FTP-based rotor blade surface topography and deformation measurement method

Abstract

The invention discloses a rotor blade surface topography and deformation measurement method based on FTP, a measurement system is composed of a high-energy grating projection device, a high-speed imaging module, a rotating speed synchronous control device, a cable and the like, and the high-energy grating projection device is matched with the high-speed imaging module capable of 1 us exposure. Clear imaging of the aero-engine rotor blade at a high rotating speed and a high linear speed is realized, and the problem that motion blur is easy to generate in rotor blade imaging at a high rotating speed of an engine is solved. Through the rotating speed synchronous control device, synchronous acquisition of the rotor blade and the high-speed imaging module is realized, and the problem that the detected blade is not easy to identify due to asynchronism of the rotor blade and the imaging module is solved. The invention innovatively provides the method and the requirement for evaluating the matching of the light source and the imaging quality before the measurement of the surface topography and the deformation of the rotor blade at the inlet of the aero-engine based on the FTP, and lays a foundation for the FTP topography measurement of the aero-engine in a limited space.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of aero-engine testing, and particularly relates to a rotor blade surface morphology and deformation measurement method based on FTP, which is suitable for an aero-engine inlet rotor blade. BACKGROUND

[0002] At present, there is no effective means for online measurement of the surface profile damage degree of the fan blade, so it is of great significance to realize online measurement of the surface profile of the fan blade and evaluate the damage degree of the fan blade for the fine evaluation of the change of the engine aerodynamics and strength.

[0003] In the process of three-dimensional measurement of high-speed changing dynamic scenes, even if the shooting speed is fast, theoretically, the patterns photographed by the front and rear frames all have position changes, so the three-dimensional reconstruction algorithm based on a single frame of pattern is most suitable for three-dimensional measurement of dynamic scenes in principle. In order to meet the requirements of three-dimensional measurement of dynamic scenes, scholars have developed a series of three-dimensional reconstruction algorithms based on a single frame of pattern. These algorithms are roughly divided into two categories: single-frame reconstruction method based on binary pattern projection and single-frame reconstruction method based on stripe pattern projection.

[0004] The single-frame reconstruction method based on binary pattern projection uniquely marks each sampling point in the plane by projecting a designed coding pattern, but this method needs to use the pixels in the surrounding area of the current point to assist in coding, and the spatial resolution is not high, and the recovery ability for the detailed information of the object is weak. The single-frame method based on stripe pattern projection is to project the gray continuous change stripe information, and then extract the phase information containing the height information of the object in the transform domain, and use the point-by-point phase information to mark the surface to be measured densely, and complete the three-dimensional reconstruction. Among them, since Fourier transform profilometry (FTP) has the characteristics of high calculation efficiency and easy-to-select parameters, it has been most widely applied in high-speed three-dimensional shape measurement of transient processes.

[0005] The typical Fourier transform profilometry method is divided into a classical Fourier transform profilometry (FTP), a temporal Fourier transform profilometry (TFTP) and a micro Fourier transform profilometry (muFTP). For the FTP method, only one frame of pattern needs to be projected to complete the reconstruction, the requirement for the projection device is low, and there is no inter-frame motion blur problem, but the object detail information cannot be reconstructed due to the existence of spatial filtering, and therefore the FTP method is only suitable for three-dimensional measurement of a rapidly changing smooth and continuous surface. For the TFTP method, a series of phase shift patterns need to be projected, a sinusoidal intensity change is constructed on the time axis, and an independent transformation is solved at each pixel, and therefore at least a plurality of phase shift patterns need to be projected repeatedly (to satisfy the sampling quantization frequency on the time axis). The TFTP method needs to use a projection pattern switching device compared with the FTP method, but can complete the measurement of a spatial steep change and discontinuous surface, and therefore the TFTP method is suitable for high-speed measurement of a spatial discontinuous but time continuous surface. For the muFTP method, three frequency different stripe patterns and a white field pattern need to be projected at intervals to complete absolute phase recovery, and therefore compared with the FTP method, the method can complete the measurement of isolated and scattered objects, but the measurement efficiency is halved, and a frame rate motion error is introduced. Therefore, the muFTP method is suitable for high-speed measurement of a transient scene containing a plurality of isolated objects.

