High-speed rotating blade deformation measurement method, system, equipment and medium

Abstract

The embodiments of this specification provide a method, system, equipment and medium for measuring the deformation of a high-speed rotating blade, wherein the system includes a blade, a phase locking device and a computer; the blade is arranged on a hub, and the hub is controlled by a computer to drive the blade to rotate; the phase locking device includes an infrared photoelectric trigger switch and a camera group connected to a synchronous controller, and before the experiment, the synchronous controller controls each camera of the camera group to synchronously shoot the blade to generate image group one, and sends it to the computer; during the experiment, the blade rotates, and the computer controls the infrared photoelectric trigger switch to send an infrared beam to the blade, and after receiving the reflected beam, sends a high-level pulse signal to the synchronous controller, and the synchronous controller controls each camera of the camera group to synchronously shoot the blade to generate image group two and send it to the computer; the blade displacement is obtained by calculation by the computer.

Description

Technical Field

[0001] The present invention relates to the field of aerospace testing technology, and in particular to a method, system, equipment and medium for measuring deformation of a high-speed rotating blade. Background Art

[0002] Digital Image Correlation (DIC) is an optical deformation measurement technology that uses correlation matching based on the natural texture or artificial speckle features distributed on the surface of the object to obtain two-dimensional morphology and deformation information of the object. Three-Dimensional DIC (3D DIC) is based on DIC and stereo vision technology to obtain three-dimensional morphology and deformation information. Compared with traditional physical measurement technologies such as placing resistance strain gauges on the surface of the object to be measured, this type of non-contact measurement method has the advantages of full-field measurement, high accuracy, relatively simple optical path, adjustable measurement field of view, and no special requirements for the measurement environment. It is widely used in fields such as material strain measurement, engineering structure health monitoring, and deformation measurement of rotating components. In particular, the demand for high-precision deformation measurement of high-speed rotating objects such as wind turbine blades and aircraft propeller blades is becoming increasingly prominent.

[0003] When measuring the deformation of high-speed rotating blades based on digital image correlation, there are often two factors that lead to a decrease in measurement accuracy. First, due to the high blade speed, the speckle images before and after deformation often have a large inter-frame rotation angle, resulting in de-correlation, and thus correlation matching fails. Second, the delay of the synchronization control signal makes the blade displacement observed by the camera likely to include both the blade deformation itself and the rigid displacement caused by the movement of the hub. Directly using the observed displacement will increase the measurement error.

[0004] In view of this, there is an urgent need to provide a high-speed rotating blade deformation measurement method and system that can solve the above two problems. Summary of the Invention

[0005] One or more embodiments of this specification provide a high-speed rotating blade deformation measurement system, characterized by comprising a blade, a phase locking device, and a computer;

[0006] The blades are arranged on a propeller hub, and the propeller hub is controlled by a computer to drive the blades to rotate;

[0007] The phase locking device includes an infrared photoelectric trigger switch and a camera group connected to a synchronous controller, and both are in communication with the computer; the camera group is arranged in a position so that each camera can simultaneously capture the position of any blade of the blade and the hub;

[0008] Before the experiment, the synchronization controller controlled each camera in the camera group to synchronously capture the propeller blade to generate image group 1, and sent the image group 1 to the computer. During the experiment, the propeller blade rotated, and the computer controlled the infrared photoelectric trigger switch to transmit an infrared beam to the propeller blade. After receiving the reflected beam, the computer sent a high-level pulse signal to the synchronization controller. The synchronization controller then controlled each camera in the camera group to synchronously capture the propeller blade to generate image group 2, and sent the image group 2 to the computer.

[0009] The computer uses a digital image correlation method to perform three-dimensional reconstruction on the blades in the image group one and the image group two, respectively, to obtain original point cloud data and a deformation point cloud data set; then, a three-dimensional point cloud registration method is used to calculate the rigid transformation matrix of the blade relative to the initial phase; the three-dimensional coordinates of the blade after rotation are obtained by the digital image correlation method, and the three-dimensional coordinates of the blade after rotation are transformed into a reference coordinate system where the blade's initial phase is located based on the rigid transformation matrix to obtain the blade displacement.

