Method and system for judging damage of high-pile wharf of steel pipe pile

Abstract

The invention provides a steel pipe pile high-pile wharf damage judgment method and system, and relates to the technical field of steel pipe pile high-pile wharf damage judgment. According to wharf design parameters, a rigidity matrix representing the overall rigidity characteristic of the wharf is constructed, and spectral decomposition is conducted on the matrix in a healthy state; respectively defining the obtained feature value set and the feature vector space as a reference spectrum and a reference vector space, and establishing a lossless reference; for a to-be-detected state, obtaining a current spectrum and a current vector space through the same process, and calculating Jensen-Shannon divergence between the current spectrum and a reference spectrum to generate a global damage index for quantitatively evaluating the overall rigidity degradation degree of the structure; if the index exceeds the limit, the deviation degree of the vector space is further analyzed through projection operation, and an abnormal deviation component is reversely mapped to a physical coordinate, so that accurate spatial positioning of the damage is realized.

Description

Technical Field

[0001] This invention relates to the field of damage assessment technology for high-pile steel pipe pile wharves, specifically a method and system for assessing damage to high-pile steel pipe pile wharves. Background Technology

[0002] As a core component of port infrastructure, the long-term safe operation of steel pipe pile high-pile wharves is of paramount importance. Due to the long-term exposure to complex factors such as ship impacts, wave cyclic loads, and environmental corrosion, the wharf structure will inevitably suffer cumulative damage. Therefore, accurate and efficient damage assessment of the wharf's health status is crucial for preventing catastrophic accidents and developing scientific maintenance strategies, and has significant economic and safety implications. Traditional damage assessment methods mainly rely on regular manual visual inspections and special tests. These methods are not only highly subjective and time-consuming, but also make it difficult to detect early hidden damage within the structure.

[0003] To overcome the limitations of manual inspection, existing technologies generally employ methods based on sensor monitoring and physical model analysis. The first type of method involves deploying sensors on the structure to monitor its vibration response and inferring damage by analyzing changes in dynamic characteristics such as frequency and mode shape. However, this type of method is extremely sensitive to environmental disturbances, such as temperature and load changes, and can only provide a qualitative judgment on whether damage has occurred, making it difficult to quantify the degree of damage or accurately locate the location of the damage. The other type of method relies on establishing a sophisticated finite element model and evaluating the structural state by repeatedly comparing the model's predictions with measured data. This method is computationally complex, and its accuracy is highly dependent on the consistency between the model itself and the actual structure. Even small errors in the model parameters can lead to misjudgments, making it difficult to reliably apply in practical engineering.

[0004] The fundamental shortcoming of the aforementioned existing technologies is that none of them have established a quantitative judgment benchmark that does not rely on subjective experience and can effectively isolate the interference of environmental and operational variables; vibration monitoring methods cannot extract the essential characteristics caused purely by structural stiffness degradation from the mixed response signals; and the finite element method is constrained by the confusion between model error and structural damage, and cannot achieve accurate isolation and quantification of damage.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for determining damage to steel pipe pile high-pile wharves, so as to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: A method for determining damage to a high-pile steel pipe pile wharf, comprising the following steps: Step 1: Based on the current data parameters of the target steel pipe pile high pile wharf, construct an abstract mathematical object representing its overall mechanical properties. This abstract mathematical object is a stiffness matrix, which is based on the current data parameters of each unit of the wharf, i.e., determined by the geometric topology, material constants and boundary constraints of the high pile wharf structure through mapping relationships. Step 2: Perform spectral analysis on the stiffness matrix of the target steel pipe pile high pile wharf in a healthy and undamaged state to decompose it into a set of orthogonal basis vectors and their corresponding scalar weights. Arrange all scalar weights in order and define them as the reference spectrum. Then, form a reference vector space from the set of orthogonal basis vectors. Step 3: Perform the same spectral analysis on the stiffness matrix of the target steel pipe pile high pile wharf to obtain the current spectrum and the current vector space. By calculating the distance between the current spectrum and the reference spectrum in a probabilistic statistical sense, a global damage index is generated. Step 4: If the global damage index exceeds the preset threshold, damage is determined to have occurred. The deviation of each orthogonal basis vector in the current vector space from the corresponding orthogonal basis vector in the reference vector space is calculated through projection operation. Based on the deviation of all orthogonal basis vectors, the positioning score of each unit is calculated. The physical space coordinates corresponding to the unit with the highest positioning score are determined as the damage location, thereby achieving accurate positioning.