[0006] The rotor blade of an aero-engine is in high-speed rotation, the linear speed can be greater than 400 m / s, and the surface belongs to a rapidly changing smooth and continuous surface, and therefore the single-frame image FTP is suitable for three-dimensional reconstruction measurement. SUMMARY

[0007] The present application provides a rotor blade surface morphology and deformation measurement method based on FTP, which can realize accurate measurement of the rotor blade surface morphology and deformation in the limited space of an aero-engine, and solves the problem that there is no effective means for online measurement of the surface profile damage degree of a fan blade.

[0008] The FTP three-dimensional measurement principle is that the measurement principle of the traditional Fourier transform profilometry method is that a single frequency high-frequency sinusoidal stripe is first projected to the measured surface by a projection device, and a deformed stripe pattern modulated by the object height is captured from another angle by an imaging device, which can be expressed as: (1); Wherein, a(x, y) is background light intensity, b(x, y) is fringe intensity amplitude, and phi(x, y) is phase distribution containing object height information. Fourier transform is carried out on I(x, y), a filter window function with appropriate size is selected to filter out the base frequency component containing object height information, and inverse Fourier transform is carried out on the base frequency component to obtain: (2); The phase distribution thereof can be obtained through formula (3): (3) Wherein, arctan[•] represents inverse tangent function, Im[•] and Re[•] represent taking imaginary part and real part of complex number respectively. Since the value range of inverse tangent function is defined in (-pi, pi], the result obtained by solving is a series of truncated phase with periodic ambiguity, and phase unwrapping needs to be carried out. In dynamic measurement, two-dimensional Fourier analysis processing can be carried out frame by frame, or three-dimensional Fourier analysis can be directly carried out on all data to obtain three-dimensional truncated phase field. Through system calibration (including projector calibration and camera calibration), the real three-dimensional space coordinate distribution of the measured scene can be obtained, and dynamic measurement is completed.

[0009] The object of the application is achieved by the following technical solutions: A rotor blade surface morphology and deformation measurement method based on FTP, comprising a measurement system, the measurement system comprising a high-energy grating projection device, a high-speed imaging module and a rotating speed synchronous control device; Measurement layout and requirements: clear imaging of the rotor blade of the aero-engine under high rotating speed and high linear speed is realized by the high-energy grating projection device in cooperation with the high-speed imaging module; the rotor blade and the high-speed imaging module are synchronized by the rotating speed synchronous control device; Evaluation of light source and imaging quality matching before test measurement: after the FTP measurement layout is prepared, the evaluation of light source and imaging quality matching between the high-energy grating projection device and the high-speed imaging module is carried out; Obtaining calibration parameters: the geometric parameters and optical parameters of the system are calibrated in advance before measurement, and the corresponding calibration coefficients are obtained for processing the test image later; Measurement process and requirements: step B1, synchronous signal inspection; step B2: rotor blade fringe image acquisition; step B3: running program to calculate rotor blade three-dimensional coordinates; step B4: calculating rotor blade three-dimensional deformation based on the marker point.

[0010] Further, in the measurement layout and requirements, the high-energy grating projection device is required to have a light power greater than 40W and the light power is adjustable; the high-speed imaging module is required to have a minimum exposure time of 1us, and the fringe image projected by the high-energy grating projection device on the rotor blade can be clearly imaged under the 1us exposure time of the high-speed imaging module.

[0011] Further, in the measurement layout and requirements, a rotating speed sensor is installed on the stator inside the engine, and a circumferential unique mark is made on the rotor shaft. The mark and the rotating speed sensor act once per revolution of the rotor, and the rotating speed sensor outputs a pulse once per week. A square wave signal once per week is generated by the synchronous control device for synchronous phase locking of the rotor blade. The circumferential angle of the mark on the rotor shaft is consistent with the circumferential angle of the measured rotor blade. The synchronous phase locking signal is input to the synchronization signal port of the high-speed imaging module to ensure that the position of the rotor blade is synchronized with the collection of the high-speed imaging module.

[0012] Further, in the light source and imaging quality matching evaluation before the test measurement, the following is included: Step A1, measurement system setup and debugging: set up the FTP imaging light path according to the measurement system, adjust the high-energy grating projection device to ensure that the stripes on the rotor blade are clearly visible, and adjust the high-speed imaging module to ensure that the stripe image is clear. Step A2, high-speed imaging module imaging quality evaluation: the high-speed imaging module collects a group of stripe images, and the stripe intensity amplitude of the stripe image is obtained by processing the image processing program. If the intensity amplitude is 100 or above, the intensity amplitude meets the test requirements, otherwise the light power of the high-energy grating projection device needs to be increased to re-collect and process until the intensity amplitude is 100 or above.