[0010] One or more embodiments of this specification provide a high-speed rotating blade deformation measurement method based on the high-speed rotating blade deformation measurement system described above, including:

[0011] The computer acquires the synchronization controller to control each camera of the camera group to synchronously shoot the blade in a stationary state to generate the first image group;

[0012] During the rotation of the propeller blade, the computer acquires the second image group obtained by the camera group in the phase locking device and sends it to the computer. Specifically, the computer controls the infrared photoelectric trigger switch to send an infrared beam, and when receiving the reflected beam, sends a high-level pulse signal to the synchronization controller. The synchronization controller controls each camera of the camera group to synchronously capture the propeller blade to generate the second image group and send it to the computer.

[0013] The computer uses the digital image correlation method to perform three-dimensional reconstruction of the blades in the image groups based on the first and second image groups, respectively, to obtain the original point cloud data and the deformation point cloud data set;

[0014] The rigid transformation matrix of the blade relative to the initial phase is calculated by the three-dimensional point cloud registration method; the three-dimensional coordinates of the blade after rotation are obtained by the digital image correlation method. Based on the rigid transformation matrix, the three-dimensional coordinates of the blade after rotation are transformed into the reference coordinate system where the blade's initial phase is located to obtain the blade displacement.

[0015] One or more embodiments of this specification provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned high-speed rotating blade deformation measurement method is implemented.

[0016] One or more embodiments of this specification provide a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the high-speed rotating blade deformation measurement method described above is implemented.

[0017] The phase locking device of this embodiment is configured to achieve phase locking of high-speed rotating blades. Since the position of the infrared photoelectric trigger switch and the frequency of the transmitted infrared light beam are fixed, and only the uniform blade deformation measurement situation is considered, only when the blade runs to a certain phase will it reflect the infrared light beam to trigger the stereo camera to record the image, thereby achieving blade phase locking. During the computer deformation process, the three-dimensional point cloud alignment of the blade's morphology before and after deformation is performed to eliminate the blade's rigid body displacement, thereby further improving the measurement accuracy of blade deformation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 A schematic diagram of the structure of a high-speed rotating blade deformation measurement system provided in one or more embodiments of this specification;

[0020] Figure 2 A schematic diagram of rigid displacement induced by the rotation of the hub 3 during a test of a high-speed rotating blade deformation measurement system provided in one or more embodiments of this specification;

[0021] Figure 3 A flowchart of calculating the optimal rigid transformation using the ICP algorithm in a high-speed rotating blade deformation measurement system provided by one or more embodiments of this specification;

[0022] Figure 4 A flow chart of a method for measuring deformation of a high-speed rotating blade provided in one or more embodiments of this specification;

[0023] Figure 5 A schematic diagram of the structure of a computer provided for one or more embodiments of this specification. DETAILED DESCRIPTION

[0024] In order to help those skilled in the art better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below in conjunction with the drawings in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this invention.

[0025] The present invention will be described in detail below with reference to specific implementation methods and the accompanying drawings.

[0026] System Example

[0027] According to an embodiment of the present invention, a high-speed rotating blade deformation measurement system is provided. Figure 1 FIG. 1 is a schematic structural diagram of a high-speed rotating blade deformation measurement system provided in this embodiment. The high-speed rotating blade deformation measurement system according to an embodiment of the present invention includes a blade 1, a phase locking device 2, and a computer.

[0028] The blade 1 is mounted on a hub 3 of a ground test platform, and the hub 3 is controlled by a computer to drive the blade 1 to rotate;

[0029] The phase locking device 2 is used to achieve phase locking of high-speed rotating blades, and includes an infrared photoelectric trigger switch 22 and a camera group 23 connected to the synchronization controller 21. The infrared photoelectric trigger switch 22 and the camera group 23 are both communicatively connected to the computer; the camera group 23 is set in a position such that each camera can simultaneously photograph any blade in the blade 1 and the position of the hub 3.

[0030] The working process is as follows:

[0031] Before the experiment, synchronization controller 21 controlled each camera in camera group 23 to synchronously capture blade 1, generating image group 1, and sending the image to the computer. During the experiment, blade 1 rotated, and the computer controlled infrared photoelectric trigger switch 22 to transmit an infrared beam to blade 1. After receiving the reflected beam, the computer sent a high-level pulse signal to synchronization controller 21. Synchronization controller 21 controlled each camera in camera group 23 to synchronously capture blade 1, generating image group 2, and sending the image to the computer.