[0008] Furthermore, based on the data parameters of the target steel pipe pile high-pile wharf, the logic for constructing an abstract mathematical object representing its overall mechanical properties is as follows: The entire steel pipe pile high-pile wharf structure is discretized into multiple finite element model elements, including pile elements for simulating steel pipe piles, beam elements for simulating crossbeams, and plate elements for simulating panels. The data parameters include the geometric topology, material constants, and boundary constraints of all elements in the target steel pipe pile high pile wharf. The geometric topology includes geometric dimensions and their spatial layout spacing, wherein the spatial layout spacing is defined by the node coordinates and element connection relationships in the finite element model elements. The material constants include the elastic modulus and Poisson's ratio. The boundary constraints simulate the pile-soil interaction by setting the equivalent spring stiffness of the soil at the pile bottom. Based on the geometric dimensions and material constants of each element, the element stiffness matrix is ​​calculated according to the principles of structural mechanics. For pile elements, the geometric dimensions are pile length, diameter and wall thickness. For beam and slab elements, the geometric dimensions are their cross-sectional dimensions. Based on the connection relationship between the node coordinates and the elements, the stiffness matrices of all elements are assembled into the initial global stiffness matrix of the steel pipe pile high pile wharf structure. Then, according to the boundary constraints, the initial global stiffness matrix is ​​subjected to boundary condition processing to eliminate rigid displacement, and finally a symmetric positive definite stiffness matrix is ​​generated.

[0009] Furthermore, the logic for performing spectral analysis on the stiffness matrix of a high-pile wharf in a healthy and undamaged state is as follows: The stiffness matrix is ​​decomposed into a spectral matrix to obtain a set of orthonormal basis vectors and eigenvalues ​​corresponding to each orthonormal basis vector. The eigenvalues ​​are scalar weights. The eigenvalues ​​are arranged in descending order to form an eigenvalue sequence that serves as the reference spectrum. This set of orthonormal basis vectors is defined as the reference vector space.

[0010] Furthermore, the global damage index is calculated using a spectrum-based probability distribution divergence metric, specifically including: Define the reference spectrum as and define the current spectrum as , Indicates the current moment. It is the transpose symbol; The eigenvalue sequences of the baseline spectrum and the current spectrum are normalized into probability distributions, and the probability distributions of the baseline spectrum and the current spectrum are calculated using the following formulas: ; in, To prevent division by zero constant, , These represent the order in the reference spectrum. The scalar weight of the current position, and its ranking in the current spectrum. scalar weights of bits This represents the sorting order of the scalar weights in the eigenvalue sequence, and , The total number of eigenvalues ​​in the eigenvalue sequence. and They are respectively ranked in the reference spectrum at the 1st The scalar weighted normalized probability value of the current position, and the position ranked in the current spectrum. The scalar weighted normalized probability value of the bit; Calculate the intermediate distribution The global damage exponent at the current time is calculated using the Jensen-Shannon divergence: ; in, The global damage index at the current moment has a range of values. The larger the value, the higher the degree of damage, and the base of the logarithm is 2. , To avoid a preset constant with a denominator of 0.

[0011] Furthermore, calculate the guarantee criterion value of the orthogonal basis vector corresponding to the i-th scalar weight in the current spectrum. : ; in, Let be the orthonormal basis vector in the reference vector space corresponding to the scalar weight of the i-th position of the reference spectrum. Let i be the orthonormal basis vector in the current vector space corresponding to the i-th scalar weight of the current spectrum. This represents the dot product of vectors; the absolute value is used to eliminate sign uncertainty. Represents the L2 norm; Define the deviation of the orthogonal basis vector corresponding to the i-th scalar weight in the current spectrum as: ,in ; Using the pre-calibrated unit sensitivity matrix Calculate the positioning score of each unit j at the current time. Its formula is: ; in, For the orthogonal basis vectors sorted at position i, the first one is the first one. The projection coefficient of each element, the absolute value of which is used to eliminate the projection sign cancellation effect, and j is the index of the element in the target steel pipe pile high pile wharf; Positioning score The element with the highest value is identified as the damage location. By combining the element's node coordinates with the geographic mapping relationship of the actual structure, damage localization is achieved.

