Structural displacement video measurement method and system based on phase cross-correlation and medium

Abstract

The invention discloses a structure displacement video measurement method and system based on phase cross-correlation and a medium. The method comprises the following steps: firstly, constructing a multi-feature amplitude by using video frame graying and morphological expansion technologies, and providing reliable feature parameters for phase cross-correlation calculation; performing coarse search by using a phase cross-correlation peak picking strategy to obtain main peak space coordinates and pixel-level displacement; fine search is carried out by using an extended phase cross-correlation difference strategy, horizontal and vertical decomposition of a cross-correlation function is completed, and differential geometric operation is carried out on a main peak and an auxiliary peak to obtain sub-pixel displacement, so that a coarse and fine search mechanism of displacement measurement is formed; an initial frame is used as a reference frame, cross-correlation operation is carried out on the reference frame and a current frame, internal and external parameters calibrated by a camera are combined, conversion from an image coordinate system to a world coordinate system is completed, and structural motion displacement measurement is accurately achieved. The method is simple to operate and flexible, displacement measurement is completed by using the shape of the structure or the natural texture, and a dense and high-precision measurement result is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of structural displacement measurement, and in particular relates to a structural displacement video measurement method, system and medium based on phase cross-correlation. Background Art

[0002] In the fields of bridge construction, aerospace and mechanical engineering, structural displacement measurement and analysis have always been of great practical significance. As an important indicator of overall structural behavior and safety, displacement can help understand its structural characteristics and evaluate structural safety by monitoring the dynamic displacement of the structure under different load types. Structural displacement measurement technology is divided into contact and non-contact types. Traditional contact technology achieves displacement measurement by installing sensors on the surface of the structure, which has disadvantages such as complex wiring, difficult installation, and low spatial resolution. At the same time, the installation of sensors will bring about mass loading effects, which may change the dynamic characteristics of the structure, resulting in a decrease in structural performance and affecting the accuracy and objectivity of the test results. Non-contact laser triangulation sensors have problems such as short measurement range and high price. The visual measurement technology combined with image processing algorithms has significant advantages such as full-field measurement, remote measurement, non-contact, low cost, and flexible use. It has become an important part of the field of non-contact structural displacement measurement technology and has broad application prospects.

[0003] In order to give full play to the significant advantages of visual measurement methods, feature-based point tracking methods and template matching methods based on digital image correlation (DIC) have provided a new perspective for structural displacement measurement technology and have been widely developed and applied. The patent with publication number CN118376162A proposes a method for measuring the displacement influence line of bridge structures based on computer vision technology, using the corner detection method to identify the feature points of the bridge structure and extract the coordinates of the feature points to track the displacement of the bridge structure. However, the point tracking technology is challenging for the number of key points extracted in a given region of interest (ROI), and the measurement results are usually sparse, which cannot meet the high-resolution requirements of displacement measurement. In addition, multiple parameters and thresholds need to be adjusted during the measurement process. The patent with publication number CN117392368A proposes a method and system for setting a region of interest for structural displacement measurement, using template matching based on DIC and evaluating ROI feature points to increase the number of ROI feature point detection and matching, and meet the needs of high-precision structural deformation measurement. However, the template matching method has the disadvantages of time-consuming calculation and the inconvenience of usually pre-setting manual markers on the structure to be measured. Summary of the invention

[0004] The object of the present invention is to provide a structural displacement video measurement method, system and medium based on phase cross-correlation.

[0005] The purpose of the present invention is achieved through the following technical solutions:

[0006] A structural displacement video measurement method based on phase cross-correlation, the specific steps are as follows:

[0007] Step 1: Use a stable light source to illuminate the structure to be tested, use a video acquisition device to record the vibration video of the structure, and grayscale the vibration video of the structure to be tested;

[0008] Step 2: Perform multi-feature processing on the grayscale video of the structure to be measured to obtain multi-feature amplitudes with more shape features than the original video frame;

[0009] Step 3: Select the region of interest from the multi-feature amplitude frame sequence and use the phase cross-correlation peak picking strategy to complete the pixel-level displacement measurement;

[0010] Step 4: Based on the phase cross-correlation peak picking strategy, the cross-correlation function is decomposed into one-dimensional signals in the horizontal and vertical directions; and then the extended phase cross-correlation difference strategy is used to complete the sub-pixel displacement measurement in the horizontal and vertical directions;

[0011] Step 5: Use the initial frame as a reference frame and perform correlation operations with subsequent frames, i.e. repeat steps 3-4, to achieve fast and accurate measurement of the vibration displacement of the test piece and generate a vibration displacement signal;

[0012] Step 6: Finally, use the internal and external parameters of the camera calibration to complete the conversion from the image coordinate system to the world coordinate system, and complete the actual measurement of vibration displacement and modal analysis.

