Thin-wall structure damage positioning method and device based on curvature modal shape

Abstract

The invention belongs to the technical field of structural damage positioning, and particularly relates to a thin-wall structural damage positioning method and device based on curvature modal shape. The method comprises the following steps: S1, obtaining modal shape data of a structure; s2, calculating a curvature modal shape corresponding to the modal shape data by using a Gaussian-Laplacian operator; s3, decomposing the curvature modal shape into a low-rank matrix L and a damage position indication matrix B, and performing spatial continuity constraint on the matrix B by using a Markov random field; and S4, determining a low-rank matrix L by taking the fact that the rank of the low-rank matrix L is smaller than a set value as a target, solving a damage position indication matrix B by using a first-order Markov random field model, and performing damage positioning according to the damage position indication matrix B. According to the method, a reference signal in a healthy state is not needed, the robustness to noise is improved, and the damage feature information in the multi-order modal shape can be fused and processed.

Description

Technical Field

[0001] The present application belongs to the technical field of structural damage location, and in particular relates to a method and device for locating damage in a thin-walled structure based on curvature modal vibration type. Background Art

[0002] With the widespread use of thin-walled structures such as metals and composite materials in the aerospace field, how to ensure their service status through inspection and maintenance has become an important issue. Among the vibration-based structural health monitoring methods, damage localization methods based on curvature mode vibration shapes have been widely studied due to their high sensitivity to local damage. Although such methods have made great progress, in practical applications, such methods themselves have poor robustness to measurement noise, and the curvature mode based on the finite difference of the modal vibration shape further amplifies the impact of noise, making it difficult for such methods to obtain reliable damage localization results. Secondly, the traditional damage localization technology based on curvature mode vibration shape lacks the understanding of the spatial characteristic distribution of damage, does not constrain the spatial continuity characteristics of the damage area, and cannot efficiently and accurately extract the characteristics of the damage area. In addition, a single curvature mode vibration shape is only sensitive to damage in a local area, and it is difficult to cover the damage localization task in the entire area. Summary of the invention

[0003] In order to solve the above problems, the present application provides a thin-walled structure damage location method and device based on curvature mode vibration type to solve the defect of inaccurate feature extraction of damaged area.

[0004] The first aspect of the present application provides a thin-walled structure damage location method based on curvature mode vibration shape, which mainly includes:

[0005] Step S1, obtaining modal vibration data of the structure;

[0006] Step S2, using Gauss-Laplace operator to calculate the curvature mode shape corresponding to the mode shape data;

[0007] Step S3, decomposing the curvature mode vibration shape into a low-rank matrix L and a damage position indication matrix B, wherein the damage position indication matrix B takes a value of 1 in the damaged area and a value of 0 in the healthy area, and using a Markov random field to constrain the spatial continuity of the matrix B;

[0008] Step S4: first determine the low-rank matrix L with the rank of the low-rank matrix L being less than a set value as the goal, then use the first-order Markov random field model to solve the damage position indication matrix B, and locate the damage based on the damage position indication matrix B.

[0009] Preferably, step S1 further comprises:

[0010] Step S11, obtaining the resonant frequency of the thin-walled structure by frequency sweeping;

[0011] Step S12, using the same resonance frequency to excite the thin-walled structure;

[0012] Step S13: using laser scanning technology to obtain high spatial resolution modal vibration shape data.

[0013] Preferably, in step S2, when the Gaussian-Laplacian operator is used to process the modal vibration shape data, the Gaussian filter scale factor used is 1.5.

[0014] Preferably, step S4 further includes:

[0015] The damage position indicator matrix B value corresponding to the multi-order modal vibration shapes is calculated, and the damage index of the damaged location is determined by averaging.

[0016] The second aspect of the present application provides a thin-walled structure damage location device based on curvature mode vibration shape, mainly comprising:

[0017] A modal vibration shape data acquisition module is used to acquire the modal vibration shape data of the structure;

[0018] A curvature mode shape calculation module is used to calculate the curvature mode shape corresponding to the mode shape data using the Gauss-Laplace operator;

[0019] The curvature mode shape decomposition module is used to decompose the curvature mode shape into a low-rank matrix L and a damage location indicator matrix B, where the damage location indicator matrix B takes a value of 1 in the damaged area and a value of 0 in the healthy area. The Markov random field is used to constrain the spatial continuity of the matrix B.