[0012] Furthermore, determining the occurrence of damage also includes a confirmation process in the time domain, namely, for By performing an exponentially weighted moving average filter, the smoothed global damage index is obtained: ; in, The smoothed global damage index. for The smoothed global damage index at time step 1. Forgetting factor, The sampling interval; when When the number of consecutive samplings exceeding the preset threshold reaches N, a damage alarm is triggered, where N is a preset positive integer greater than 1.

[0013] Furthermore, the logic for obtaining the preset threshold is as follows: multiple measurements are performed on the target steel pipe pile high pile wharf in a healthy and undamaged state to obtain a series of historical data of global damage indices to form a historical dataset. The mean and standard deviation of the historical dataset are calculated, and the mean plus three times the standard deviation is used as the preset threshold.

[0014] The present invention also provides a damage assessment system for high-pile steel pipe pile wharves, the system being used to execute the above-described damage assessment method for high-pile steel pipe pile wharves, comprising: The matrix construction module is used to construct an abstract mathematical object representing the overall mechanical properties of the target steel pipe pile high pile wharf based on the current data parameters of the target steel pipe pile high pile wharf. This abstract mathematical object is a stiffness matrix, which is based on the current data parameters of each unit of the wharf, that is, determined by the geometric topology, material constants and boundary constraints of the high pile wharf structure through mapping relationships. The data analysis module is used to perform spectral analysis on the stiffness matrix of the target steel pipe pile high pile wharf in a healthy and undamaged state, so as to decompose it into a set of orthogonal basis vectors and their corresponding scalar weights, arrange all the scalar weights in order and define them as the reference spectrum, and form the reference vector space by the set of orthogonal basis vectors. The damage calculation module is used to perform the same spectral analysis on the stiffness matrix of the target steel pipe pile high pile wharf, obtain the current spectrum and the current vector space, and generate a global damage index by calculating the distance between the current spectrum and the reference spectrum in a probabilistic statistical sense. The location determination module is used to determine that damage has occurred if the global damage index exceeds a preset threshold. It calculates the deviation of each orthogonal basis vector in the current vector space from the corresponding orthogonal basis vector in the reference vector space through projection operation. Based on the deviation of all orthogonal basis vectors, it calculates the positioning score of each unit and determines the physical space coordinates corresponding to the unit with the highest positioning score as the damage location, thereby achieving accurate positioning.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention constructs an abstract mathematical object (stiffness matrix) representing the overall stiffness characteristics of a structure and performs spectral decomposition on it, transforming a healthy physical state into a stable mathematical benchmark defined by a benchmark spectrum and a benchmark vector space. This benchmark is fundamentally different from the vibration frequency that is susceptible to environmental disturbances or the finite element results that rely on subjective modeling in traditional methods. It captures the intrinsic essential characteristics of the structural stiffness distribution, laying a reliable foundation for subsequent accurate comparisons. This invention generates a global damage index by calculating the distance between the current spectrum and the reference spectrum in a probabilistic statistical sense (Jensen-Shannon divergence). This method can keenly perceive the overall and subtle shifts in the structural stiffness distribution and express these shifts as a value with a clear physical meaning between 0 and 1, namely the global damage index. This achieves a leap from qualitative judgment to quantitative assessment of the degree of damage and effectively solves the problem that existing technologies cannot quantify the degree of damage. This invention uses mathematical projection operations to deeply analyze the degree of directional deviation between the corresponding vectors in the current vector space and the reference vector space. By mapping the vector components with abnormally high deviations back to their corresponding physical space coordinates, the technical solution can accurately indicate the specific location of the damage. This mapping mechanism from mathematical space anomalies to physical space positioning does not rely on the personal experience and judgment of engineers, and avoids the uncertainty of complex model corrections. Thus, it achieves accurate and objective positioning of the damage location, providing clear guidance for subsequent targeted maintenance. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2 This is a curve showing the fitting of the current probability value and the global damage index in this invention. Figure 3 This is a fitting curve of the intermediate distribution-global damage index of the present invention; Figure 4 This is a scatter plot of the current probability value and global damage index of this invention. Figure 5 This is a line graph showing the current probability value, intermediate distribution, and global damage index of this invention. Figure 6 This is a flowchart of the overall system modules of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0018] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0019] Example: Please see Figures 1-5 The present invention provides a technical solution: A method for determining damage to a high-pile steel pipe pile wharf, comprising the following steps: Step 1: Based on the current data parameters of the target steel pipe pile high pile wharf, construct an abstract mathematical object representing its overall mechanical properties. This abstract mathematical object is a stiffness matrix, which is based on the current data parameters of each unit of the wharf, i.e., determined by the geometric topology, material constants and boundary constraints of the high pile wharf structure through mapping relationships. Based on the data parameters of the target steel pipe pile high-pile wharf, the logic for constructing an abstract mathematical object representing its overall mechanical properties is as follows: The entire steel pipe pile high-pile wharf structure is discretized into multiple finite element model elements, including pile elements for simulating steel pipe piles, beam elements for simulating crossbeams, and plate elements for simulating panels. By discretizing the continuous mechanical response in the actual structure, the response at a finite number of discrete unit nodes is approximated, realizing the transformation from infinite degrees of freedom to finite degrees of freedom. Nodes are set at key locations in the structure, including the top, bottom and middle segment points of the steel pipe piles, the ends and middle of the beams, and the corners and midpoints of the panels. Each node has six degrees of freedom, including three translational degrees of freedom and three rotational degrees of freedom. The node coordinates accurately record the spatial geometry of the structure. To address the structural characteristics of the high-pile steel pipe pile wharf, differentiated element types are adopted. The pile elements are simulated using three-dimensional beam elements, with each element defined by two nodes, considering axial, bending, shear, and torsional deformations. This accurately reflects the combined bending and torsional deformation of the steel pipe piles under complex loads such as waves and water flow. The beam elements also use three-dimensional beam elements, focusing on bending and shear effects. The plate elements use shell elements to simulate the concrete panel, considering both in-plane stiffness and out-of-plane bending stiffness, accurately reflecting the mechanical behavior of the panel under vehicle loads and cargo loads. After geometric discretization, material properties are assigned to each element. Based on field sampling and laboratory test results, the elastic modulus and Poisson's ratio of steel are input for the steel pipe pile element, and the corresponding material parameters of concrete are input for the concrete panel and beam element. These material constants will directly participate in the calculation process of the element stiffness matrix. Special attention should be paid to the simulation of boundary conditions. By conducting static load tests on pile foundations in the field, key parameters of pile-soil interaction are obtained and converted into equivalent spring stiffness applied to the pile bottom node, thereby accurately simulating the actual constraint condition between the pile foundation and the ground. After obtaining the complete discrete model, the system assembly of the stiffness matrix begins. Based on the direct stiffness method principle in structural mechanics, the element stiffness matrix of each element in the local coordinate system is first calculated. For beam elements, the coupling effects of axial deformation, bending deformation, shear deformation, and torsional deformation need to be considered; for plate elements, the combined effects of in-plane tension, in-plane shear, and bending-torsional deformation need to be comprehensively considered. Then, according to the node connection relationship, all element stiffness matrices are transformed from the local coordinate system to the global coordinate system through coordinate transformation, and systematically assembled into the initial global stiffness matrix according to the node degree of freedom number. This assembly process ensures the balance of nodal forces and the compatibility of displacements. The data parameters include the geometric topology, material constants, and boundary constraints of all elements in the target steel pipe pile high pile wharf. The geometric topology includes geometric dimensions and their spatial layout spacing, wherein the spatial layout spacing is defined by the node coordinates and element connection relationships in the finite element model elements. The material constants include the elastic modulus and Poisson's ratio. The boundary constraints simulate the pile-soil interaction by setting the equivalent spring stiffness of the soil at the pile bottom. In geometric topology, node coordinates define the spatial