[0013] Furthermore, in the step 1, the structure to be tested has edge features or natural textures; the vibration video grayscales the original RGB video using the formula Gray=R×0.299+G×0.587+B×0.114, where R, G, and B are the three color channel values ​​of the image respectively.

[0014] Furthermore, the multi-feature processing in step 2 includes three steps: image morphological expansion, complex amplitude model construction, and multi-feature amplitude extraction;

[0015] Step 2.1: Perform morphological processing on the grayscale video frame to dilate the image; dilate an input image I(x, y) using a structural element K to dilate the dilated image I D The calculation formula for (x,y) is:

[0016]

[0017] Where x and y represent the position of the pixel on the camera sensor plane, and ⊕ represents the morphological dilation operation;

[0018] Step 2.2: Using the original image and the expanded image as the real part and imaginary part of the complex analytical signal respectively, the construction formula of the complex amplitude model is:

[0019] I DA (x,y)=I(x,y)+iI D (x,y)

[0020] Step 2.3: Calculate the modulus of the constructed complex analysis signal to obtain the multi-feature amplitude of the original video frame. Let abs[·] represent the modulus operation, and its calculation formula is:

[0021] T(x,y)=abs[I DA (x,y)]

[0023] Furthermore, the step 3 uses a phase cross-correlation peak picking strategy to measure the pixel-level displacement signal of the vibration of the structure to be measured, specifically:

[0024] Step 3.1: selecting a region of interest (ROI) from the multi-feature amplitude sequence after the grayscale video dilation processing;

[0025] Step 3.2: Perform Fourier transform on the multi-feature amplitude ROI, and obtain the two-dimensional Single function c(x, y) according to the inverse Fourier transform of the normalized cross power spectrum. Let F represent Fourier transform, * represent conjugate operation, and the calculation formula is:

[0026]

[0027] Step 3.3: Use the peak picking method to obtain the main peak Max_peak (δ x ,δ y ) and record its coordinates (δ x ,δ y ), and then complete the pixel-level displacement measurement, let max[·] represent the maximum value operation, and its calculation formula is:

[0028] Max_peak(δ x ,δ y )=max[c(x,y)].

[0029] Furthermore, the step 4 uses an extended phase cross-correlation differential strategy to measure the sub-pixel displacement signals of the vibration of the structure to be measured in the horizontal and vertical directions, specifically:

[0030] Step 4.1: Taking the main peak coordinates of the two-dimensional Singer function c(x, y) described in step 3 as the center, perform horizontal and vertical decomposition to generate corresponding one-dimensional signals c(x) and c(y);

[0031] Step 4.2: Pick up the main peak and the secondary peak of the one-dimensional signal c(x) and c(y) respectively, and perform differential geometry operations to obtain a sub-pixel displacement with strong noise resistance, and complete the sub-pixel displacement measurement; use x main 、x sec With x third Represent the main peak and secondary peak coordinates of c(x) respectively. The analytical expression of horizontal displacement is as follows, and the same is true for vertical displacement;

[0032]

[0033] A measurement system for a structural displacement video measurement method based on phase cross-correlation, comprising an acquisition module, an expansion module, a rough measurement module, a fine measurement module and an output module;

[0034] The acquisition module includes an LED light source, a high-speed camera, a camera lens, a tripod and a computer; and is used to obtain the vibration video of the structure to be tested in step 1;

[0035] The expansion module is used to grayscale the structural vibration video in step 1; and to expand the structural vibration video in step 2 to obtain multiple characteristic amplitudes;

[0036] The rough measurement module is used for selecting a region of interest from the video after the grayscale expansion process in step 3, locating the maximum peak coordinate of the two-dimensional Singer function by using the phase cross-correlation peak picking strategy, and then measuring the pixel-level displacement signal of the vibration of the structure to be measured;

