Shock wave overpressure field global measurement method based on multi-view image fusion

Abstract

The invention discloses a shock wave overpressure field global measurement method based on multi-view image fusion, belongs to the technical field of explosive shock wave measurement, and is suitable for weapon equipment power evaluation and blasting safety analysis. The method comprises the following steps of: synchronously acquiring a time sequence image of the whole explosion process through a distributed multi-view high-speed imaging system, preprocessing the image by adopting pixel-by-pixel comparison, square operation enhancement and normalization processing, and positioning a shock wave edge contour; the blasting center coordinate is positioned through binocular parallax, the shock wave initial radius is determined by combining spatial domain analysis, and the key feature points of the front and rear edges of the wavefront are detected by using a dynamic search window and a radial gradient field. Based on multi-view constraints, a three-dimensional point cloud is generated through direct linear triangulation, and a three-dimensional wave front form is reconstructed in combination with least square spherical fitting. And finally, constructing a wavefront radius-time evolution model, and deducing a quantitative relationship between the instantaneous propagation velocity and the peak overpressure in combination with a Ranki ne-Huton iot relationship, thereby realizing the global high-precision calculation of the overpressure field.

Description

Technical Field

[0001] The present invention belongs to the technical field of explosion shock wave overpressure measurement, and specifically relates to a full-domain measurement method of shock wave overpressure field based on multi-view image fusion, which is applicable to the fields of weapon and equipment power assessment, mine blasting safety assessment, etc. Background Art

[0002] Shock wave overpressure is a key parameter for assessing the destructive power of weapons and equipment and a core physical parameter for evaluating the terminal effectiveness of high-efficiency weapon systems. Its quantitative characterization is directly related to the energy release characteristics and damage mechanisms of ammunition explosions. Shock wave overpressure acquisition systems are crucial instruments for effectively acquiring shock wave overpressure signals and objectively and accurately evaluating the destructive power of weapon systems and engineering blasts. Currently, mainstream shock wave overpressure testing methods fall into two categories: centralized lead-line electrical measurement and distributed storage testing. In the centralized lead-line electrical measurement method, sensors and multi-channel acquisition systems are installed separately. Multiple sensors are connected to the terminal data acquisition system via long-axis cables, and signals are transmitted via these cables. In the distributed storage testing method, sensors and data acquisition systems are installed in an integrated manner. This method reduces cable length compared to the lead-line testing method and enhances interference resistance.

[0003] However, with the increasing demand for rapid deployment and rapid evaluation in actual combat exercises, existing testing methods have the following problems:

[0004] 1. High testing costs and low deployment efficiency: Traditional electrical testing methods rely on a centralized wired transmission architecture, requiring the installation of numerous specialized cables and connectors at each test point. This is costly and cumbersome. Furthermore, in explosive environments, flying shrapnel and high-temperature flames can easily damage cables and connectors, necessitating the installation of additional protective devices, further increasing overall costs and hindering rapid deployment.

[0005] 2. Inadequate real-time shock wave data processing: Traditional electrical measurement methods require data to be transmitted via cables to a backend for offline processing. This prevents rapid data processing and on-site visualization of reconstruction results after the explosion. This severely limits the rapid assessment of damage effectiveness and the efficiency of decision-making and response during training exercises or actual combat.

[0006] 3. Low shock wave field measurement accuracy: Traditional shock wave testing methods are limited by the number of sensors and layout conditions, resulting in sparse data points and difficulty in accurately characterizing the spatiotemporal evolution characteristics of the shock wave overpressure field. In particular, significant measurement errors will occur in areas where the wavefront curvature changes dramatically, seriously affecting the accuracy of shock wave field reconstruction and the reliability of damage assessment. Summary of the Invention

[0007] In order to solve the defects in the prior art, the present invention discloses a method for measuring the global shock wave overpressure field based on multi-view image fusion. The technical solution is as follows:

[0008] A method for measuring the global shock wave overpressure field based on multi-view image fusion, characterized by comprising the following steps:

[0009] Step S1: Acquire multi-view shock wave images. By deploying a distributed multi-view high-speed imaging system, synchronously acquire time-series image data of the entire explosion process from multiple viewpoints to visualize the shock wave propagation process.

