Vibration testing method for health monitoring of underground structure

Abstract

The invention relates to the field of structure health monitoring, in particular to a vibration testing method for underground structure health monitoring. The method comprises the following steps: capturing a vibration signal of an underground structure in real time, and carrying out denoising and feature extraction on the vibration signal by adopting space-time wavelet decomposition to obtain a decomposed signal; based on the decomposed signals, a health state model of the underground structure is constructed through weighted regression, and the health state of the underground structure is evaluated; calculating a stiffness matrix, a mass matrix and a damping matrix of the underground structure based on the health state of the underground structure; and the damage of the underground structure is evaluated by establishing a dynamic response model of the underground structure. The problem that the damage position and degree of an underground structure cannot be comprehensively and accurately reflected due to the fact that an existing structure health monitoring technology is difficult to effectively remove noise and extract detail features of signals, cannot dynamically adapt to changes of the health state of the structure and cannot combine various modal parameters for comprehensive damage evaluation is solved.

Description

Technical Field

[0001] The present invention relates to the field of structural health monitoring, and particularly to a vibration testing method for underground structural health monitoring. Background Art

[0002] With the acceleration of the urbanization process, the construction of underground projects is increasing day by day, such as subways, tunnels, underground parking lots, and pipelines. The safety and stability of these underground structures are directly related to the normal operation of urban infrastructure and the life and property safety of citizens. Therefore, how to effectively monitor and evaluate the health status of underground structures has become an urgent problem to be solved. Traditional methods for underground structural health monitoring usually rely on manual inspection or regular inspection. This method is not only inefficient but also unable to monitor the status of the structure in real time and may miss some sudden damages or potential safety hazards. Therefore, there is an urgent need for a more efficient and real-time monitoring technology that can continuously and real-time collect vibration signals during the operation of underground structures and evaluate the health status of the structure through accurate signal analysis.

[0003] In recent years, with the continuous progress of sensing technology and data processing technology, structural health monitoring technology based on vibration signals has gradually been applied. Since vibration signals are closely related to the dynamic characteristics of structures, they can effectively reflect the health status of structures. Especially when monitoring underground structures, vibration signals can provide important bases for damage location, identification, and evaluation. However, existing technologies face certain limitations in practical applications. For example, they cannot flexibly monitor and analyze the complexity and changing working environment of underground structures, and it is difficult to ensure high precision and high timeliness during signal acquisition and processing. Therefore, how to optimize vibration signal acquisition, improve the accuracy of signal processing, and comprehensively evaluate the health status of underground structures through analysis has become an important research direction in current technologies. Summary of the Invention

[0004] The present invention provides a vibration testing method for underground structural health monitoring to solve the problems that existing structural health monitoring technologies mostly rely on traditional frequency-domain analysis or time-domain analysis methods, making it difficult to effectively remove noise and extract detailed features of signals; ignoring the time-varying characteristics of vibration signals and failing to dynamically adapt to changes in the health status of structures, resulting in low accuracy of health status estimation; and failing to combine multiple modal parameters for comprehensive damage assessment, resulting in the inability to comprehensively and accurately reflect the damage location and degree of underground structures.

[0005] The vibration testing method for underground structural health monitoring includes the following steps:

[0006] S1. Capture the vibration signals of the underground structure in real time, perform denoising and feature extraction on the vibration signals using spatio-temporal wavelet decomposition to obtain the decomposed signals; based on the decomposed signals, construct a health state model of the underground structure through weighted regression to evaluate the health state of the underground structure;

[0007] S2. Based on the health state of the underground structure, calculate the stiffness matrix, mass matrix and damping matrix of the underground structure; and evaluate the damage of the underground structure by establishing a dynamic response model of the underground structure.

[0008] Preferably, the S1 specifically includes:

[0009] During the spatio-temporal wavelet decomposition of the vibration signals, extract the local features of the vibration signals at different time and space positions through spatio-temporal wavelet transform to obtain the spatio-temporal wavelet transform result.

[0010] Preferably, the S1 specifically includes:

[0011] In the spatio-temporal wavelet transform, introduce a reconstruction factor, adjust the resolution of the vibration signals during the spatio-temporal wavelet transform according to the local changes of the vibration signals in the spatio-temporal domain, and obtain the final spatio-temporal wavelet transform result through the spatio-temporal wavelet transform formula with the reconstruction factor; the spatio-temporal wavelet transform formula with the reconstruction factor is:

[0012]

[0013] where, W ψ (a, b, t, s) is the final spatio-temporal wavelet transform result; a and b are respectively used to control the scale and offset; t represents time; s represents the space position; x(t, s) is the vibration signal of the underground structure; r(t, s) is the reconstruction factor; ψ a，b (t, s) is the spatio-temporal wavelet basis function.