[0020] The matrix solving module is used to first determine the low-rank matrix L with the rank of the low-rank matrix L being less than a set value as the goal, and then use a first-order Markov random field model to solve the damage position indication matrix B, and locate the damage according to the damage position indication matrix B.

[0021] Preferably, the modal vibration shape data acquisition module includes:

[0022] A resonance frequency determination unit, used for obtaining the resonance frequency of the thin-walled structure by frequency sweeping;

[0023] an excitation unit for exciting the thin-walled structure using the same resonance frequency;

[0024] The laser scanning unit is used to obtain high spatial resolution modal vibration shape data using laser scanning technology.

[0025] Preferably, in the curvature mode shape calculation module, when the Gaussian-Laplacian operator is used to process the mode shape data, the Gaussian filter scale factor used is 1.5.

[0026] Preferably, the device further comprises:

[0027] Preferably, the damage index of the damaged location is determined by calculating the damage position indication matrix B value corresponding to the multi-order modal vibration shapes by averaging.

[0028] A third aspect of the present application provides a computer device, characterized in that it includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the thin-walled structure damage location method based on curvature modal vibration type as described above.

[0029] A fourth aspect of the present application provides a readable storage medium, which stores a computer program, characterized in that when the computer program is executed by a processor, it is used to implement the thin-walled structure damage location method based on curvature mode vibration type as described above.

[0030] The present application does not require a reference signal in a healthy state, improves robustness to noise, and can integrate and process damage feature information in multi-order modal vibration shapes. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a flow chart of a preferred embodiment of the thin-walled structure damage location method based on curvature mode vibration type of the present application.

[0032] Figure 2 Schematic diagram of a single-sided clamped plate with two damaged areas.

[0033] Figure 3 It is a schematic diagram of the normalized results of the 10th-order mode shape of the plate.

[0034] Figure 4 It is a schematic diagram of the 10th curvature mode vibration shape of the plate.

[0035] Figure 5 This is a schematic diagram of the sparse matrix of the 10th-order curvature mode obtained using only RPCA.

[0036] Figure 6 It is a schematic diagram of the RPCA damage location results under the 10th-order curvature mode considering the continuity constraint of the damage space.

[0037] Figure 7 It is a schematic diagram of damage localization results that integrates multi-modal vibration damage information.

[0038] Figure 8It is a schematic diagram of the structure of a computer device suitable for implementing the embodiments of the present application. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical scheme and advantages of the implementation of this application clearer, the technical scheme in the implementation of this application will be described in more detail in combination with the drawings in the implementation of this application. In the drawings, the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The described implementation is a part of the implementation of this application, not all of the implementations. The implementation described below with reference to the drawings is exemplary and is intended to be used to explain this application, and cannot be understood as a limitation on this application. Based on the implementation in this application, all other implementations obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. The implementation of this application is described in detail below in combination with the drawings.

[0040] This application provides a thin-walled structure damage location method based on curvature mode vibration shape, such as Figure 1 As shown, it mainly includes:

[0041] Step S1, obtaining modal vibration data of the structure;

[0042] Step S2, using Gauss-Laplace operator to calculate the curvature mode shape corresponding to the mode shape data;

[0043] Step S3, decomposing the curvature mode vibration shape into a low-rank matrix L and a damage position indication matrix B, wherein the damage position indication matrix B takes a value of 1 in the damaged area and a value of 0 in the healthy area, and using a Markov random field to constrain the spatial continuity of the matrix B;

[0044] Step S4: first determine the low-rank matrix L with the rank of the low-rank matrix L being less than a set value as the goal, then use the first-order Markov random field model to solve the damage position indication matrix B, and locate the damage based on the damage position indication matrix B.

[0045] The present application example is a metal aluminum plate containing two local area damages, such as Figure 2 As shown, the aluminum plate size is 0.35×0.23×0.003m 3 , Young's modulus E = 69 GPa, Poisson's ratio v = 0.35, mass density ρ = 2700 kg / m 3 Ten percent of the thickness of the opposite sides of the two damaged areas marked with square patterns were cut off to simulate damage. In addition, the left side of the aluminum plate was clamped and the right side of the plate was excited with a shaker (LDS V406) to obtain its mode shape data.