[0010] Step S2: Preprocessing the shock wave image by performing pixel-by-pixel comparison calculation and square operation to enhance feature differences, and combining average normalization to eliminate image noise, generating new pixel values ​​reflecting local contrast to determine the preliminary position of the shock wave edge contour;

[0011] Step S3: Extracting key parameters of the shock wave front, including accurately locating the center of the explosion based on the principle of binocular parallax, calculating the Euclidean distance between each pixel in the image and the center of the explosion through spatial domain analysis, and determining the initial radius of the shock wave based on the statistical distribution characteristics of the distance;

[0012] Step S4: Detect key feature points of the shock wave front, accurately capture the leading and trailing edge positions of the wave front through dynamic search window adaptive adjustment, radial gradient field calculation, and positive and negative gradient extreme value calibration, and provide high-precision feature point data for 3D reconstruction;

[0013] Step S5: Reconstruct the three-dimensional wavefront under multi-view constraints, generate a three-dimensional point cloud using a direct linear triangulation method, and accurately describe the three-dimensional shape and expansion law of the shock wavefront through a least squares spherical fitting model;

[0014] Step S6: Calculate the shock wave overpressure field. Based on the wavefront radius and time series of adjacent frames, construct a wavefront radius-time evolution model, derive the instantaneous propagation velocity, and establish a quantitative relationship between the overpressure peak and velocity in combination with the Rankine-Hugoniot relationship to complete the global characterization of the overpressure field.

[0015] The present invention also discloses a global measurement system for shock wave overpressure fields based on multi-view image fusion, which is characterized by comprising:

[0016] A distributed multi-camera high-speed imaging system is used to synchronously capture time-series images of the entire explosion process, acquiring time-series image data of the entire explosion process from multiple perspectives to visualize the shock wave propagation process;

[0017] The preprocessing module is used to enhance image feature differences and eliminate brightness deviations. It enhances feature differences through pixel-by-pixel comparison calculation and square operation, and combines average normalization processing to eliminate image noise. It generates new pixel values ​​that reflect local contrast to determine the preliminary position of the shock wave edge contour;

[0018] The parameter extraction module extracts key parameters of the shock wave front, including accurately locating the coordinates of the explosion center based on the principle of binocular parallax, calculating the Euclidean distance between each pixel in the image and the explosion center through spatial domain analysis, analyzing the statistical distribution characteristics of the distance, and determining the initial radius of the shock wave;

[0019] The feature detection module is used to dynamically search and calibrate key feature points of the wavefront. Through dynamic search window adaptive adjustment, radial gradient field calculation, and positive and negative gradient extreme value calibration, it accurately captures the leading and trailing edge positions of the wavefront, providing high-precision feature point data for 3D reconstruction.

[0020] The 3D reconstruction module is used to generate a 3D point cloud and fit a spherical model. It reconstructs the 3D wavefront under multi-view constraints, generates a 3D point cloud using a direct linear triangulation method, and accurately describes the 3D shape and expansion law of the shock wavefront through a least squares spherical fitting model.

[0021] The overpressure field calculation module is used to construct a wavefront spatiotemporal evolution model and derive the overpressure peak value; calculate the shock wave overpressure field, construct a wavefront radius-time evolution model based on the wavefront radius and time series of adjacent frames, derive the instantaneous propagation velocity, and establish a quantitative relationship between the overpressure peak value and velocity in combination with the Rankine-Hugoniot relationship to complete the global characterization of the overpressure field.

[0022] Beneficial effects

[0023] 1. Improved deployment efficiency and cost-effectiveness: The distributed, non-contact optical measurement system eliminates the cumbersome wired connections and high hardware costs of traditional electrical measurement methods. This makes it particularly suitable for the rapid deployment and withdrawal requirements of combat training. The system's simple structure and flexible deployment eliminate the need for complex protective measures, significantly enhancing the measurement system's mobility and adaptability.

[0024] 2. Rapid data acquisition and on-site visualization: By synchronously capturing images of the entire explosion process with a high-speed camera and combining them with image processing and model fitting algorithms, the shock wavefront structure and propagation characteristics can be quickly acquired and reconstructed after the explosion. This allows for rapid on-site assessment and real-time decision-making, meeting the timeliness requirements of the modern battlefield.