[0014] Preferably, the S1 specifically includes:

[0015] Perform hierarchical decomposition on the final spatio-temporal wavelet transform result using the time-frequency joint analysis method to obtain the features of the vibration signals in different time periods and frequency ranges.

[0016] Preferably, the S1 specifically includes:

[0017] The mathematical representation of the health state model of the underground structure is:

[0018]

[0019] where, Y(t, s) represents the health state of the underground structure, indicating the health state estimation of the underground structure at time t and space position s; N is the number of decomposition levels; Xi (t, s) is the decomposition result of the vibration signal at the i-th level; w i (t, s) is the weighting coefficient, representing X i (t, s) is the weight at different positions and times; ∈(t, s) is the regression error term.

[0020] Preferably, the S1 specifically includes:

[0021] The weighting coefficient in the health state model of the underground structure is dynamically adjusted with the change of time and spatial position, and the specific formula is:

[0022]

[0023] where t′ is the adjacent time of time t; Y(t′, s) represents the health state estimation of the underground structure at time t′ and spatial position s; λ is the regularization term.

[0024] Preferably, the S2 specifically includes:

[0025] The health state of the underground structure affects the modal parameters for damage assessment, and the modal parameters include the stiffness, mass and damping of the underground structure; when damage occurs, the stiffness, mass and damping of the underground structure will change, thus affecting the response of the underground structure.

[0026] Preferably, the S2 specifically includes:

[0027] External excitation is a factor affecting the vibration of the underground structure, and the influence of the external excitation is adjusted based on the health state of the underground structure.

[0028] Preferably, the S2 specifically includes:

[0029] Adopt the modal recursive partial differential equation method to establish the dynamic response model of the underground structure; the change of the health state of the underground structure corresponding to the vibration of the underground structure is used as a feedback mechanism in the solution of the modal recursive partial differential equation, and the feedback mechanism is realized through the following formula:

[0030]

[0031] where is the acceleration of the underground structure at time t and position s; F(t, s) is the external excitation acting on the underground structure at time t and position s; C(t, s) is the damping matrix of the underground structure at time t and position s; is the vibration velocity of the underground structure at time t and position s; K(t, s) is the stiffness matrix of the underground structure at time t and position s; u(t, s) is the vibration displacement of the underground structure at time t and position s; M(t, s) is the mass matrix of the underground structure at time t and position s; and is the feedback regulation coefficient; Y(t, s) represents the health state of the underground structure, indicating the health state estimation of the underground structure at time t and spatial position s; Y(t′, s) is the health state estimation of the underground structure at time t′ and spatial position s; t′ is the adjacent time of time t; is the attenuation factor.

[0032] The beneficial effects of the technical solution of the present invention are as follows:

[0033] 1. By arranging acceleration sensors at key nodes of the underground structure, the vibration signals of the underground structure can be captured in real time, and time-frequency wavelet decomposition is used to denoise and extract features from the vibration signals, thereby improving the accuracy of the health assessment of the underground structure; through multi-level decomposition and time-frequency joint analysis of the vibration signals, the vibration characteristics of the underground structure at different times and spatial positions can be effectively extracted, helping to identify potential damage areas and quantitatively evaluate the severity of the damage.

[0034] 2. A health state model of the underground structure is established based on the weighted regression method, enabling the relationship between the vibration signals and the health state of the underground structure to be dynamically adjusted, adapting to the time-varying characteristics of the vibration signals of the underground structure, and flexibly responding to local changes, thereby providing accurate health state estimation; by integrating the health state into the modal recursive partial differential equation and combining the changes in modal parameters such as the stiffness, mass, and damping of the underground structure, the dynamic response of the underground structure can be more realistically reflected, ensuring the timely discovery and quantification of damage to the underground structure during the damage assessment process.

