measurement repeatability accuracy in the industrial photogrammetry system.

[0109] Proven by laboratory tests, the measurement repeatability accuracy (RMS) of the measurement method and the shooting device of this application in a large-size space range is between 3 - 5 μm, which is higher than the high precision of the existing measurement technology. Therefore, the present invention can be called an ultra-high-precision deformation measurement method, specifically manifested in that it can be improved again on the basis of the high-precision technology in the country. In practical applications, it is improved from 15 μm to within 5 μm, and in the laboratory experiments, it is improved from about 9 μm to about 3 μm.

[0110] IV. Conclusion

[0111] The present invention solves the problem of low deformation measurement accuracy caused by inconsistent poses of multiple shooting cameras in industrial photogrammetry. In the case of excellent network robustness, maintaining as high a network consistency as possible can significantly improve the resolution of deformation measurement and achieve the purpose of high-precision deformation measurement. At the same time, laboratory measurements show that by mechanically controlling the network consistency between multiple measurements, the measurement repeatability accuracy during the measurement of the precise calibration field of the measurement camera is at least twice as high as that of daily manual measurement. The method of the present invention enables the measurement repeatability accuracy (RMS) of the industrial photogrammetry technology in a large-size space range to reach between 3 - 5 μm, achieving the expected effect, providing data and technical support for the high-precision deformation measurement of space telescope trusses or large-size spacecraft structural components, and having good promotion and application value.

[0112] It should be noted that the above is only a preferred embodiment of the present invention, and it is not a limitation to the present invention in any form. Any person skilled in the art, without departing from the scope of the technical solution of the present invention, can make changes or modifications to equivalent embodiments of equivalent changes by using the disclosed technical content, and all fall within the protection scope of the present invention.

Claims

1. A method for ultra-high-precision deformation measurement based on industrial photogrammetry, characterized in that It includes the following steps: 1) Layout fiducial points on the object to be measured: Ensure that each fiducial point set is photographed by at least two or more camera stations during measurement. All camera stations, fiducial points, and photographic rays form a reticular structure of several triangles, constituting the industrial photogrammetry network pattern; 2) Calculate the measurement network form consistency: Preset the position and attitude of the camera, and input the position and attitude of the preset camera into the controller of the high-precision repetitive positioning and pose shooting device through instructions, so that the high-precision repetitive positioning and pose shooting device controls the camera to move and rotate for shooting according to the preset position and attitude; among them, the camera attitude has a total of 6 degrees of freedom, that is, the displacement parameters x, Y, Z of three degrees of freedom and the spatial rotation parameters ω, κ. Through multiple groups of shooting operations, the measurement network form consistency can be calculated; 3) Ultra-high-precision deformation measurement: Select the optimal measurement network pattern in step 2), and control the position and degrees-of-freedom attitude of the measurement camera through the moving track, lead screw guide rail, and rotary table of the high-precision repetitive positioning and orientation shooting device. Input the position and attitude of the camera into the controller of the high-precision repetitive positioning and orientation shooting device by means of instructions, so that the controller controls the camera to move and rotate for shooting according to the preset position and attitude. Since the high-precision repetitive positioning and orientation shooting device has relatively high repetitive positioning and orientation accuracy, a relatively high network pattern consistency accuracy can be achieved, thus realizing the purpose of ultra-high-precision deformation measurement in industrial photogrammetry.