[0032] The computer uses a digital image correlation method to perform three-dimensional reconstruction of the blades in the image groups based on image group 1 and image group 2, respectively, to obtain original point cloud data and deformation point cloud data sets, respectively; then, a three-dimensional point cloud registration method is used to calculate the rigid transformation matrix of the blade relative to the initial phase; the three-dimensional coordinates of the blade after rotation are obtained by the digital image correlation method, and the three-dimensional coordinates of the blade after rotation are transformed into a reference coordinate system where the blade has its initial phase based on the rigid transformation matrix, thereby eliminating the rigid body displacement and obtaining the true displacement of blade 1.

[0033] In the system of this embodiment, the phase locking device 2 is set to achieve phase locking of high-speed rotating blades. Since the position of the infrared photoelectric trigger switch and the frequency of the transmitted infrared light beam are fixed, and only the uniform blade deformation measurement situation is considered, only when the blade runs to a certain phase will it reflect the infrared light beam to trigger the stereo camera to record the image, thereby achieving the locking of the blade phase. In addition, during the computer deformation process, the three-dimensional point cloud alignment of the blade's morphology before and after deformation is performed to eliminate the blade's rigid body displacement, thereby further improving the measurement accuracy of the blade deformation.

[0034] In some embodiments, reference Figure 2 As shown, it is a schematic diagram of the rigid displacement introduced by the rotation of the hub 3 provided in this embodiment; when there is a certain delay in the synchronous acquisition control signal of the synchronous controller 21 or the blade speed changes, such as the rotation speed of the locked blade 1 phase (normal rotation speed) is different from the rotation speed of the original phase (0 rotation speed), there is a certain deviation between the two phases, that is, the blade 1 cannot be completely locked, so the deformation is calculated directly based on the digital image correlation method, which is not the real deformation data. In addition to the non-rigid deformation of the blade itself, the blade displacement captured by the camera group 23 also has the rigid displacement caused by the rotation of the hub 3. Therefore, the deformation amount of blade 1 calculated directly based on the digital image correlation method is not the real deformation data, and the rigid displacement caused by the rotation of the hub 3 must be eliminated first. Therefore, the displacement amount of blade 1 calculated in this embodiment includes the following steps:

[0035] Step 101: Based on the image group 1, the computer uses a digital image correlation method to perform three-dimensional reconstruction of the blade root or the hub 3 in the image group to obtain an origin cloud data set;

[0036] Step 102: Based on the second image group, the computer uses a digital image correlation method to perform three-dimensional reconstruction of the blade root or the hub 3 in the image group to obtain a deformation point cloud data set.

[0037] Step 102: Calculate the rigid transformation matrix of the blade relative to the initial phase using a three-dimensional point cloud registration method based on the original point cloud data and the deformed point cloud data set.

[0038] Step 103 , obtaining the three-dimensional coordinates of the rotated blade 1 based on a digital image correlation method; in this step, reconstructing the three-dimensional coordinates based on a digital correlation method is a conventional technical means, which will not be elaborated here.

[0039] Step 104 : transform the obtained three-dimensional coordinates of the blade 1 after rotation into a reference coordinate system where the initial phase of the blade 1 is located based on the rigid transformation matrix to obtain the displacement of the blade 1 .

[0040] In this embodiment, it is considered that in addition to the non-rigid deformation of the blade itself, the blade root or the hub 3 will also produce rigid displacement. However, compared with the displacement of the blade, the rigid displacement generated when the blade root or the hub 3 rotates is smaller. Based on the rigid displacement generated when the blade root or the hub 3 rotates, the real displacement data is determined, and the rigid body displacement is eliminated while improving the deformation measurement accuracy.

[0041] In the above embodiment, in actual applications, when the physical size of the blade 1 is long and the camera needs to shoot one of the blades and the hub 3 at the same time, the distance from the blade and the hub 3 may be far, resulting in the speckle on the surface of both occupying too small an image pixel, which will cause errors in the digital image correlation matching; and the non-rigid deformation of the blade root is small and can be ignored. Therefore, this embodiment calculates the displacement of the blade 1 based on the blade root point cloud data in image group one and image group two.