[0035] 3. By comprehensively using the vibration test results and health state estimation, combined with damage mode analysis, global and local damage assessments of the underground structure are provided; by monitoring the change trend of the health state, the damage location and degree of the structure can be inferred, which helps to achieve early warning and preventive maintenance of the underground structure. Description of the Drawings

[0036] Figure 1 is the flowchart of the vibration test method for health monitoring of the underground structure described in the present invention. Detailed Embodiments

[0037] To further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0038] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0039] The following specifically describes in conjunction with the drawings the specific solution of the vibration test method for underground structure health monitoring provided by the present invention.

[0040] Refer to the attached Figure 1 , which shows the flow chart of the vibration test method for underground structure health monitoring provided by an embodiment of the present invention. The method includes the following steps:

[0041] S1. Real-time capture the vibration signal of the underground structure, perform denoising and feature extraction on the vibration signal using spatio-temporal wavelet decomposition to obtain the decomposed signal; based on the decomposed signal, construct a health state model of the underground structure through weighted regression to evaluate the health state of the underground structure;

[0042] Arrange acceleration sensors at different parts of the underground structure to real-time capture the acceleration data of the underground structure during vibration and generate vibration signals; the arrangement of acceleration sensors needs to consider the geometric characteristics and potential vibration modes of the underground structure. Usually, acceleration sensors are arranged at the key nodes and vulnerable areas of the underground structure, such as joints, parts with larger deformation or possible force concentration.

[0043] The acquisition frequency of the vibration signal needs to be optimized according to the natural frequency of the underground structure and the frequency characteristics of the external excitation source to ensure that the main vibration modes of the underground structure can be captured. Usually, the sampling frequency should be set to more than twice the vibration frequency of the underground structure to ensure meeting the requirements of the Nyquist sampling theorem and thus avoid signal aliasing. In addition, during the data acquisition process, attention should also be paid to the influence of environmental noise, and signal filtering and noise suppression technologies should be used to ensure that the collected vibration signals can truly reflect the vibration response of the underground structure.

[0044] The vibration signal of the underground structure collected is denoted as x(t, s), where t represents time and s represents spatial position. Taking x(t, s) as the input signal into the processing flow; the vibration signal undergoes multi-level spatio-temporal wavelet decomposition for denoising and feature extraction to enhance the structural health information in the vibration signal and remove noise; the multi-level spatio-temporal wavelet decomposition first extracts the local features of the vibration signal at different time and spatial positions through spatio-temporal wavelet transform, thus helping with damage assessment in subsequent analysis. The spatio-temporal wavelet transform can be described by the following formula:

[0045]

[0046] where, is the result of spatio-temporal wavelet transform, representing the projection of the vibration signal x(t, s) and the spatio-temporal wavelet basis function ψ a，b (t, s) at a given scale a and offset b; ψ a，b (t, s) is the spatio-temporal wavelet basis function, and a and b are used to control the scale and offset respectively to determine the frequency range and position range of signal decomposition. Through multi-scale and multi-position wavelet transform, important feature information of the vibration signal in the time domain, frequency domain, and spatial domain is extracted.

[0047] In spatio-temporal wavelet transform, the local characteristics of the vibration signal have an important impact on the result of spatio-temporal wavelet transform. To improve the local adaptability of spatio-temporal wavelet transform, a reconstruction factor is introduced, which can automatically adjust the resolution of the vibration signal during spatio-temporal wavelet transform according to the local changes of the vibration signal in the spatio-temporal domain. Specifically, the reconstruction factor dynamically assigns more appropriate weights to different regions by measuring the gradient changes of the vibration signal in the time and space dimensions. The gradient reflects the amplitude of the change of the vibration signal. In the region with a large change amplitude, its reconstruction factor will increase accordingly, thus enhancing the spatio-temporal resolution of the region. The specific formula is as follows:

[0048]

[0049] where, r(t, s) is the reconstruction factor; γ is a regulation factor used to control the influence degree of the gradient; the gradients and represent the local change amplitudes of the vibration signal in the time and space dimensions respectively. Through the reconstruction factor, the dynamic changes of the vibration signal are fully considered, enabling the resolution of spatio-temporal wavelet transform to be intelligently adjusted and optimized.

[0050] The introduction of the reconstruction factor enables spatio-temporal wavelet transform to dynamically adjust its resolution according to the local features of the vibration signal, making spatio-temporal wavelet transform have higher time and space resolution in regions with high change amplitudes, while reducing the computational burden in regions with stable change amplitudes. The formula of spatio-temporal wavelet transform with the reconstruction factor is:

[0051]

[0052] W ψ (a, b, t, s) is the final spatio-temporal wavelet transform result; ψ a，b (t, s) is the spatio-temporal wavelet basis function; a and b are used to control the scale and offset respectively; the weight of the spatio-temporal wavelet basis function is affected by the reconstruction factor, so as to realize the adaptive enhancement of the local characteristics of the vibration signal.