2. The ultra-high-precision deformation measurement method based on industrial photogrammetry according to claim 1, characterized in that It includes the following steps: 1) Layout fiducial points on the object to be measured: Ensure that each fiducial point set is photographed by at least two or more camera stations during measurement. All camera stations, fiducial points, and photographic rays form a reticular structure of several triangles, constituting the industrial photogrammetry network pattern; 2) Calculate the consistency of the measurement network pattern: Preset the position and attitude of the camera, and input the position and attitude of the preset camera into the controller of the high-precision repetitive positioning and pose-taking device through instructions, so that the high-precision repetitive positioning and pose-taking device controls the camera to move and rotate for shooting according to the preset position and attitude; among them, the camera attitude has a total of 6 degrees of freedom, that is, the displacement parameters X, Y, Z of three degrees of freedom and the spatial rotation parameters ω, κ. Through multiple groups of shooting operations, the consistency of the measurement network pattern can be calculated, and the calculation is as follows: First, perform m groups of repeated measurements on the same target under the same measurement network configuration. Each measurement collects n images, and the exterior orientation elements of each image are represented as X ij 、Y ij 、Z ij 、 ω ij 、κ ij , where i = 1, 2,..., m; j = 1, 2,..., n; Secondly, find the absolute values of the differences in the exterior orientation elements between the m groups, with a total of data, which are respectively represented as ΔX uj , ΔY uj , ΔZ uj , Δω uj , Δk uj , where u = 1, 2, …, j = 1, 2,..., n; Then, calculate the standard deviation of the absolute value of the difference in exterior orientation elements among n photos; wherein, RMS represents the standard deviation, j = 1, 2,..., n; Finally, calculate the average value of the standard deviations of the exterior orientation elements of u groups according to formulas (2-1) to (2-6); Among them, The data obtained from formulas (2-7) to (2-12) reflects the level of consistency of the measurement network pattern in industrial photogrammetry. The smaller the value of the 6-degree-of-freedom parameter obtained, the better the consistency of the measurement network pattern. Conversely, the worse the consistency of the measurement network pattern; 3) Ultra-high-precision deformation measurement: Select the optimal measurement network pattern in step 2), and control the position and degrees-of-freedom attitude of the measurement camera through the moving track, lead screw guide rail, and rotary table of the high-precision repetitive positioning and orientation shooting device. Input the position and attitude of the camera into the controller of the high-precision repetitive positioning and orientation shooting device by means of instructions, so that the controller controls the camera to move and rotate for shooting according to the preset position and attitude. Since the high-precision repetitive positioning and orientation shooting device has relatively high repetitive positioning and orientation accuracy, a relatively high network pattern consistency accuracy can be achieved, thus realizing the purpose of ultra-high-precision deformation measurement in industrial photogrammetry.

3. The ultra-high-precision deformation measurement method based on industrial photogrammetry according to claim 1 or 2, characterized in that The high-precision repetitive positioning and orientation shooting device includes a bracket. The bracket (1) is a square bracket formed by sequentially connecting four square frames. Moving tracks (2) are provided on both the top frame and the bottom frame of the square bracket. A hollow cuboid support frame (3) perpendicular to the top frame and the bottom frame is provided between the moving tracks (2) on the top frame and the bottom frame. A lead screw guide rail (10) is installed on the support frame (3). A pan-tilt adapter plate (4) is installed on the lead screw guide rail (10). A rotary table (5) is installed on the pan-tilt adapter plate (4). A camera (7) is fixed on the rotary table (5). The moving track (2) and the lead screw guide rail (10) are both connected to a motor, and the motor and the rotary table (5) are both connected to a controller.

4. The ultra-high-precision deformation measurement method based on industrial photogrammetry according to claim 3, characterized in that The camera is a CIM-3 camera.

5. The ultra-high-precision deformation measurement method based on industrial photogrammetry according to claim 3, characterized in that The controller is a PLC programmable logic controller.

6. The ultra-high-precision deformation measurement method based on industrial photogrammetry according to claim 3, characterized in that, The four square frames are composed of two long ones and two short ones to form a rectangular bracket.

7. The ultra-high-precision deformation measurement method based on industrial photogrammetry according to claim 3, wherein The rotating turntable is fixed to the camera through a mounting plate (6).

8. The ultra-high-precision deformation measurement method based on industrial photogrammetry according to claim 3, characterized in that At the top and bottom of the support frame (3), connecting plates (9) are provided, and pulleys (8) are installed on the connecting plates (9). The pulleys (8) are clamped in the slide rails of the moving track (2).

9. The ultra-high precision deformation measurement method based on industrial photogrammetry according to claim 8, characterized in that, Both ends of the lead screw guide rail (10) are respectively installed on the connecting plates (9) at the top and bottom of the support frame (3) and are perpendicular to the connecting plates (9).

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