[0013] Further, in the acquisition of calibration parameters, the single-frame stripe analysis method based on Fourier transform profilometry is used to calculate the continuous phase θ carrying the height information of the object. The geometric parameters and optical parameters of the system are accurately obtained by the calibration method, and the corresponding relationship between the image coordinates [u, v] collected by the high-speed imaging module and the world coordinates [X C , Y C ] is obtained. Further, the phase θ of the stripe image projected by the high-energy grating projection device is extracted to establish the [u, v, θ] parameter model matrix A, and then Z C= A*a is calculated by the constructed parameter model matrix A and the known three-dimensional coordinates of the calibration plate image.

[0014] Further, in step B1, the synchronization signal check, the engine rotor is rotated, and it is checked whether the rotating speed synchronization control device can normally output the synchronization signal and the high-speed imaging module can normally collect the measured rotor blade during the rotation. If the engine cannot be rotated, the signal check is performed at a rotating speed of 600 to 3000 r / min.

[0015] Further, in step B2, the rotor blade stripe image collection, according to the engine operating state, the rotor blade stripe images at different rotating speeds are collected and stored.

[0016] Further, step B3, running program calculates the three-dimensional coordinates of the rotor blade, based on Fourier transform to calculate the phase of the rotor blade stripe image, the specific process is: reading the rotor blade stripe image, selecting the rotor blade ROI area, windowing the image according to the image size; Fourier transform is carried out on the windowed image; based on the calibration data, set the fundamental frequency center [u0, v0] and the bandwidth σ size; based on the fundamental frequency center [u0, v0], the bandwidth σ designs a Gaussian band-pass filter; the designed band-pass filter is used to carry out frequency domain filtering on the windowed image and carry out inverse Fourier transform; the original phase of the inverse transformed image is obtained; the original phase is unwrapped using the quality-oriented unwrapping method, and the unwrapped phase data is obtained and stored; Based on the geometric parameters, optical parameters and coefficient a obtained during calibration, according to the parameter model matrix constructed during calibration, according to the image coordinates and phase data [u, v, θ], the three-dimensional coordinates [X C , Y C , Z C ] of the rotor blade are solved; the three-dimensional point cloud [X C , Y C , Z C ] in the camera coordinate system is converted to the engine coordinate system [X w , Y w , Z w ].

[0017] Further, step B4, based on the calculation of the three-dimensional deformation of the rotor blade, the three-dimensional coordinates of the marker points are obtained, the specific method is: the collected rotor blade stripe image is subjected to Gaussian filtering to remove the stripe information, a detection algorithm is used to identify the marker points, the pixel coordinates of the marker points are obtained, the phase of the marker points is obtained based on the phase data obtained in step B3, and then the three-dimensional coordinates [X TC , Y TC , Z TC ] of the marker points are solved by the coefficient a obtained during calibration and the parameter model matrix constructed, and are converted to the engine coordinate system [X TW , Y TW , Z TW ]; Based on the three-dimensional coordinates [X TW , Y TW , Z TW ] of the marker points, the three-dimensional point cloud [X w , Y w , Z wData alignment, and the three-dimensional deformation of the corresponding points is calculated by the following method: taking the reference marker points and the corresponding rotor blade reference three-dimensional point cloud data as the reference, the mobile marker points are sorted, the rigid body transformation [R, t] matrix of the sorted marker points relative to the reference marker points is calculated, and the mobile three-dimensional point cloud is subjected to rigid body transformation [R, t] to obtain the aligned three-dimensional point cloud [X A , Y A , Z A ] data, and the difference between the aligned three-dimensional point cloud [X A , Y A , Z A ] and the reference three-dimensional point cloud [X w , Y w , Z w ] is the three-dimensional deformation of the rotor blade under the corresponding state.

[0018] The beneficial effects of the present application are: (1) The present application innovatively proposes a method for measuring the surface morphology and deformation of the inlet rotor blade of an aero-engine based on FTP. The measurement system is composed of a high-energy grating projection device, a high-speed imaging module, a rotation speed synchronous control device, and a cable. The high-energy grating projection device is matched with a high-speed imaging module with 1us exposure to realize clear imaging of the rotor blade of the aero-engine at high rotation speed and high linear speed (>400m / s), solving the problem of motion blur in imaging of the rotor blade at high rotation speed of the engine. The rotation speed synchronous control device realizes synchronization of the rotor blade and the high-speed imaging module, solving the problem of difficulty in identifying the measured blade due to asynchronization of the rotor blade and the imaging module.