configuration of the structure, determine the overall size and bandwidth of the stiffness matrix, and the element connection relationship defines the force transmission path, which directly affects the distribution characteristics of the overall stiffness of the structure. Parameters such as the diameter and wall thickness of steel pipe piles not only affect the cross-sectional stiffness, but also relate to local stability. Among material constants, the elastic modulus characterizes the material's ability to resist elastic deformation and is the core parameter of the stiffness matrix. Poisson's ratio reflects the material's lateral deformation characteristics and is particularly crucial for stress distribution analysis of plate and shell structures. The equivalent spring stiffness under boundary constraints is determined based on pile-soil interaction theories such as the m-method or py-curve method. The spring stiffness value is obtained by inversion from geological survey data and geotechnical test results. This approach avoids both oversimplification of fixed constraints and unreasonable increases in degrees of freedom. Based on the geometric dimensions and material constants of each element, the element stiffness matrix is ​​calculated according to the principles of structural mechanics. For pile elements, the geometric dimensions are pile length, diameter and wall thickness. For beam and slab elements, the geometric dimensions are their cross-sectional dimensions. The stiffness matrix of the pile element is established based on Timoshenko beam theory or Euler-Bernoulli beam theory. It considers the coupling effect of axial deformation, bending deformation, shear deformation and torsional deformation and calculates geometric properties such as cross-sectional area, moment of inertia and polar moment of inertia through cross-sectional parameters (diameter, wall thickness). The stiffness matrix of beam elements is also based on beam theory, but the calculation is simplified according to the actual stress characteristics of beams. It focuses on bending stiffness and shear stiffness and ignores the influence of secondary factors. The stiffness matrix of plate elements is established based on Mindlin plate theory or Kirchhoff plate theory. It considers the combined effects of in-plane tension, in-plane shear and bending torsional deformation, and calculates the section stiffness matrix through thickness parameters. Based on the connection relationship between the node coordinates and the elements, the stiffness matrices of all elements are assembled into the initial global stiffness matrix of the steel pipe pile high pile wharf structure. According to the boundary constraints, the initial global stiffness matrix is ​​subjected to boundary condition processing to eliminate rigid displacement, and finally a symmetric positive definite stiffness matrix is ​​generated. The assembly process of the global stiffness matrix is ​​based on the principle of the direct stiffness method. According to the node connection relationship, the stiffness matrices of each element in the global coordinate system are integrated into the global matrix. This process requires the establishment of a complete node degree of freedom numbering system to ensure that the contribution of each element is correctly superimposed to the corresponding position of the global matrix. After the assembly is completed, the global stiffness matrix is ​​corrected according to the boundary conditions to eliminate rigid body displacement modes and finally generate a symmetric positive definite global stiffness matrix. The assembly of the initial global stiffness matrix embodies the core concept of the finite element method of integrating zeros into a whole, including the principle of the direct stiffness method, coordinate transformation technology, and storage optimization strategy. The principle of the direct stiffness method is based on the nodal equilibrium condition and displacement compatibility condition, assembling the element stiffness matrix into the corresponding position of the global matrix according to the nodal degree of freedom number. The coordinate transformation technology transforms the stiffness matrix of each element in the local coordinate system to the global coordinate system through the transformation matrix, ensuring the objectivity of the mechanical response. The storage optimization strategy utilizes the symmetry, sparsity, and banded distribution characteristics of the global stiffness matrix, and adopts compressed storage technology to reduce the computational resource requirements. Eliminating rigid displacements prevents singularities in the stiffness matrix and ensures the feasibility of subsequent eigenvalue solutions. In the boundary condition introduction method, for fixed constraints, the rows and columns related to the corresponding degrees of freedom are directly deleted. For spring constraints, the spring stiffness values ​​are superimposed on the diagonal elements of the overall stiffness matrix. The symmetry of positive definiteness originates from the reciprocal theorem of work, which is a fundamental requirement of elasticity. Positive definiteness ensures that the strain energy of the system is always positive, which is consistent with physical reality. This property provides a mathematical guarantee that the eigenvalues ​​in subsequent spectral analysis are all positive real numbers.