[0042] In some embodiments, the three-dimensional point cloud registration method uses the Iterative Closest Point (ICP) algorithm to register the blade root point cloud before and after deformation. The essence is the optimal registration method based on the least squares method. The basic idea is to perform registration on two sets of point cloud sets, namely the deformation point cloud set P = {p i} and the source point cloud Q = {q i}, by finding an optimal transformation matrix T in space n o rm (composed of the rotation matrix R and the translation vector t), so that the distance between each point cloud in the deformed point cloud set P and the source point cloud set Q is minimized, and T is solved by the objective function norm , thereby determining the optimal rigid transformation, the specific distance minimum objective function is as follows:

[0043]

[0044] Where n is the number of 3D points in the point cloud;

[0045] The ICP algorithm repeatedly selects corresponding matching point pairs and calculates the optimal rigid transformation until the convergence accuracy requirement for correct registration is met. Figure 3 , which is a flowchart of calculating the optimal rigid transformation matrix using the ICP algorithm provided in this embodiment. The specific calculation is as follows:

[0046] Step 201: Extract the closest matching point to each point in the source point cloud set Q from the deformed point cloud set P. Brute force search can be used to calculate the Euclidean distance between all points in the deformed point cloud set P and each point in the source point cloud set Q. The point with the smallest distance is taken as the matching point to obtain the point cloud set P'.

[0047] Step 202: Obtain a rigid transformation that minimizes the average distance between the point cloud set P' and the source point cloud set Q, minimizing the objective function formula (1);

[0048] Step 203: Apply the rotation and translation parameters obtained in step 202 to each point cloud in the deformed point cloud set P to obtain each new transformed point cloud, and calculate the distance between each new transformed point cloud and each point cloud in the source point cloud set Q.

[0049] Step 204 , when determining whether the distance is less than a preset threshold, if so, stop the iterative calculation and go to step 205 ; otherwise, continue the iteration with the new transformed point cloud as the new original point cloud and go to step 201 .

[0050] Step 205: Obtain the optimal rigid transformation;

[0051] This embodiment is optional. The brute force search in step 201 is relatively time-consuming, especially when the point cloud data is large, which greatly reduces the efficiency of ICP. Therefore, the kd tree search method can be used instead of the brute force search.

[0052] Optionally, the optimization solution in step 202 may be based on a singular value decomposition (SVD) method, and the steps are as follows:

[0053] a) Decentralize the points in the point cloud set P' and the source point cloud set Q by subtracting their own centroids:

[0054]

[0055]

[0056] b) Find the covariance matrix of the two point clouds P" and Q' after decentralization:

[0057]

[0058] c) Calculate the rotation matrix R:

[0059] Perform SVD decomposition on the above formula (3), and we have

[0060]

[0061] When W is full rank, there is a unique solution:

[0062] R=UV T (5)

[0063] d) Calculate the translation vector t:

[0064] The translation vector t is obtained based on the center points of the two point clouds:

[0065]

[0066] Method Example

[0067] According to an embodiment of the present invention, a method for measuring deformation of a high-speed rotating blade based on the above system is provided. Figure 4 FIG. 2 is a flow chart of a method for measuring deformation of a high-speed rotating blade according to an embodiment of the present invention. The method for measuring deformation of a high-speed rotating blade according to an embodiment of the present invention includes:

[0068] Step S1: A computer obtains a first image group generated by synchronously capturing a blade in a stationary state by each camera of a camera group controlled by a synchronization controller;

[0069] Step S2: During the rotation of the blade, the computer obtains a second image group obtained by the camera group in the phase locking device photographing the blade. Specifically, the computer controls the infrared photoelectric trigger switch 22 to transmit an infrared beam, and upon receiving the reflected beam, transmits a high-level pulse signal to the synchronization controller 21. The synchronization controller 21 controls each camera of the camera group 23 to synchronously photograph the blade 1, generate a second image group, and transmit the image group to the computer.