[0019] (2) The present application innovatively proposes a method and requirement for light source and imaging quality matching evaluation before measuring the surface morphology and deformation of the inlet rotor blade of an aero-engine based on FTP, laying the foundation for FTP morphology measurement of the aero-engine in a limited space.

[0020] (3) The present application innovatively proposes a process and requirement for measuring the surface morphology and deformation of the inlet rotor blade of an aero-engine based on FTP. Step one: synchronous signal inspection; step two: rotor blade stripe image acquisition; step three: running program to calculate the three-dimensional coordinates of the rotor blade; step four: calculating the three-dimensional deformation of the rotor blade based on the marker points. According to the method, the synchronization of the movement of the rotor blade and the image acquisition at high rotation speed of the engine can be ensured, the accurate extraction of the stripe phase in the noise background and the accurate measurement of the surface morphology and deformation of the rotor blade can be realized.

[0021] The foregoing main scheme of the present application and each further selected scheme thereof can be freely combined to form multiple schemes, all of which are the schemes that can be adopted and claimed by the present application; and the present application can also be freely combined between each non-conflicting selection and between other selections. A person skilled in the art can understand that there are multiple combinations according to the prior art and common knowledge after understanding the schemes of the present application, all of which are the technical schemes claimed by the present application, and are not listed here. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 is a schematic diagram of the measurement system of the present application.

[0023] In the figure: 1 - engine inlet assembly, 2 - rotor blade, 3 - rotational speed sensor, 4 - rotational speed synchronous control device, 5 - high-speed imaging module, 6 - high-energy grating projection device. DETAILED DESCRIPTION

[0024] The following non-limiting examples are intended to illustrate the present application.

[0025] Example 1 Reference Figure 1 As shown in the figure, a rotor blade surface topography and deformation measurement method based on FTP includes a measurement system, which includes a high-energy grating projection device, a high-speed imaging module, and a rotational speed synchronous control device.

[0026] Measurement layout and requirements: clear imaging of the rotor blade of the aero-engine under high rotational speed (>10000r / min) and high linear speed (>400m / s) is realized by the high-energy grating projection device in combination with the high-speed imaging module, solving the problem of motion blur in imaging of the rotor blade under high rotational speed of the engine. The rotational speed synchronous control device is used to realize synchronization of the rotor blade and the high-speed imaging module, solving the problem of difficulty in identifying the measured blade due to asynchronization of the rotor blade and the imaging module.

[0027] Evaluation of light source and imaging quality matching before test measurement: after the FTP measurement layout is prepared, the light source and imaging quality matching between the high-energy grating projection device and the high-speed imaging module is evaluated, solving the problem of poor image quality in FTP topography measurement under weak exposure caused by the limited space and high rotational speed of the aero-engine.

[0028] Obtaining calibration parameters: the geometric parameters and optical parameters of the system are calibrated in advance before measurement, and the corresponding calibration coefficients are obtained for processing the test images later.

[0029] Measurement process and requirements: step B1, synchronization signal check; step B2: rotor blade stripe image acquisition; step B3: running program to calculate the three-dimensional coordinates of the rotor blade; step B4: calculating the three-dimensional deformation of the rotor blade based on the marker points.

[0030] The measurement layout and requirements are as shown in the following table: Figure 1 As shown in the figure, the measurement system comprises a high-energy grating projection device 6, a high-speed imaging module 5 and a rotating speed synchronous control device 4. Compared with the common grating projection device and the imaging module, the high-energy grating projection device in the embodiment requires a higher light power, which is ensured to be above 40W, and the light power is adjustable. The high-speed imaging module needs to achieve a minimum exposure time of 1us, and the stripe image projected by the high-energy grating projection device on the rotor blade can be clearly imaged under the exposure time of the high-speed imaging module 1us.