[0053] The final spatio-temporal wavelet transform result is hierarchically decomposed by using the time-frequency joint analysis method to obtain the fine characteristics of the vibration signal in different time periods and frequency ranges, so as to remove the low-frequency noise and strengthen the details of the high-frequency signal. The hierarchical decomposition is carried out through the following formula:

[0054]

[0055] where X(t, s) is the decomposed signal, representing the vibration characteristics of the underground structure at time t and spatial position s; N is the number of decomposition levels; a i is the scale at the i-th layer of decomposition; b i is the offset at the i-th layer of decomposition; W ψ (a i , b i , t, s) is the final spatio-temporal wavelet transform result, representing the projection of the vibration signal x(t, s) and the spatio-temporal wavelet basis function ψ a，b (t, s) at the given scale a i and offset b i ; is the Fourier transform coefficient of the vibration signal, representing the component of the vibration signal at frequency f i ; f i is the frequency parameter at the i-th layer of decomposition, representing the specific frequency component of the vibration signal in the frequency domain. The signal of each layer represents the vibration characteristics of different frequencies and spatial positions. Through multi-level decomposition, not only the low-frequency noise is removed, but also the ability to capture the health characteristics of the structure is enhanced.

[0056] After the spatio-temporal wavelet decomposition is completed, a health state model of the underground structure is established through weighted regression, and a regression analysis is carried out on different modes of the vibration signal, reflecting the vibration characteristics of the underground structure at different times and spatial positions; by analyzing the health state model of the underground structure, the state of the underground structure can be clarified, including whether it has damage, the severity of the damage, and the specific location where the damage occurs.

[0057] Specifically, the health state model of the underground structure establishes the relationship between the health state and the vibration signal through weighted regression. By dynamically adjusting the weighting coefficients, the contributions of vibration signals at each time and each spatial position to the health state are made different, thus adapting to the time-varying characteristics and local features of the underground structure vibration signals and ensuring the accuracy and flexibility of the health state model of the underground structure. The mathematical representation of the health state model of the underground structure is as follows:

[0058]

[0059] Where, Y(t, s) represents the health state of the underground structure, indicating the health state estimation of the underground structure at time t and spatial position s; X i (t, s) is the decomposition result of the vibration signal at the i-th level, representing the vibration signal characteristics at this level; w i (t, s) is the weighting coefficient, indicating the weight of X i (t, s) at different positions and times; ∈(t, s) is the regression error term in the health state model.

[0060] The weighting coefficient w i (t, s) is dynamically adjusted with the changes of time and spatial position, ensuring that the health state model of the underground structure can accurately reflect the contribution of the vibration signal to the health state. The update rule of the weighting coefficient is dynamically adjusted according to the prediction error of the health state model and the correlation of the signal characteristics, aiming to maximize the prediction accuracy of the regression process and reduce the influence of external interference factors. The update rule of the weighting coefficient is as follows:

[0061]

[0062] Where, t′ is the adjacent time of time t; Y(t′, s) represents the health state estimation of the underground structure at time t′ and spatial position s; λ is the regularization term, used to control the penalty term of the weighting coefficient to prevent overfitting. By dynamically adjusting the weighting coefficient, the health state model of the underground structure can adapt to the changes of the signal and improve the prediction accuracy.

[0063] S2. Calculate the stiffness matrix, mass matrix and damping matrix of the underground structure based on its health state; and evaluate the damage of the underground structure by establishing a dynamic response model of the underground structure.

[0064] The health state of an underground structure represents the vibration characteristics of the underground structure at different locations and times, reflects its health condition, and provides basic information for subsequent damage assessment. It is an important indicator of the health of the underground structure. Therefore, the health state of the underground structure affects modal parameters such as stiffness, mass, and damping in damage assessment. When damage occurs, modal parameters such as stiffness, mass, and damping of the underground structure will change, thus affecting the vibration response. The specific formulas are as follows:

[0065] K(t, s) = K0 + ΔK(t, s)·(1 - Y(t, s))

[0066] M(t, s) = M0 + ΔM(t, s)·(1 - Y(t, s))