[0070] Step S3: The computer uses a digital image correlation method to perform three-dimensional reconstruction of the blades in the image groups based on the first image group and the second image group, respectively, to obtain original point cloud data and deformation point cloud data sets;

[0071] Step S4: Calculate the rigid transformation matrix of the blade relative to the initial phase using a three-dimensional point cloud registration method; obtain the three-dimensional coordinates of the blade after rotation using a digital image correlation method; transform the three-dimensional coordinates of the blade after rotation into the reference coordinate system where the blade's initial phase is located based on the rigid transformation matrix to obtain the displacement of blade 1.

[0072] In some embodiments, in step S3, a digital image correlation method is used to perform three-dimensional reconstruction on the blade root or the hub 3 in image group one to obtain original point cloud data, and to perform three-dimensional reconstruction on the blade root or the hub 3 in image group two to obtain a deformation point cloud data set.

[0073] In some embodiments, the displacement of blade 1 is calculated based on the blade root point cloud data in image group 1 and image group 2. The three-dimensional point cloud registration method uses an ICP algorithm and determines the displacement of blade 1 based on a minimum distance objective function, wherein the minimum distance objective function is:

[0074]

[0075] Based on the minimum objective function of formula (7), the ICP algorithm repeatedly selects corresponding matching point pairs and calculates the optimal rigid transformation matrix until the convergence accuracy requirement of correct registration is met. The specific process is as follows:

[0076] Step 301: extract the closest matching point to each point in the source point cloud set Q from the deformed point cloud set P. Brute force search can be used to calculate the Euclidean distance between all points in the deformed point cloud set P and each point in the source point cloud set Q. The point with the smallest distance is selected as the matching point to obtain the point cloud set P'.

[0077] Step 302: Obtain a rigid transformation that minimizes the average distance between the point cloud set P' and the source point cloud set Q, minimizing the objective function formula (7);

[0078] Step 303: Apply the rotation and translation parameters obtained in step 302 to each point cloud in the deformed point cloud set P to obtain each new transformed point cloud, and calculate the distance between each new transformed point cloud and each point cloud in the source point cloud set Q.

[0079] Step 304: Determine whether the distance is less than a preset threshold. If so, stop iterative calculation and go to step 305. Otherwise, continue iteration with the new transformed point cloud as the new original point cloud and go to step 301.

[0080] Step 305: Obtain the optimal rigid transformation.

[0081] This embodiment is optional. The brute force search in step 301 is relatively time-consuming, especially when the point cloud data is large, which greatly reduces the efficiency of ICP. Therefore, the kd tree search method can be used instead of the brute force search.

[0082] Optionally, the optimization solution in step 302 may be based on a singular value decomposition (SVD) method, and the steps are as follows:

[0083] a) Decentralize the points in the point cloud set P' and the source point cloud set Q by subtracting their own centroids:

[0084]

[0085]

[0086] b) Find the covariance matrix of the two point clouds P" and Q' after decentralization:

[0087]

[0088] c) Calculate the rotation matrix R:

[0089] Perform SVD decomposition on the above formula (9), and we have

[0090] W=U∑V T (10)

[0091] When W is full rank, there is a unique solution:

[0092] R=UV T (11)

[0093] d) Calculate the translation vector t:

[0094] The translation vector t is obtained based on the center points of the two point clouds:

[0095]

[0096] The method embodiment of the present invention is a method embodiment corresponding to the above-mentioned system embodiment. The specific operations performed in each step can be understood by referring to the description of each device in the system embodiment, and will not be repeated here.

[0097] like Figure 5 As shown, the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for measuring deformation of a high-speed rotating blade in the above embodiment is implemented. Alternatively, when the computer program is executed by a processor, the method for measuring deformation of a high-speed rotating blade in the above embodiment is implemented. When the computer program is executed by the processor, the following method steps are implemented:

[0098] Step S1: A computer obtains a first image group generated by synchronously capturing a blade in a stationary state by each camera of a camera group controlled by a synchronization controller;

[0099] Step S2: During the rotation of the propeller blade, the computer obtains a second set of images obtained by the camera group in the phase locking device photographing the propeller blade;

[0100] Step S3: The computer uses a digital image correlation method to perform three-dimensional reconstruction of the blades in the image groups based on the first image group and the second image group, respectively, to obtain original point cloud data and deformation point cloud data sets;

[0101] Step S4: Calculate the rigid transformation matrix of the blade relative to the initial phase through the three-dimensional point cloud registration method; obtain the three-dimensional coordinates of the blade after rotation through the digital image correlation method, and transform the three-dimensional coordinates of the blade after rotation into the reference coordinate system where the blade's initial phase is located based on the rigid transformation matrix to obtain the blade displacement.