[0046] In some optional implementations, step S1 further includes:

[0047] Step S11, obtaining the resonant frequency of the thin-walled structure by frequency sweeping;

[0048] Step S12, using the same resonance frequency to excite the thin-walled structure;

[0049] Step S13: using laser scanning technology to obtain high spatial resolution modal vibration shape data.

[0050] In this embodiment, in order to determine the resonant frequency of the aluminum plate, a PSV-500 laser scanning system is used to generate a random signal of 0 to 2000 Hz to excite the aluminum plate. Taking the 10th order mode as an example, the 10th order resonant frequency of the aluminum plate, 798 Hz, is used for excitation, and the PSV-500 laser scanning system is used to measure the velocity of each point on the surface of the aluminum plate. The excitation frequency is set to 798 Hz, the acquisition signal bandwidth is set to 300 Hz, and the relevant modal vibration shape data Φ(x, y) is obtained. The normalized results of the modal vibration shape are shown in the attached Figure 3 .

[0051] Then, in step S2, the Gaussian-Laplace operator is used to process the modal vibration shape, and by selecting a suitable scale factor σ, the noise-resistant curvature modal vibration shape is obtained, which is expressed as follows:

[0052]

[0053] Where, the mode vibration shape is Φ(x,y), σ is the Gaussian filter scale factor, represents the convolution operator. Among them, the Gaussian-Laplacian operator is as follows:

[0054]

[0055] In some optional implementations, in step S2, when the Gaussian-Laplacian operator is used to process the modal vibration data, the Gaussian filter scale factor used is 1.5, and the Gaussian-Laplacian operator with a scale parameter σ=1.5 is convolved with the modal vibration data Φ(x, y) to calculate the curvature modal vibration of the 10th order vibration mode. The calculation result is as follows: Figure 4 shown.

[0056] After that, in step S3, the curvature mode shape decomposition is performed. Here, the prior art is first introduced, and the traditional robust principal component analysis method (RPCA) is used to extract the local shape distortion characteristics induced by damage from the curvature mode shape of the damaged thin-walled structure. The core idea is to decompose the curvature mode shape Φ″d of the damaged thin-walled structure into a low-rank matrix L and a sparse matrix S (damage feature information). The solution process is as follows:

[0057] minimise||L|| * +ξ||S||1 obeys||Φ″ d -LS|≤∈;

[0058] Where ξ is the equilibrium parameter, ||L|| * is the kernel norm of matrix L, ||S||1 is the l1 norm of matrix S; the sparse matrix S obtained by traditional robust principal component analysis method is shown in the attached Figure 5 , it can be seen that the damage location result is not high. The present application uses an improved robust principal component analysis method based on spatial continuity constraints (see the following formula) to decompose the curvature mode vibration shape Φ″d under the damage state into a low-rank matrix L and a damage location indication matrix B. The damage location result of the 10th-order vibration shape obtained by using the improved robust principal component analysis is shown in the attached Figure 6 .

[0059] Damage in thin-walled structures usually occurs in a limited and continuous area. Therefore, when calculating the sparse matrix S, a spatial continuity constraint can be imposed on the damage features in the matrix S. Here, the matrix B is used as the damage location indicator matrix to replace the original sparse matrix S. The matrix B takes the value of 1 only in the damaged area and the value of 0 in the healthy area. The Markov random field is used to constrain the spatial continuity of the matrix B. According to the Ising model, the energy of the matrix B can be expressed as:

[0060] Σu ij (B ij )+Σ <ij，kl> λ ij，kl |B ij -B kl |;

[0061] In the formula, u ij represents the binary characteristics of matrix B, λ ij，kl Indicates the degree of dependence of the continuous area on its adjacent measurement points, where u ij It is expressed as:

[0062]

[0063] Respectively ij and λ ij，kl Write as β and γ, and finally get the robust principal component analysis model considering the local space continuity constraint improvement. The calculation of matrix L and B is transformed into solving the optimization problem as follows:

[0064]

[0065] Finally, the above optimization problem is solved. It can be understood that it is difficult to jointly optimize and solve L and B at the same time. Therefore, in step S4, the present application adopts an alternating step-by-step optimization method. First, the low-rank matrix L is determined, and then the damage area indication matrix B is solved as a standard form of a first-order Markov random field. The solution can be completed by image segmentation.