[0025] 3. Improved data density and measurement accuracy: Multi-camera technology enables multi-angle observation of the shock wavefront, effectively addressing the sparse location of traditional sensors. Combined with wavefront fitting models and propagation characteristics modeling, it accurately reflects changes in wavefront curvature, enabling high-precision reconstruction of wavefront morphology and overpressure fields, and improving the reliability of damage assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 Schematic diagram of the steps for optical measurement of overpressure field;

[0027] Figure 2 Schematic diagram of shock wave overpressure field measurement scene;

[0028] Figure 3 This is a schematic diagram of the coordinates of the explosion center using binocular positioning. DETAILED DESCRIPTION

[0029] Based on the propagation mechanism of explosion shock waves in air media, this paper proposes a global measurement method of shock wave overpressure field based on multi-view image fusion, which realizes high-precision measurement and characterization of explosion shock wave overpressure field through optical non-contact measurement. Figure 1 As shown, the specific implementation is as follows:

[0030] S1. Collect multi-view shock wave images, see Figure 2 As shown;

[0031] A distributed multi-camera high-speed imaging system was deployed at a ground observation point 300 meters from the explosion epicenter. This system simultaneously captured time-series image data of the entire explosion process from multiple perspectives and angles, visualizing the propagation of the shock wave. The distributed multi-camera high-speed imaging system consists of three core modules: an image acquisition subsystem, an image storage and transmission subsystem, and a central control subsystem.

[0032] 1. Image acquisition subsystem:

[0033] The system comprises two high-performance high-speed cameras and their associated accessories, along with a drone high-speed imaging subsystem. The main camera captures time-series images of the explosion's shock wave propagation, while the auxiliary camera forms a stereoscopic vision measurement system with the main camera, enabling precise positioning of the target area and calculation of spatial coordinates. The drone high-speed imaging subsystem consists of a multi-rotor drone, a high-speed camera, an optoelectronic pod, and an optoelectronic conversion and transmission module.

[0034] 2. Image storage and transmission subsystem:

[0035] Each high-speed camera is equipped with two high-speed storage devices, which are transmitted to the central control subsystem via optical fiber.

[0036] 3. Central control subsystem:

[0037] Integrate multiple control computers for data processing to achieve centralized control and collaborative work of the system.

[0038] S2, preprocessing shock wave image;

[0039] The dynamic detonation process is converted into multiple static images. Using a pixel-by-pixel comparison method, the grayscale values ​​of corresponding pixels in the reference image ref(x,y) are compared with those in the target image obj(x,y). This method introduces a square operation into the differential calculation of adjacent frames to enhance feature differences. It also uses average normalization to eliminate deviations caused by changes in overall image brightness. Ultimately, a new pixel value pic(x,y) is generated that reflects the local contrast between the two images, thereby determining the approximate location of the shock wave edge contour in the target image.

[0040]

[0041] S3, extracting key parameters of the shock wave front;

[0042] S3.1, binocular camera intersection positioning explosion center coordinates, see Figure 3 shown

[0043] In order to accurately locate the center of gravity in the image processed by S2, a binocular positioning technology based on the parallax principle is used. The binocular camera synchronously collects the left and right views to form a binocular convergent stereo vision measurement solution. Based on the parallax-depth formula:

[0044]

[0045] Convert the disparity map to a depth map and calculate the center of gravity coordinates using the intrinsic parameter matrix. Here, Z represents depth, f is focal length, B is baseline distance, and d is disparity.

[0046] S3.2. Calculate the initial radius of the shock wave within the explosion area

[0047] Through spatial domain analysis, the Euclidean distance D(i,j) between each pixel in the image and the explosion center is calculated:

[0048]

[0049] Where (i0, j0) represents the coordinates of the explosion center, and (i, j) represents the coordinates of any pixel in the image. Based on probability density analysis, the statistical distribution characteristics of the shock wave radius are analyzed to determine the initial shock wave radius.

[0050] S4. Detect key feature points of the shock wave front

[0051] Taking the explosion center obtained in S3.1 as the origin and the radius calculated in S3.2 as the initial radius, an automatic detection algorithm based on a dynamic search mechanism is proposed to extract the key feature points of the wavefront. The specific steps are as follows:

[0052] 1. Initialize the search window: The initial search box size is set to 10% of the initial radius.