[0037] The precision measurement module is used to use the two-dimensional Singer function as input in step 4, and convert it into a one-dimensional signal, and use the extended phase cross-correlation difference strategy to measure the sub-pixel displacement signal of the vibration of the structure to be measured in the horizontal and vertical directions;

[0038] The output module is used in steps 5 and 6 to perform expansion module, coarse measurement module and fine measurement module operations on all video frames and initial frames to quickly obtain accurate and robust displacement signals, and complete the actual measurement and modal analysis of structural displacement by converting the image coordinate system to the world coordinate system.

[0039] A computer-readable storage medium stores a computer program / instruction, which, when executed by a processor, implements the steps of a structural displacement video measurement method based on phase cross-correlation.

[0040] A computer program product comprises a computer program / instruction, which, when executed by a processor, implements the steps of a method for video measurement of structural displacement based on phase cross-correlation.

[0041] An electronic device comprises: a memory for storing a computer program; and a processor for executing the computer program to implement an instruction tracking method described in a structural displacement video measurement method based on phase cross-correlation.

[0042] The beneficial effects of the present invention are:

[0043] 1. Compared with the feature-based point tracking method, the present invention is based on phase cross-correlation matching and has dense, accurate and high-resolution measurement results. By combining the phase cross-correlation peak picking strategy with the extended phase cross-correlation differential strategy, it has good robustness to environmental noise and can still show excellent measurement results in videos in noisy environments.

[0044] 2. Compared with the template matching method based on DIC, the present invention uses morphological expansion technology to increase structural features, thereby using the shape or natural texture of the structure to replace artificial marks, with simple operation and flexible measurement methods. By using frequency domain phase spectrum correlation matching, only a single match is required to achieve rapid measurement of structural displacement, effectively improving measurement efficiency and providing the possibility for real-time measurement of structural displacement. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic diagram of the overall workflow of the present invention;

[0046] Figure 2 It is a schematic diagram of the process flow of the multi-feature amplitude extraction method of the present invention;

[0047] Figure 3 It is a schematic diagram of the phase cross-correlation peak picking strategy flow of the present invention;

[0048] Figure 4 It is a schematic diagram of the extended phase cross-correlation differential strategy flow of the present invention;

[0049] Figure 5 This is a simulation picture of an underdamped oscillating sphere;

[0050] Figure 6 is the displacement measurement result of the present invention;

[0051] Figure 7 To actually take a picture of the cantilever beam in the camera plane;

[0052] Figure 8 This is the actual measurement result of the present invention. DETAILED DESCRIPTION

[0053] The present invention is further described below in conjunction with the accompanying drawings.

[0054] See also Figures 1 to 4, this embodiment provides a structural displacement video measurement method based on phase cross-correlation. The technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0055] The hardware used in the phase cross-correlation-based structural displacement video measurement method of the present invention includes an LED light source, a high-speed camera, a camera lens, a tripod and a computer. Before the test, the monocular camera is calibrated. This is a one-time work, and the purpose is to obtain the conversion coefficient between the image coordinate system and the world coordinate system using the monocular camera calibration principle. The conversion coefficient is obtained based on the intrinsic parameters of the camera and the extrinsic parameters between the camera and the moving structure. The internal parameters mainly include the focal length, pixel size, etc. of the camera, and the external parameters mainly include the object distance.

[0056] When working, Figure 1 As shown, the structural displacement video measurement method based on phase cross-correlation of the present invention comprises the following steps:

[0057] Step 1: Use a stable light source to illuminate the structure to be tested. The structure to be tested should have edge features or natural textures, and use a video acquisition device to record the vibration of the structure;

[0058] Step 2: Obtain a vibration video of the structure to be tested, and grayscale the vibration video. The original RGB video is grayscaled using the formula Gray=R×0.299+G×0.587+B×0.114, where R, G, and B are the three color channel values ​​of the image respectively;

[0059] Step 3: Perform multi-feature processing on the grayscale video of the structure to be tested, including three steps: image morphological expansion, complex amplitude model construction, and multi-feature amplitude extraction, to obtain multi-feature amplitudes with more shape features than the original video frame, such as Figure 2 As shown, specifically:

[0060] (1) Performing morphological processing on the grayscale video frame to dilate the image; dilating an input image I(x, y) using a structural element K to dilate the dilated image I D The calculation formula for (x,y) is:

[0061]

[0062] where x and y represent the position of the pixel on the camera sensor plane, represents the morphological dilation operation;

[0063] (2) Using the original image and the expanded image as the real part and imaginary part of the complex analytical signal respectively, the construction formula of the complex amplitude model is:

[0064] I DA (x,y)=I(x,y)+iI D (x,y)

[0065] (3) Calculate the modulus value of the constructed complex analytical signal to obtain the multi-feature amplitude of the original video frame. Let abs[·] represent the modulus operation, and its calculation formula is:

[0066] T(x,y)=abs[I DA (x,y)]

[0067] Step 4: Select the region of interest from the multi-feature amplitude frame sequence and use the phase cross-correlation peak picking strategy to complete the pixel-level displacement measurement, such as Figure 3 As shown, specifically:

[0068] (1) selecting a region of interest (ROI) from the multi-feature amplitude sequence after the grayscale video dilation processing;

[0069] (2) Performing Fourier transform on the multi-feature amplitude ROI, obtaining a two-dimensional Single function c(x, y) according to the inverse Fourier transform of the normalized cross power spectrum, represents Fourier transform, * represents conjugate operation, and the calculation formula is:

[0070]

[0071] (3) The peak picking method is used for the c(x, y) to obtain the main peak Max_peak(δ x ,δ y ) and record its coordinates (δ x ,δ y ), and then complete the pixel-level displacement measurement; let max[·] represent the maximum value operation, and its calculation formula is:

[0072] Max_peak(δ x ,δ y )=max[c(x,y)]

[0073] Step 5: Based on the phase cross-correlation peak picking strategy, the cross-correlation function is decomposed into one-dimensional signals in the horizontal and vertical directions. With the main peak coordinates of the two-dimensional Singer function c(x,y) as the center, the horizontal and vertical decomposition is performed to generate the corresponding one-dimensional signals c(x) and c(y);

[0074] Step 6: Use the extended phase cross-correlation differential strategy to quickly, accurately and robustly complete the sub-pixel displacement measurement in the horizontal and vertical directions. Pick the main peak and the secondary peak of the one-dimensional signal c(x) and c(y) respectively, and perform differential geometry operations to complete the sub-pixel displacement measurement, such as Figure 4 As shown. Use x main 、x sec With x third They represent the main peak and secondary peak coordinates of c(x) respectively. The analytical expression for the horizontal displacement is as follows, and the same is true for the vertical displacement.

[0075]

[0076] Step 7: Use the initial frame as a reference frame and perform correlation operations with subsequent frames, that is, repeat steps 4-6 to achieve fast and accurate measurement of the vibration displacement of the test piece and generate a vibration displacement signal;

[0077] Step 8: Use the conversion factors obtained from the internal and external parameters of the camera calibration to complete the conversion from the image coordinate system to the world coordinate system, and complete the actual measurement of vibration displacement and modal analysis.

[0078] The present invention also proposes a structural displacement video measurement system based on phase cross-correlation, the system comprising:

[0079] Module 1: Acquisition module, which obtains the vibration video of the structure to be tested according to the content described in step 1;

[0080] Module 2: Expansion module, according to the contents described in steps 2 and 3, is used to pre-process the structural vibration video, including video grayscale and expansion structure processing, to obtain multi-feature amplitudes;

[0081] Module 3: a rough measurement module, according to the content described in step 4, is used to select a region of interest from the video after the grayscale expansion processing, locate the maximum peak coordinate of the two-dimensional Singer function by using the phase cross-correlation peak picking strategy, and then measure the pixel-level displacement signal of the vibration of the structure to be measured;

[0082] Module 4: The fine measurement module, according to the contents described in steps 5 and 6, uses the two-dimensional Singer function of the rough measurement module as input and converts it into a one-dimensional signal, and uses the extended phase cross-correlation difference strategy to measure the sub-pixel displacement signal of the vibration of the structure to be measured in the horizontal and vertical directions;

[0083] Module 5: Output module, according to the contents described in steps 7 and 8, performs the expansion module, coarse measurement module and fine measurement module operations on all video frames and initial frames to quickly obtain accurate and robust displacement signals, and completes the actual measurement of structural displacement and modal analysis through the conversion from image coordinate system to world coordinate system.