[0102] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0103] Each embodiment in this specification is described in a progressive manner. The same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the device or system embodiments, since they are basically similar to the method embodiments, the description is relatively simple. For the relevant parts, refer to the partial description of the method embodiments. The device and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. A person of ordinary skill in the art can understand and implement it without making any creative efforts.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A high-speed rotating blade deformation measurement system, characterized in that: It comprises a blade (1), a phase locking device (2) and a computer; The blade (1) is arranged on a hub (3), and the hub (3) is controlled by a computer to drive the blade (1) to rotate; The phase locking device (2) comprises an infrared photoelectric trigger switch (22) and a camera group (23) connected to a synchronous controller (21), and both are in communication connection with the computer; the camera group (23) is arranged in a position such that each camera can simultaneously photograph any blade of the blade (1) and the position of the hub (3); Before the experiment, the synchronous controller (21) controls each camera of the camera group (23) to synchronously shoot the blade (1) to generate image group 1, and sends the image group 1 to the computer; during the experiment, the blade (1) rotates, and the computer controls the infrared photoelectric trigger switch (22) to send an infrared beam to the blade (1), and after receiving the reflected beam, sends a high-level pulse signal to the synchronous controller (21), and the synchronous controller (21) controls each camera of the camera group (23) to synchronously shoot the blade (1) to generate image group 2, and sends the image group 2 to the computer; The computer uses a digital image correlation method to perform three-dimensional reconstruction on the blades in the image group 1 and the image group 2 respectively, and obtains original point cloud data and a deformation point cloud data set; then calculates the rigid transformation matrix of the blade relative to the initial phase by a three-dimensional point cloud registration method; obtains the three-dimensional coordinates of the blade after rotation by a digital image correlation method, and transforms the three-dimensional coordinates of the blade after rotation to a reference coordinate system where the blade's initial phase is located based on the rigid transformation matrix to obtain the displacement of the blade (1).

2. The high-speed rotating blade deformation measurement system according to claim 1, characterized in that: The computer, based on the first image group, uses a digital image correlation method to perform three-dimensional reconstruction on the blade root or the hub (3) in the first image group, thereby obtaining an original point cloud data set; and the computer, based on the second image group, uses a digital image correlation method to perform three-dimensional reconstruction on the blade root or the hub (3) in the second image group, thereby obtaining a deformation point cloud data set.

3. The high-speed rotating blade deformation measurement system according to claim 1 or 2, characterized in that: The three-dimensional point cloud registration method adopts an iterative nearest neighbor algorithm.

4. The high-speed rotating blade deformation measurement system according to claim 3, characterized in that: The displacement of the blade (1) is calculated based on the blade root point cloud data in the image group 1 and the image group 2 as follows: Based on the original point cloud dataset and the deformed point cloud dataset, we find the optimal transformation matrix T in a space. norm , so that the distance between each point cloud in the deformed point cloud set P and the source point cloud set Q is minimized, and T is solved by the objective function norm , determine the optimal rigid transformation, the specific distance minimum objective function is as follows: Where R is the rotation matrix, t is the translation vector, and q i is the three-dimensional coordinate of the i-th source point cloud, p i is the 3D coordinate of the i-th deformed point cloud, i = 1 to n, n is the number of 3D points in the point cloud; The optimal rigid transformation matrix is calculated using the ICP algorithm. The specific calculation is as follows: Step 201: extract the closest matching point to each point in the source point cloud set Q from the deformed point cloud set P, calculate the Euclidean distance between all points in the deformed point cloud set P and each point in the source point cloud set Q, and take the point with the smallest distance as the matching point to obtain the point cloud set P'; Step 202: Obtain a rigid transformation that minimizes the average distance between the point cloud set P' and the source point cloud set Q, minimizing the objective function formula (1); Step 203: Apply the rotation and translation parameters obtained in step 202 to each point cloud in the deformed point cloud set P to obtain each new transformed point cloud, and calculate the distance between each new transformed point cloud and each point cloud in the source point cloud set Q. Step 204: Determine whether the distance is less than a preset threshold. If so, stop iterative calculation and go to step 205. Otherwise, continue iteration with the new transformed point cloud as the new original point cloud and go to step 201. Step 205: Obtain the optimal rigid transformation.