[0053] 2. Adaptive search box adjustment: The search box size is adaptively adjusted to accommodate changes in the shock wave radius based on the asymmetry of the wavefront, the proximity to the fireball, and the level of background noise.

[0054] 3. Calculate the radial gradient field: Use the inverse difference method to calculate the light intensity gradient value in each search box. The positive gradient extreme value corresponds to the compression area at the trailing edge of the shock wave, and the negative gradient mutation accurately calibrates the leading edge position of the wavefront.

[0055] 4. Output key feature points of the wavefront: For the detected shock wave front, the positions of the detected feature points are marked in a visual manner.

[0056] S5, reconstructing the three-dimensional wavefront under multi-view constraints;

[0057] S5.1. Generate 3D point cloud

[0058] The direct linear triangulation (DLT) method is used to reconstruct the 3D spatial position of the key feature points captured by different cameras at the same time in step S4. Using the image point coordinates under multiple perspectives and the camera projection matrix, the spatial point X = [X, Y, Z, 1] is solved. T ∈R 4 , so that its projection into multiple cameras is consistent with the known image points. For each camera i, there is a corresponding camera projection matrix P i ∈R 3×4 , there is an image point x i =[u i ,v i ,1] T ∈R 3 , satisfying the projection relationship:

[0059] x i ~P i X(4)

[0060] By constructing the following linear equations to eliminate the scale factor, we obtain an over-reduced constraint system about X:

[0061]

[0062] in, Represents the matrix P iThe j-th row vector of , j = 1, 2, 3. Solve the over-constrained linear system for all cameras and use singular value decomposition (SVD) to obtain the spatial point X∈R 4 The homogeneous coordinates of are used to obtain the three-dimensional shock wave point cloud.

[0063] S5.2. 3D Wavefront Reconstruction Based on Spherical Fitting

[0064] To further characterize the shock wave structure, a spherical fitting method is proposed for the point cloud reconstructed by S5.1. The goal is to fit an optimal spherical model in the sense of least squares, and its mathematical expression is:

[0065] (xx c ) 2 +(yy c ) 2 +(zz c ) 2 =r 2 (6)

[0066] Where (x c ,y c ,z c ) is the coordinate of the center of the fitting sphere, and r is the radius of the sphere. By expanding the equation and algebraically rearranging it, it can be converted into a linear fitting form:

[0067] x 2 +y 2 +z 2 =β1x+β2y+β3z+β4 (7)

[0068] The fitting parameters β1, β2, β3, β4 have the following relationship with the center and radius of the sphere:

[0069] β1=2x c (8)

[0070] β2=2y c (9)

[0071] β3=2z c (10)

[0072]

[0073] Assume that the input point cloud has N points (x i ,y i ,z i ), construct the matrix form:

[0074]

[0075] Solve a system of linear equations using the method of least squares:

[0076] A·β=b (13)

[0077] Get the optimal fitting parameters β=[β1,β2,β3,β4] T , the coordinates of the sphere center and radius are directly calculated from the fitting coefficients:

[0078]

[0079] S6. Calculate the shock wave overpressure field;

[0080] In the dynamic observation of explosion shock waves, the entire process can be regarded as a sequence of N frames with different wavefront radii. The wavefront radius between adjacent frames and the time sequence of images acquired by a high-speed camera are used to construct a wavefront radius-time evolution model to quantitatively describe the spatiotemporal expansion law of the shock wave front. Let the acquisition time corresponding to the i-th frame be t i :

[0081]

[0082] Where t0 is the first frame time, f is the camera frame rate; the radius between the shock wave front and the explosion center in the i-th frame is recorded as r i .based on For discrete data, use forward differencing to approximate instantaneous velocity:

[0083]

[0084] Will A continuous model r = r(t) is constructed to describe the evolution of the wavefront radius over time. Numerical differentiation is performed on it to derive the instantaneous propagation velocity V of the shock wave at a certain moment:

[0085]

[0086] According to the Rankine-Hugoniot relationship, the relationship between the peak overpressure of the shock wave and the wavefront diffusion velocity is:

[0087]

[0088] Among them, p1 is the gas pressure behind the wave, p0 is the gas pressure before the wave, that is, the static pressure of air, γ represents the adiabatic index, ρ0 represents the air density before the wave, and c0 represents the speed of sound. According to the speed of sound equation, the density ρ0 is replaced by the variable related to the speed of sound