[0066] Specifically, the values ​​of parameters α, β, and γ are iteratively solved: parameter α controls the complexity of the healthy curvature mode vibration shape. The larger the parameter α, the lower the complexity of the representation; parameter β indicates the influence of noise; parameter γ controls the spatial continuity of matrix B. The SOFT-IMPUTE algorithm can effectively identify the optimal L. The parameter r sets the size of the original curvature mode vibration matrix to r = min (m1, m2). The parameter α can set the second largest singular value. The matrix L obtained by the SOFT-IMPUTE algorithm is divided by parameter α. Until rank(L)>r is satisfied, the parameter β usually takes a larger value and is reduced by one time each iteration until it reaches 4.5σ 2 , σ 2 M ij -L ij The parameter γ usually takes the same value as the parameter β.

[0067] Finally, the damage localization index can be expressed by the following formula:

[0068]

[0069] In some optional implementations, step S4 further includes:

[0070] The damage position indicator matrix B value corresponding to the multi-order modal vibration shapes is calculated, and the damage index of the damaged location is determined by averaging.

[0071] In this embodiment, for N r The curvature of the order mode is used to calculate the robust multi-damage index DI ij :

[0072]

[0073] The damage location index S of each coordinate (i, j) of each mode of the multi-order mode ij It is either 0 or 1. After arithmetic averaging, its value is between 0 and 1, thus showing the degree of damage at the coordinate point. The area formed by multiple coordinate points forms an intuitive regional damage map in the form of a curved surface.

[0074] For example, the damage information of the 10th and 13th modal vibration modes is combined to calculate the robust multi-damage index DI ijThe damage location results based on multi-order modal vibration shape fusion are shown in the attached Figure 7 .

[0075] This application has made innovations in three aspects: multi-scale curvature modal vibration shape calculation, robust principal component analysis method with spatial constraint improvement, and damage localization index integrating multi-order modal vibration shapes, thereby improving the damage localization accuracy and noise resistance performance based on curvature modal vibration shapes.

[0076] The second aspect of the present application provides a thin-walled structure damage location device based on curvature mode vibration shape corresponding to the above method, mainly comprising:

[0077] A modal vibration shape data acquisition module is used to acquire the modal vibration shape data of the structure;

[0078] A curvature mode shape calculation module is used to calculate the curvature mode shape corresponding to the mode shape data using the Gauss-Laplace operator;

[0079] The curvature mode shape decomposition module is used to decompose the curvature mode shape into a low-rank matrix L and a damage location indicator matrix B, where the damage location indicator matrix B takes a value of 1 in the damaged area and a value of 0 in the healthy area. The Markov random field is used to constrain the spatial continuity of the matrix B.

[0080] The matrix solving module is used to first determine the low-rank matrix L with the rank of the low-rank matrix L being less than a set value as the goal, and then use a first-order Markov random field model to solve the damage position indication matrix B, and locate the damage according to the damage position indication matrix B.

[0081] In some optional implementations, the modal vibration shape data acquisition module includes:

[0082] A resonance frequency determination unit, used for obtaining the resonance frequency of the thin-walled structure by frequency sweeping;

[0083] an excitation unit for exciting the thin-walled structure using the same resonance frequency;

[0084] The laser scanning unit is used to obtain high spatial resolution modal vibration shape data using laser scanning technology.

[0085] In some optional implementations, in the curvature mode shape calculation module, when the Gaussian-Laplacian operator is used to process the mode shape data, the Gaussian filter scale factor used is 1.5.

[0086] In some optional embodiments, the device further comprises:

[0087] The damage index calculation module is used to calculate the damage position indicator matrix B value corresponding to the multi-order modal vibration shape, and determine the damage index of the damaged part by averaging.

[0088] In a third aspect of the present application, a computer device includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a thin-walled structure damage location method based on curvature mode vibration type.

[0089] In a fourth aspect of the present application, a readable storage medium stores a computer program, and when the computer program is executed by a processor, it is used to implement the thin-walled structure damage location method based on curvature mode vibration type as described above. The computer readable storage medium may be included in the device described in the above embodiment; or it may exist independently without being assembled into the device. The above computer readable storage medium carries one or more programs, and when the above one or more programs are executed by the device, the data is processed according to the above method.