[0031] In the measurement layout and requirements, a rotating speed sensor 3 is mounted on the stator inside the engine, and a circumferential unique mark is made on the corresponding rotor shaft. The mark acts with the rotating speed sensor once every rotation of the rotor, and the rotating speed sensor outputs a pulse once every week. A square wave signal once every week is generated through the synchronous control device for synchronous phase locking of the rotor blade; the circumferential angle of the mark on the rotor shaft is consistent with the circumferential angle of the measured rotor blade; the synchronous phase locking signal is input into the synchronous signal port of the high-speed imaging module, so as to ensure that the position of the rotor blade is synchronized with the collection of the high-speed imaging module.

[0032] In the light source and imaging quality matching evaluation before the test measurement, the following steps are included: step A1, measurement system building and debugging: according to the measurement system building FTP imaging light path as shown in the figure, the high-energy grating projection device is adjusted to ensure that the stripes on the rotor blade are clearly visible, and the high-speed imaging module is adjusted to ensure that the stripe image is clear. Figure 1

[0033] Step A2, high-speed imaging module imaging quality evaluation: the high-speed imaging module collects a group of stripe images, and the stripe intensity amplitude of the stripe image is obtained through image processing program. If the intensity amplitude is 100 or above, the intensity amplitude meets the test requirements, otherwise the light power of the high-energy grating projection device needs to be increased to re-collect and process until the intensity amplitude is 100 or above.

[0034] In the acquisition of calibration parameters, a single-frame stripe analysis method based on Fourier transform profilometry (FTP) is used to calculate the continuous phase θ carrying the height information of the object. However, in order to convert the continuous phase into the coordinates in the real three-dimensional space and complete the reconstruction of the dynamic three-dimensional morphology, it is necessary to rely on the camera calibration model. The core of this process is to establish two types of mapping relationships: one is the mapping relationship between the phase θ and the object height Z C , and the other is the corresponding relationship between the two-dimensional image coordinates [u, v] and the world coordinates [X C , Y C ].

[0035] ​With the Zhang Zhengyou calibration method, the geometric parameters (such as the internal and external parameters of the high-speed imaging module, the relative position of the high-energy grating projection device and the high-speed imaging module) and the optical parameters (such as the optical path deviation and the lens distortion) of the system are accurately obtained, and the corresponding relationship between the image coordinates [u, v] collected by the high-speed imaging module and the world coordinates [X C , Y C ] is obtained. Further, by extracting the phase θ of the stripe image projected by the high-energy grating projection device, a [u, v, θ] parameter model matrix A is established, and then Z C= A*a. The coefficient a of the parameter model is calculated by the established parameter model matrix A and the known three-dimensional coordinates of the calibration plate image.

[0036] In step B1, during the synchronization signal inspection, the engine rotor is turned and it is checked whether the speed synchronization control device can normally output the synchronization signal and the high-speed imaging module can normally collect the measured rotor blade during the turning; if the engine cannot be turned, the signal inspection is performed at a low speed (600 to 3000 r / min).

[0037] In step B2, during the rotor blade stripe image collection, the rotor blade stripe images at different speeds are collected and stored according to the engine operating state.

[0038] In step B3, during the calculation of the rotor blade three-dimensional coordinates, the phase of the rotor blade stripe image is calculated based on the Fourier transform, and the specific process is as follows: reading the rotor blade stripe image, selecting the ROI region (region of interest in image processing) of the rotor blade, and windowing the image according to the image size; performing Fourier transform on the windowed image; setting the fundamental frequency center [u0, v0] and the bandwidth σ size based on the calibration data; designing a Gaussian band-pass filter based on the fundamental frequency center [u0, v0] and the bandwidth σ; performing frequency domain filtering on the windowed image using the designed band-pass filter and performing inverse Fourier transform; calculating the original phase of the inverse transformed image; using a quality-guided unwrapping method to unwrap the original phase, obtaining the unwrapped phase data and storing them.

[0039] Based on the geometric parameters, optical parameters and coefficient a obtained during calibration, according to the parameter model matrix established during calibration, the three-dimensional coordinates [X C , Y C , Z C ] of the rotor blade are solved according to the image coordinates and phase data [u, v, θ]; the three-dimensional point cloud [X C , Y C , Z C ] in the camera coordinate system is converted to the engine coordinate system [X w , Y w , Z w ].