[0089]

[0090] When p1 does not exceed 50 atmospheres, the adiabatic index γ is taken as 1.4 without considering its change, and the formula can be further simplified to deduce the shock wave peak overpressure Δp m The relationship with the propagation speed V is:

[0091]

[0092] The present invention proposes a global measurement method for shock wave overpressure fields based on multi-perspective image fusion. The entire explosion process is captured using clock-synchronized distributed multi-camera high-speed cameras. An automatic detection algorithm is used to extract key feature points of the shock wave front from each frame of the image, and three-dimensional point cloud data is constructed under the constraints of multi-perspective observation. In the time series dimension, the wavefront parameters between adjacent frames are used to construct a wavefront radius-time model and a propagation velocity-time model to form an instantaneous velocity field. Based on the theory of explosion dynamics, a wavefront peak overpressure-propagation velocity model is further derived to form an instantaneous overpressure field.

[0093] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions merely illustrate the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for measuring the global shock wave overpressure field based on multi-view image fusion, characterized in that: The following steps are involved: S1: Acquire multi-view shock wave images. By deploying a distributed multi-view high-speed imaging system, the time-series image data of the entire explosion process can be acquired synchronously from multiple perspectives. S2: Preprocess the shock wave image by performing pixel-by-pixel comparison calculations and square operations to enhance feature differences, and combine this with average normalization to eliminate image noise, generate new pixel values ​​reflecting local contrast, and determine the preliminary position of the shock wave edge contour. S3: Extract the key parameters of the shock wave front and determine the initial radius of the shock wave; S4: Detect key feature points of the shock wave front and capture the leading and trailing edge positions of the wave front through dynamic search window adaptive adjustment, radial gradient field calculation, and positive and negative gradient extreme value calibration; S5: Reconstruct the three-dimensional wavefront under multi-view constraints, generate a three-dimensional point cloud using the direct linear triangulation method, and describe the three-dimensional morphology and expansion law of the shock wavefront through the least squares spherical fitting model; S6: Calculate the shock wave overpressure field, construct a wavefront radius-time evolution model based on the wavefront radius and time series of adjacent frames, derive the instantaneous propagation velocity, establish a quantitative relationship between the overpressure peak and velocity, and complete the global characterization of the overpressure field.

2. The method according to claim 1, characterized in that The step S1 specifically includes: A distributed multi-eye high-speed imaging system is deployed at a ground observation point at a certain distance from the explosion center. The system includes: Image acquisition subsystem: includes high-performance high-speed cameras and supporting equipment, and a UAV high-speed camera subsystem, used to synchronously capture time-series images of explosion shock wave propagation from multiple perspectives; Image storage and transmission subsystem: includes high-speed image storage equipment, field optical fiber, optical fiber retraction and extension device, special optical fiber and high-speed synchronization controller, used to ensure real-time storage and stable transmission of image data; Central control subsystem: Integrates multiple control computers to achieve centralized system control and multi-module collaborative work.

3. The method according to claim 1, characterized in that The method for pre-processing the shock wave image in step S2 is: The grayscale values ​​of corresponding pixels in the reference image and the target image are compared pixel by pixel, and the square operation is introduced to enhance the feature difference. The image noise is eliminated through average normalization processing, and new pixel values ​​reflecting the local contrast are generated to determine the edge contour position of the shock wave.

4. The method according to claim 1, wherein The step S3 comprises: Step S3.1: Calculate the coordinates of the ground zero based on the parallax-depth formula of the binocular camera to provide a spatial reference for subsequent wavefront parameter extraction; Step S3.2: Through spatial domain analysis, the Euclidean distance between each pixel in the image and the explosion epicenter is calculated, and the initial radius of the shock wave is determined based on probability density analysis, providing initial parameters for modeling the dynamic expansion of the wavefront.

5. The method according to claim 4, characterized in that The parallax-depth formula in step S3.1 is: Where Z represents the depth, f is the focal length, B is the baseline distance, and d is the parallax, which is used to convert binocular parallax into three-dimensional coordinates of the ground zero.