[0084] In the first embodiment, a method for measuring structural displacement video based on phase cross-correlation is specifically provided, and its steps are shown in the flowchart. Figure 1-4 As shown, the sample preparation and measurement results of the embodiment are as follows: a circular sphere with a radius of 128 pixels is simulated and generated, and the sphere is made to vibrate underdamped in the horizontal direction, with an amplitude of 10 pixels, an attenuation factor of 1 / 30, a frame rate of 200, and a video with a duration of 1 second is generated, as shown in FIG. Figure 5 As shown. The linear expansion operator is selected, which is generally more common. The video frame sequence is frame by frame to construct multi-feature amplitudes. The phase cross-correlation peak picking strategy is used to complete the pixel-level displacement measurement, and the extended phase cross-correlation difference strategy is used to complete the sub-pixel displacement measurement. Because the simulation sample does not involve the conversion factor of the world-image coordinate system, the actual motion field is directly obtained. The time domain measurement results are shown in Figure 6 Comparing the errors between the simulation setting data and the calculation data of the present invention, the RMSE calculation result is 0.028 pixels.

[0085] In the second embodiment, a method for measuring structural displacement video based on phase cross-correlation is specifically provided, and its steps are shown in the flowchart. Figure 1-4 As shown, the sample preparation and measurement results of the embodiment are as follows: prepare a cantilever beam with a length of 50 cm, and use a hammer to excite the bottom of the cantilever beam. Use a digital camera or mobile phone to capture and record the vibration process of the cantilever beam to obtain a video containing the vibration information of the cantilever beam. At the same time, use a contact method (triangle light laser sensor measurement) to measure the vibration of the object to be measured as a comparison reference value. During the acquisition process, the acquisition frame rate is set to 1000, and an LED light source is used for supplementary lighting. The overall structure is as follows Figure 7 As shown. Select the linear expansion operator, which is generally more common. Construct multi-feature amplitudes frame by frame in the video frame sequence. Use the phase cross-correlation peak picking strategy to complete the pixel-level displacement measurement, and use the extended phase cross-correlation difference strategy to complete the sub-pixel displacement measurement. The conversion factor between the actual displacement of the object under test in the actual space plane and the motion size (pixel) of the object in the camera plane at the actual measurement distance is 0.2248 mm / pixel. Multiply the time series absolute motion displacement field by the conversion scale factor to obtain the actual motion field. The time domain measurement result is as follows Figure 8 As shown, by comparing the error between the actual measured data and the calculated data of the present invention, the RMSE calculation result is 0.0164 mm.

[0086] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for measuring structural displacement video based on phase cross-correlation, characterized in that: The specific steps are as follows: Step 1: Use a stable light source to illuminate the structure to be tested, use a video acquisition device to record the vibration video of the structure, and grayscale the vibration video of the structure to be tested; Step 2: Perform multi-feature processing on the grayscale video of the structure to be measured to obtain multi-feature amplitudes with more shape features than the original video frame; Step 3: Select the region of interest from the multi-feature amplitude frame sequence and use the phase cross-correlation peak picking strategy to complete the pixel-level displacement measurement; Step 4: Based on the phase cross-correlation peak picking strategy, the cross-correlation function is decomposed into one-dimensional signals in the horizontal and vertical directions; and then the extended phase cross-correlation difference strategy is used to complete the sub-pixel displacement measurement in the horizontal and vertical directions; Step 5: Use the initial frame as a reference frame and perform correlation operations with subsequent frames, i.e. repeat steps 3-4, to achieve fast and accurate measurement of the vibration displacement of the test piece and generate a vibration displacement signal; Step 6: Finally, use the internal and external parameters of the camera calibration to complete the conversion from the image coordinate system to the world coordinate system, and complete the actual measurement of vibration displacement and modal analysis.

2. The method for measuring structural displacement by video based on phase cross-correlation according to claim 1, characterized in that: In step 1, the structure to be tested has edge features or natural textures; the vibration video grayscales the original RGB video using the formula Gray=R×0.299+G×0.587+B×0.114, where R, G, and B are the three color channel values ​​of the image respectively.