[0040] Step B4, in calculating the three-dimensional deformation of the rotor blade based on the marker points, involves obtaining the three-dimensional coordinates of the marker points. Specifically, this is done by performing Gaussian filtering on the acquired rotor blade stripe image to remove stripe information, using a detection algorithm (such as circle recognition) to identify the marker points, obtaining their pixel coordinates, interpolating the phase data obtained in step B3 to obtain the phase of the marker points, and then solving for the three-dimensional coordinates [X] of the marker points using the coefficient 'a' obtained during calibration and the constructed parameter model matrix. TC Y TC Z TC Then transform to the engine coordinate system [X] TW Y TW Z TW ].

[0041] Based on the three-dimensional coordinates of the marker point [X] TW Y TW Z TW [X] Perform 3D point cloud mapping of rotor blades w Y w Z w Data alignment and calculation of the corresponding 3D deformation are performed as follows: The moving marker points are sorted based on the reference marker points and the corresponding rotor blade reference 3D point cloud data (this can be based on the graphic formed by the marker points). The rigid body transformation [R, t] matrix of the sorted marker points relative to the reference marker points is calculated. The rigid body transformation [R, t] is then performed on the moving 3D point cloud to obtain the aligned 3D point cloud [X]. A Y A Z A Data, aligned 3D point cloud [X] A Y A Z A ] and reference 3D point cloud [X w Y w Z w The difference is the three-dimensional deformation of the rotor blades under the corresponding conditions.

[0042] The foregoing basic examples and their further alternative examples of the present invention can be freely combined to form multiple embodiments, all of which are embodiments that can be adopted and claimed by the present invention. In the present invention, each alternative example can be arbitrarily combined with any other basic example and alternative example.

[0043] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for measuring the surface morphology and deformation of rotor blades based on FTP, characterized in that: The system includes a measurement system, which comprises a high-energy grating projection device, a high-speed imaging module, and a rotational speed synchronization control device. Measurement layout and requirements: A high-energy grating projection device combined with a high-speed imaging module is used to achieve clear imaging of aero-engine rotor blades at high speeds and high linear velocities; a speed synchronization control device is used to synchronize the acquisition of rotor blade data with the high-speed imaging module. Pre-test measurement light source and imaging quality matching assessment: After preparing according to the FTP measurement layout, the matching between the light source and imaging quality of the high-energy grating projection device and the high-speed imaging module is assessed. Obtain calibration parameters: Before measurement, the geometric and optical parameters of the system are calibrated in advance, and the corresponding calibration coefficients are obtained for later processing of test images; Measurement process and requirements: Step B1, Synchronization signal check; Step B2, Rotor blade stripe image acquisition; Step B3: Run the program to calculate the three-dimensional coordinates of the rotor blades; Step B4: Calculate the three-dimensional deformation of the rotor blades based on the marker points.

2. The method for measuring the surface morphology and deformation of rotor blades based on FTP according to claim 1, characterized in that: In the measurement layout and requirements, the high-energy grating projection device is required to have an optical power greater than 40W and the optical power is adjustable; the high-speed imaging module must achieve a minimum exposure time of 1us, and the striped image projected by the high-energy grating projection device onto the rotor blades can be clearly imaged under the 1us exposure time of the high-speed imaging module.

3. The method for measuring the surface morphology and deformation of rotor blades based on FTP according to claim 1 or 2, characterized in that: In the measurement layout and requirements, a speed sensor is installed on the stator inside the engine, and a unique circumferential mark is made on the corresponding rotor shaft. Every time the rotor rotates, the mark interacts with the speed sensor once, and the speed sensor outputs a pulse once per week. The synchronous control device generates a square wave signal once per week for synchronous phase locking of the rotor blades. The circumferential angle of the mark on the rotor shaft is consistent with the circumferential angle of the rotor blade being measured. The synchronous phase-locked signal is input to the synchronous signal port of the high-speed imaging module to ensure that the position of the rotor blades is synchronized with the acquisition of the high-speed imaging module.

4. The method for measuring the surface morphology and deformation of rotor blades based on FTP according to claim 1, characterized in that: The pre-test measurement assessment of the compatibility between the light source and the imaging quality includes: Step A1, Measurement System Setup and Debugging: Set up the FTP imaging optical path according to the measurement system, adjust the high-energy grating projection device to ensure that the stripes on the rotor blades are clearly visible, and adjust the high-speed imaging module to ensure that the stripe image is clear; Step A2, high-speed imaging module imaging quality assessment: The high-speed imaging module acquires a set of stripe images, and the stripe intensity amplitude of the stripe images is obtained by processing them with an image processing program. If the intensity amplitude is 100 or above, the intensity amplitude meets the test requirements. Otherwise, the optical power of the high-energy grating projection device needs to be increased to re-acquire and process the images until the intensity amplitude is 100 or above.