[0090] Reference below Figure 8 , which shows a schematic structural diagram of a computer device 400 suitable for implementing the embodiments of the present application. Figure 8 The computer device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0091] like Figure 8 As shown, the computer device 400 includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage part 408 into a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the device 400 are also stored. The CPU 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0092] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed, so that a computer program read therefrom is installed into the storage section 408 as needed.

[0093] In particular, according to the embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 409, and / or installed from the removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, the above functions defined in the method of the present application are executed. It should be noted that the computer storage medium of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, - but not limited to - a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, an apparatus or a device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in combination with an instruction execution system, an apparatus or a device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0094] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0095] The modules or units involved in the embodiments described in this application may be implemented by software or hardware. The modules or units described may also be set in a processor, and the names of these modules or units do not constitute limitations on the modules or units themselves in some cases.

[0096] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A thin-walled structure damage location method based on curvature mode vibration shape, characterized in that: include: Step S1, obtaining modal vibration data of the structure; Step S2, using Gauss-Laplace operator to calculate the curvature mode shape corresponding to the mode shape data; Step S3, decomposing the curvature mode vibration shape into a low-rank matrix L and a damage position indication matrix B, wherein the damage position indication matrix B takes a value of 1 in the damaged area and a value of 0 in the healthy area, and using a Markov random field to constrain the spatial continuity of the matrix B; Step S4: first determine the low-rank matrix L with the rank of the low-rank matrix L being less than a set value as the goal, then use the first-order Markov random field model to solve the damage position indication matrix B, and locate the damage based on the damage position indication matrix B.

2. The thin-walled structure damage location method based on curvature mode vibration shape according to claim 1, characterized in that: Step S1 further comprises: Step S11, obtaining the resonant frequency of the thin-walled structure by frequency sweeping; Step S12, using the same resonance frequency to excite the thin-walled structure; Step S13: using laser scanning technology to obtain high spatial resolution modal vibration shape data.

3. The thin-walled structure damage location method based on curvature mode vibration shape according to claim 1, characterized in that: In step S2, when the Gaussian-Laplacian operator is used to process the modal vibration shape data, the Gaussian filter scale factor used is 1.

5.

4. The thin-walled structure damage location method based on curvature mode vibration shape according to claim 1, characterized in that: Step S4 further includes: The damage position indicator matrix B value corresponding to the multi-order modal vibration shapes is calculated, and the damage index of the damaged location is determined by averaging.

5. A thin-walled structure damage location device based on curvature mode vibration shape, characterized in that: include: A modal vibration shape data acquisition module is used to acquire the modal vibration shape data of the structure; A curvature mode shape calculation module is used to calculate the curvature mode shape corresponding to the mode shape data using the Gauss-Laplace operator; The curvature mode shape decomposition module is used to decompose the curvature mode shape into a low-rank matrix L and a damage location indicator matrix B, where the damage location indicator matrix B takes a value of 1 in the damaged area and a value of 0 in the healthy area. The Markov random field is used to constrain the spatial continuity of the matrix B. The matrix solving module is used to first determine the low-rank matrix L with the rank of the low-rank matrix L being less than a set value as the goal, and then use a first-order Markov random field model to solve the damage position indication matrix B, and locate the damage according to the damage position indication matrix B.

6. The thin-walled structure damage location device based on curvature mode vibration shape according to claim 5, characterized in that: The modal vibration shape data acquisition module includes: A resonance frequency determination unit, used for obtaining the resonance frequency of the thin-walled structure by frequency sweeping; an excitation unit for exciting the thin-walled structure using the same resonance frequency; The laser scanning unit is used to obtain high spatial resolution modal vibration shape data using laser scanning technology.

7. The thin-walled structure damage location device based on curvature mode vibration shape according to claim 5, characterized in that: In the curvature mode shape calculation module, when the Gaussian-Laplacian operator is used to process the mode shape data, the Gaussian filter scale factor used is 1.

5.

8. The thin-walled structure damage location device based on curvature mode vibration shape according to claim 5, characterized in that: The device also includes: The damage index calculation module is used to calculate the damage position indicator matrix B value corresponding to the multi-order modal vibration shape, and determine the damage index of the damaged part by averaging.

9. A computer device, characterized in that: The invention comprises a processor, a memory and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the thin-walled structure damage location method based on curvature mode vibration shape as described in any one of claims 1 to 4.

10. A readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, it is used to implement the thin-walled structure damage location method based on curvature mode vibration shape as described in any one of claims 1 to 4.

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