6. The method according to claim 1, characterized in that The specific steps of detecting the key characteristic points of the shock wave front in step S4 are: Initialize the search window to 10% of the initial radius to limit the initial detection range; Adaptively adjust the search box size based on wavefront asymmetry, proximity to the fireball, and background noise level to improve the robustness of feature point detection; The radial gradient field is calculated by the reverse difference method, and the leading and trailing edges of the wavefront are accurately calibrated by the positive gradient extreme value and negative gradient mutation. Output visually annotated feature point positions to provide a high-confidence data source for 3D reconstruction.

7. The method according to claim 1, characterized in that The step S5 comprises: Step S5.1: Using the direct linear triangulation method, the coordinates of the multi-view image points and the camera projection matrix are used to solve the 3D point cloud and realize the spatial fusion of the multi-view observation data; Step S5.2: Perform least squares spherical fitting on the three-dimensional point cloud to obtain the coordinates and radius of the sphere center and accurately reconstruct the three-dimensional geometric shape of the shock wave front.

8. The method according to claim 7, characterized in that The mathematical expression of spherical fitting in step S5.2 is: (x-x c ) 2 +(y-y c ) 2 +(z-z c ) 2 =r 2 (7) After expanding into a linear system, the coordinates and radius of the sphere center are solved by the least squares method: Used to quantify the spatial expansion characteristics of the wavefront; where (x c ,y c ,z c ) are the coordinates of the center of the fitting sphere, r is the radius of the sphere; fitting parameters β1, β2, β3, β4.

9. The method according to claim 1, characterized in that The step S6 comprises: A wavefront radius-time evolution model is constructed based on the wavefront radius and time series of adjacent frames to quantitatively describe the spatiotemporal laws of shock wave propagation. The instantaneous propagation velocity is approximated by forward difference, and a velocity-time dynamic model is established; Combined with the Rankine-Hugoniot relationship, the shock wave peak overpressure Δp is derived m The simplified formula of the propagation velocity V is used to achieve high-precision calculation of the overpressure field over the entire domain: Among them, p1 is the gas pressure behind the wave, p0 is the gas pressure before the wave, that is, the static pressure of air, and c0 represents the speed of sound.

10. A shock wave overpressure field global measurement system based on multi-view image fusion, characterized in that: include: A distributed multi-camera high-speed imaging system is used to synchronously capture time-series images of the entire explosion process, acquiring time-series image data of the entire explosion process from multiple perspectives to visualize the shock wave propagation process; The preprocessing module is used to enhance image feature differences and eliminate brightness deviations. It enhances feature differences through pixel-by-pixel comparison calculation and square operation, and combines average normalization processing to eliminate overall image brightness changes. It generates new pixel values ​​that reflect local contrast to determine the preliminary location of the shock wave edge contour; The parameter extraction module extracts key parameters of the shock wave front, including accurately locating the coordinates of the explosion center based on the principle of binocular parallax, calculating the Euclidean distance between each pixel in the image and the explosion center through spatial domain analysis, and determining the initial radius of the shock wave based on the statistical distribution characteristics of the distance; The feature detection module is used to dynamically search and calibrate key feature points of the wavefront. Through dynamic search window adaptive adjustment, radial gradient field calculation, and positive and negative gradient extreme value calibration, it accurately captures the leading and trailing edge positions of the wavefront, providing high-precision feature point data for 3D reconstruction. The 3D reconstruction module is used to generate a 3D point cloud and fit a spherical model. It reconstructs the 3D wavefront under multi-view constraints, generates a 3D point cloud using a direct linear triangulation method, and accurately describes the 3D shape and expansion law of the shock wavefront through a least squares spherical fitting model. The overpressure field calculation module is used to construct a wavefront spatiotemporal evolution model and derive the overpressure peak value; calculate the shock wave overpressure field, construct a wavefront radius-time evolution model based on the wavefront radius and time series of adjacent frames, derive the instantaneous propagation velocity, and establish a quantitative relationship between the overpressure peak value and velocity in combination with the Rankine-Hugoniot relationship to complete the global characterization of the overpressure field.

11. A non-volatile storage medium, characterized in that: The non-volatile storage medium includes a stored program, wherein when the program is executed, the device where the non-volatile storage medium is located is controlled to execute the method according to any one of claims 1 to 9.

12. An electronic device, characterized in that: The method comprises a processor and a memory; the memory stores computer-readable instructions, and the processor is used to execute the computer-readable instructions, wherein the computer-readable instructions execute the method according to any one of claims 1 to 9 when executed.

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