5. The method for measuring the surface morphology and deformation of rotor blades based on FTP according to claim 1, characterized in that: In obtaining calibration parameters, a single-frame fringe analysis method based on Fourier transform profilometry is used to calculate the continuous phase θ carrying the object's height information. Using the calibration method, the geometric and optical parameters of the system are accurately obtained, yielding the image coordinates [u, v] and world coordinates [X] acquired by the high-speed imaging module. C Y C The correspondence between [u, v, θ] is further established by using the phase θ of the stripe image projected by the high-energy grating projection device to establish the [u, v, θ] parameter model matrix A, then Z C= A*a, the coefficients a of the parameter model are obtained by using the constructed parameter model matrix A and the known three-dimensional coordinates of the calibration plate image.

6. The method for measuring the surface morphology and deformation of rotor blades based on FTP according to claim 1, characterized in that: In step B1, during the synchronization signal check, the engine rotor is rotated to check whether the speed synchronization control device can output a synchronization signal normally and whether the high-speed imaging module can normally acquire the rotor blades under test during the rotation process; if the engine cannot be rotated, the signal check is performed at a speed of 600 to 3000 r / min.

7. The method for measuring the surface morphology and deformation of rotor blades based on FTP according to claim 1 or 6, characterized in that: Step B2, Rotor blade stripe image acquisition: Based on the engine operating status, rotor blade stripe images at different speeds are acquired and stored.

8. The method for measuring the surface morphology and deformation of rotor blades based on FTP according to claim 1, characterized in that: Step B3: Run the program to calculate the phase of the rotor blade fringe image in the three-dimensional coordinates of the rotor blade based on Fourier transform. The specific process is as follows: Read the rotor blade fringe image, select the rotor blade ROI region, and window the image according to the image size; perform Fourier transform on the windowed image; set the fundamental frequency center [u0, v0] and bandwidth σ based on the calibration data; design a Gaussian bandpass filter based on the fundamental frequency center [u0, v0] and bandwidth σ; use the designed bandpass filter to perform frequency domain filtering on the windowed image and perform inverse Fourier transform; obtain the original phase of the image after inverse transform; use the quality-oriented unwrapping method to unwrap the original phase, obtain the unwrapped phase data, and store it. Based on the geometric parameters, optical parameters, and coefficient 'a' obtained during calibration, and according to the parameter model matrix constructed during calibration, the three-dimensional coordinates [X, V, θ] of the rotor blades are solved using image coordinates and phase data [u, v, θ]. C Y C Z C ]; The 3D point cloud in the camera coordinate system [X C Y C Z C Transform to engine coordinate system [X] w Y w Z w ]Down.

9. The method for measuring the surface morphology and deformation of rotor blades based on FTP according to claim 1 or 8, characterized in that: Step B4, in calculating the three-dimensional deformation of the rotor blade based on the marker points, the three-dimensional coordinates of the marker points are obtained. Specifically, the Gaussian filter is applied to the acquired rotor blade stripe image to remove stripe information. A detection algorithm is used to identify the marker points and obtain their pixel coordinates. The phase of the marker points is obtained by interpolation based on the phase data obtained in step B3. Then, using the coefficient 'a' obtained during calibration and the constructed parameter model matrix, the three-dimensional coordinates [X] of the marker points are solved. TC Y TC Z TC Then transform to the engine coordinate system [X] TW Y TW Z TW ]; Based on the three-dimensional coordinates of the marker point [X] TW Y TW Z TW [X] Perform 3D point cloud mapping of rotor blades w Y w Z w Data alignment and calculation of the corresponding 3D deformation are performed. Specifically, the moving marker points are sorted based on the reference marker points and their corresponding rotor blade reference 3D point cloud data. The rigid body transformation [R, t] matrix of the sorted marker points relative to the reference marker points is calculated. The rigid body transformation [R, t] is then performed on the moving 3D point cloud to obtain the aligned 3D point cloud [X]. A Y A Z A Data, aligned 3D point cloud [X] A Y A Z A ] and reference 3D point cloud [X w Y w Z w The difference is the three-dimensional deformation of the rotor blades under the corresponding conditions.

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