3. The method for measuring structural displacement by video based on phase cross-correlation according to claim 1, characterized in that: The multi-feature processing in step 2 includes three steps: image morphological expansion, complex amplitude model construction, and multi-feature amplitude extraction; Step 2.1: Perform morphological processing on the grayscale video frame to dilate the image; dilate an input image I(x, y) using a structural element K to dilate the dilated image I D The calculation formula for (x,y) is: Where x and y represent the position of the pixel on the camera sensor plane, represents the morphological dilation operation; Step 2.2: Using the original image and the expanded image as the real part and imaginary part of the complex analytical signal respectively, the construction formula of the complex amplitude model is: I DA (x,y)=I(x,y)+iI D (x,y) Step 2.3: Calculate the modulus of the constructed complex analysis signal to obtain the multi-feature amplitude of the original video frame. Let abs[·] represent the modulus operation, and its calculation formula is: T(x,y)=abs[I DA (x,y)]。 4. The method for measuring structural displacement by video based on phase cross-correlation according to claim 1, characterized in that: The step 3 uses a phase cross-correlation peak picking strategy to measure the pixel-level displacement signal of the vibration of the structure to be measured, specifically: Step 3.1: selecting a region of interest (ROI) from the multi-feature amplitude sequence after the grayscale video dilation processing; Step 3.2: Perform Fourier transform on the multi-feature amplitude ROI, and obtain the two-dimensional Single function c(x, y) according to the inverse Fourier transform of the normalized cross power spectrum. represents Fourier transform, * represents conjugate operation, and the calculation formula is: Step 3.3: Use the peak picking method to obtain the main peak Max_peak (δ x ,δ y ) and record its coordinates (δ x ,δ y ), and then complete the pixel-level displacement measurement, let max[·] represent the maximum value operation, and its calculation formula is: Max_peak(δ x ,δ y )=max[c(x,y)]。 5. The method for measuring structural displacement by video based on phase cross-correlation according to claim 1, characterized in that: The step 4 uses an extended phase cross-correlation differential strategy to measure the sub-pixel displacement signals of the vibration of the structure to be measured in the horizontal and vertical directions, specifically: Step 4.1: Taking the main peak coordinates of the two-dimensional Singer function c(x, y) described in step 3 as the center, perform horizontal and vertical decomposition to generate corresponding one-dimensional signals c(x) and c(y); Step 4.2: Pick up the main peak and the secondary peak of the one-dimensional signal c(x) and c(y) respectively, and perform differential geometry operations to obtain a sub-pixel displacement with strong noise resistance, and complete the sub-pixel displacement measurement; use x main 、x sec With x third Represent the main peak and secondary peak coordinates of c(x) respectively. The analytical expression of horizontal displacement is as follows, and the same is true for vertical displacement; 6. A measurement system for a structural displacement video measurement method based on phase cross-correlation according to any one of claims 1 to 5, characterized in that: It includes acquisition module, expansion module, rough measurement module, fine measurement module and output module; The acquisition module includes an LED light source, a high-speed camera, a camera lens, a tripod and a computer; and is used to obtain the vibration video of the structure to be tested in step 1; The expansion module is used to grayscale the structural vibration video in step 1; and to expand the structural vibration video in step 2 to obtain multiple characteristic amplitudes; The rough measurement module is used for selecting a region of interest from the video after the grayscale expansion process in step 3, locating the maximum peak coordinate of the two-dimensional Singer function by using the phase cross-correlation peak picking strategy, and then measuring the pixel-level displacement signal of the vibration of the structure to be measured; The precision measurement module is used to use the two-dimensional Singer function as input in step 4, and convert it into a one-dimensional signal, and use the extended phase cross-correlation difference strategy to measure the sub-pixel displacement signal of the vibration of the structure to be measured in the horizontal and vertical directions; The output module is used in steps 5 and 6 to perform expansion module, coarse measurement module and fine measurement module operations on all video frames and initial frames to quickly obtain accurate and robust displacement signals, and complete the actual measurement and modal analysis of structural displacement by converting the image coordinate system to the world coordinate system.

7. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer program product comprising a computer program / instructions, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

9. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the instruction tracing method according to any one of claims 1 to 5.

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