[0067] C(t, s) = C0 + ΔC(t, s)·(1 - Y(t, s))

[0068] Where K(t, s) is the stiffness matrix of the underground structure at time t and position s; M(t, s) is the mass matrix of the underground structure at time t and position s; C(t, s) is the damping matrix of the underground structure at time t and position s; K0, M0 、 C0 are the initial stiffness matrix, initial mass matrix, and initial damping matrix of the underground structure respectively; ΔK(t, s), ΔM(t, s), ΔC(t, s) are the changes in stiffness, mass, and damping caused by damage respectively, which are obtained through experiments. As the health state changes, the modal parameters of the underground structure will dynamically respond to the corresponding changes, so that the damage state can be reflected in the subsequent dynamic response calculation.

[0069] The health state is actually a damage indicator of the underground structure. When damage occurs, the vibration characteristics of the underground structure, that is, the health state, will change, thus affecting the response of the underground structure. Therefore, the external force and the dynamic response of the underground structure can be corrected through the change of the health state.

[0070] External excitation is a key factor affecting the vibration of the underground structure, including external forces such as seismic forces, wind loads, and construction loads. The health state can be used to adjust the influence of external excitation. For example, the vibration response in the damaged area may increase or decrease, thus affecting the propagation of external excitation. The calculation of external excitation is:

[0071] F(t, s) = F0(t, s)·(1 - Y(t, s))

[0072] Where F(t, s) is the external excitation acting on the underground structure at time t and position s; F0(t, s) is the external excitation in the undamaged case, which is obtained through experimental tests and theoretical analysis.

[0073] To achieve damage assessment, modal recursive partial differential equations are used to establish a dynamic response model of the underground structure; the healthy state corresponds to the change in the vibration of the underground structure, so it can act as a feedback mechanism in the solution of the modal recursive partial differential equations. The feedback mechanism can be realized through the following formula:

[0074]

[0075] where is the acceleration of the underground structure at time t and position s, reflecting the dynamic characteristics of the vibration of the underground structure; is the vibration velocity of the underground structure at time t and position s; u(t, s) is the vibration displacement of the underground structure at time t and position s; and are feedback terms for adjustment and correction; and are feedback adjustment coefficients obtained through experiments; Y(t′, s) is the estimated healthy state of the underground structure at time t′ and spatial position s; t′ is the adjacent time of time t; is the attenuation factor for controlling the attenuation speed, obtained through experiments.

[0076] By integrating the healthy state into the modal recursive partial differential equations of the underground structure, the dynamic response of the underground structure will be able to truly reflect the health condition of the underground structure. When damage occurs, modal parameters such as the stiffness, mass, and damping of the structure change, and by modifying the modal parameters, it affects the dynamic response of the underground structure. Through the change in the dynamic response, that is and the measurement of u(t, s), the damage of the underground structure is quantified.

[0077] Finally, the results of the vibration test are the dynamic response information of the underground structure (such as acceleration, vibration displacement, vibration velocity, etc.) and the corresponding estimated healthy state, providing key data for damage assessment and subsequent structural maintenance decisions:

[0078] Dynamic response data: Obtain vibration data including acceleration, vibration displacement, and vibration velocity from the dynamic response model of the underground structure, which reflects the vibration characteristics of the underground structure at different positions and times. Analyzing the vibration signal, especially the modal parameters extracted through modal analysis, such as natural frequency, vibration mode, damping, etc., can help determine whether there are abnormal changes in the underground structure.

[0079] Healthy state: Through the modal analysis of the vibration signal and the application of the healthy state model of the underground structure, the healthy state of the underground structure at different times and spatial points can be obtained, which reflects the dynamic characteristics of the underground structure during vibration. The change in the healthy state is usually related to the damage state of the underground structure.

[0080] Damage assessment result: Based on the changes in the health status and combined with known damage patterns, the damage condition of the underground structure can be evaluated; by comparing the changes in the health status at different time points and different locations, the size and location of the damage can be further inferred.

[0081] In summary, a vibration test method for the health monitoring of underground structures has been completed.

[0082] The sequence of the invention embodiments is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or consecutive order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0083] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. The key point of each embodiment is to illustrate the differences from other embodiments.

[0084] The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments or perform equivalent replacements for some of the technical features. These modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention and should all be included in the protection scope of the present invention.