5. A method for measuring deformation of a high-speed rotating blade implemented based on the high-speed rotating blade deformation measurement system according to any one of claims 1 to 4, characterized in that: include: The computer acquires the synchronization controller to control each camera of the camera group to synchronously shoot the blade in a stationary state to generate the first image group; During the rotation of the propeller blade, the computer acquires the second image group obtained by the camera group in the phase locking device and sends it to the computer. Specifically, the computer controls the infrared photoelectric trigger switch to send an infrared beam, and when receiving the reflected beam, sends a high-level pulse signal to the synchronization controller. The synchronization controller controls each camera of the camera group to synchronously capture the propeller blade to generate the second image group and send it to the computer. The computer uses the digital image correlation method to perform three-dimensional reconstruction of the blades in the image groups based on the first and second image groups, respectively, to obtain the original point cloud data and the deformation point cloud data set; The rigid transformation matrix of the blade relative to the initial phase is calculated by the three-dimensional point cloud registration method; the three-dimensional coordinates of the blade after rotation are obtained by the digital image correlation method. Based on the rigid transformation matrix, the three-dimensional coordinates of the blade after rotation are transformed into the reference coordinate system where the blade's initial phase is located to obtain the blade displacement.

6. The method for measuring deformation of a high-speed rotating blade according to claim 5, wherein: The digital image correlation method is used to perform three-dimensional reconstruction on the blade root or the hub (3) in the first image group to obtain original point cloud data, and the three-dimensional reconstruction is performed on the blade root or the hub (3) in the second image group to obtain a deformation point cloud data set.

7. The method for measuring deformation of a high-speed rotating blade according to claim 5 or 6, wherein: The three-dimensional point cloud registration method adopts an iterative nearest neighbor algorithm.

8. The method for measuring deformation of a high-speed rotating blade according to claim 7, wherein: The displacement of the blade (1) is calculated based on the blade root point cloud data in the image group 1 and the image group 2 as follows: Based on the original point cloud dataset and the deformed point cloud dataset, we find the optimal transformation matrix T in a space. norm , so that the distance between each point cloud in the deformed point cloud set P and the source point cloud set Q is minimized, and T is solved by the objective function norm , determine the optimal rigid transformation, the specific distance minimum objective function is as follows: Where R is the rotation matrix, t is the translation vector, and q i is the three-dimensional coordinate of the i-th source point cloud, p i is the 3D coordinate of the i-th deformed point cloud, i = 1 to n, n is the number of 3D points in the point cloud; The optimal rigid transformation matrix is calculated using the ICP algorithm. The specific calculation is as follows: Step 301: extract the closest matching point to each point in the source point cloud set Q from the deformed point cloud set P. Brute force search can be used to calculate the Euclidean distance between all points in the deformed point cloud set P and each point in the source point cloud set Q. The point with the smallest distance is selected as the matching point to obtain the point cloud set P'. Step 302: Obtain a rigid transformation that minimizes the average distance between the point cloud set P' and the source point cloud set Q, minimizing the objective function formula (2); Step 303: Apply the rotation and translation parameters obtained in step 302 to each point cloud in the deformed point cloud set P to obtain each new transformed point cloud, and calculate the distance between each new transformed point cloud and each point cloud in the source point cloud set Q. Step 304: Determine whether the distance is less than a preset threshold. If so, stop iterative calculation and go to step 305. Otherwise, continue iteration with the new transformed point cloud as the new original point cloud and go to step 301. Step 305: Obtain the optimal rigid transformation.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the high-speed rotating blade deformation measurement method according to any one of claims 5 to 8 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the high-speed rotating blade deformation measurement method according to any one of claims 5 to 8 is implemented.

Images