Claims

1. A vibration testing method for underground structure health monitoring, characterized in that, It includes the following steps: S1. Capture the vibration signals of the underground structure in real time, perform denoising and feature extraction on the vibration signals by spatio-temporal wavelet decomposition to obtain the decomposed signals; based on the decomposed signals, construct a health state model of the underground structure through weighted regression to evaluate the health state of the underground structure; S2. Calculate the stiffness matrix, mass matrix and damping matrix of the underground structure based on the health state of the underground structure; And evaluate the damage of the underground structure by establishing a dynamic response model of the underground structure.

2. The vibration test method for underground structure health monitoring according to claim 1, wherein The specific content of S1 includes: During the spatio-temporal wavelet decomposition of the vibration signals, extract the local features of the vibration signals at different time and space positions through spatio-temporal wavelet transform to obtain the spatio-temporal wavelet transform result.

3. The vibration test method for underground structure health monitoring according to claim 2, wherein The specific content of S1 includes: In the spatio-temporal wavelet transform, introduce a reconstruction factor, adjust the resolution of the vibration signals during the spatio-temporal wavelet transform according to the local changes of the vibration signals in the spatio-temporal domain, and obtain the final spatio-temporal wavelet transform result through the spatio-temporal wavelet transform formula with the reconstruction factor; the spatio-temporal wavelet transform formula with the reconstruction factor is: Among them, W ψ (a, b, t, s) is the final spatio-temporal wavelet transform result; a and b are respectively used to control the scale and offset; t represents time; s represents the spatial position; x(t, s) is the vibration signal of the underground structure; r(t, s) is the reconstruction factor; ψ a，b (t, s) is the spatio-temporal wavelet basis function.

4. The vibration test method for underground structure health monitoring according to claim 3, characterized in that The specific content of S1 includes: Perform hierarchical decomposition on the final spatio-temporal wavelet transform result by using the time-frequency joint analysis method to obtain the features of the vibration signals in different time periods and frequency ranges.

5. The vibration test method for underground structure health monitoring according to claim 1, characterized in that, The specific content of S1 includes: The mathematical representation of the health state model of the underground structure is: Among them, Y(t, s) represents the health state of the underground structure, indicating the estimated health state of the underground structure at time t and spatial position s; N is the number of decomposition levels; X i (t, s) is the decomposition result of the vibration signal at the i-th level; w i (t, s) is the weighting coefficient, indicating the weight of X i (t, s) at different positions and times; ∈(t, s) is the regression error term.

6. The vibration test method for underground structure health monitoring according to claim 5, characterized in that The specific content of S1 includes: The weighting coefficients in the health state model of the underground structure are dynamically adjusted with the changes of time and space positions, and the specific formula is: where t′ is the adjacent time of time t; Y(t′, s) represents the health state estimation of the underground structure at time t′ and space position s; λ is the regularization term.

7. The vibration test method for underground structure health monitoring according to claim 1, characterized in that The specific content of S2 includes: The health state of the underground structure affects the modal parameters for damage assessment, and the modal parameters include the stiffness, mass and damping of the underground structure; when damage occurs, the stiffness, mass and damping of the underground structure will change, thus affecting the response of the underground structure.

8. The vibration test method for underground structure health monitoring according to claim 7, characterized in that The specific content of S2 includes: External excitation is a factor affecting the vibration of the underground structure, and adjust the influence of the external excitation based on the health state of the underground structure.

9. The vibration test method for underground structure health monitoring according to claim 8, wherein The specific content of S2 includes: Adopt the modal recursive partial differential equation method to establish a dynamic response model of the underground structure; take the change of the health state of the underground structure corresponding to the vibration of the underground structure as a feedback mechanism and act on the solution of the modal recursive partial differential equation. The feedback mechanism is realized through the following formula: where, ü(t, s) is the acceleration of the underground structure at time t and position s; F(t, s) is the external excitation acting on the underground structure at time t and position s; C(t, s) is the damping matrix of the underground structure at time t and position s; is the vibration velocity of the underground structure at time t and position s; K(t, s) is the stiffness matrix of the underground structure at time t and position s; u(t, s) is the vibration displacement of the underground structure at time t and position s; M(t, s) is the mass matrix of the underground structure at time t and position s; and is the feedback regulation coefficient; Y(t, s) represents the health state of the underground structure, indicating the health state estimation of the underground structure at time t and spatial position s; Y(t′, s) is the health state estimation of the underground structure at time t′ and spatial position s; t′ is the adjacent time of time t; is the attenuation factor.

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