[0020] Step 2: Perform spectral analysis on the stiffness matrix of the target steel pipe pile high pile wharf in a healthy and undamaged state to decompose it into a set of orthogonal basis vectors and their corresponding scalar weights. Arrange all scalar weights in order and define them as the reference spectrum. Then, form a reference vector space from the set of orthogonal basis vectors. The logic for performing spectral analysis on the stiffness matrix of a high-pile wharf in a healthy and undamaged state is as follows: The term "healthy and undamaged state" refers to the stable working state reached by the target steel pipe pile high-pile wharf after its construction and initial service period. The determination of this state requires a comprehensive assessment based on structural characteristics, environmental conditions, and monitoring data. Typically, the period from the 6th to the 18th month after the wharf's construction is selected as the benchmark period for establishing the healthy and undamaged state. This period is selected based on the following engineering considerations: the structure has completed its initial settlement and deformation, the concrete material has fully hardened and reached its design strength, the stress redistribution at the steel structure connection points has tended to stabilize, and the structure has undergone environmental load tests in different seasons. The stiffness matrix is ​​spectral decomposed to obtain a set of orthonormal basis vectors and eigenvalues ​​corresponding to each orthonormal basis vector. The eigenvalues ​​are scalar weights. The eigenvalues ​​are arranged in descending order to form an eigenvalue sequence that serves as the reference spectrum. This set of orthonormal basis vectors is defined as the reference vector space. Spectral analysis is a core mathematical tool in structural dynamics. Its essence is to decompose a complex structural system into a series of independent vibration modes. For complex engineering structures such as steel pipe pile high pile wharves, the overall stiffness matrix contains information on the stiffness distribution of the structure in various directions in space. Spectral analysis decomposes this huge matrix system into basic components that are easier to understand and analyze. First, it is necessary to obtain the complete stiffness matrix of the structure in a healthy and undamaged state. This matrix is ​​established through finite element analysis and contains the integrated results of the stiffness contributions of all elements. The spectral analysis process starts with solving the eigenvalue problem, which is a standard mathematical calculation process aimed at finding a special scalar solution that makes the product of the stiffness matrix and the eigenvector equal to the product of the eigenvalue and the eigenvector. The physical meaning of eigenvalues ​​is very clear. They represent the ratio of stiffness to equivalent mass of the structure in each independent vibration mode. Larger eigenvalues ​​correspond to the main load-bearing path and key stiffness contribution mode of the structure, while smaller eigenvalues ​​reflect secondary or local stiffness characteristics. Under healthy conditions, these eigenvalues ​​exhibit a specific distribution pattern, reflecting the inherent stiffness characteristics of the structure. The eigenvectors corresponding to each eigenvalue describe the deformation of the structure under that specific vibration mode. These eigenvectors are mathematically orthogonal, which means that different vibration modes are independent of each other and do not produce energy coupling. By standardizing these eigenvectors, a set of standard orthogonal basis vectors are obtained, which constitute a complete coordinate system for describing the deformation state of the structure. The eigenvalues ​​are arranged in descending order of their numerical values ​​to form an ordered sequence of eigenvalues. This sequence is defined as the reference spectrum. The importance of the reference spectrum lies in its systematic recording of the relative importance of each vibration mode of the structure in a healthy state. The eigenvalues ​​at the top correspond to the main stiffness contribution modes of the structure. These modes are usually related to the overall bending, torsion and other macroscopic deformations of the structure. Meanwhile, the standardized feature vectors form a reference vector space. Each basis vector in this space represents a basic deformation mode of the structure, ranging from overall rigid body displacement to local subtle deformation, covering all possible deformation states of the structure. The establishment of the reference vector space provides a reference for subsequent damage identification, and any change in the structural state will be reflected in the changes of these basis vectors. The establishment of a baseline spectrum can quantitatively assess the distribution characteristics of structural stiffness, while the baseline vector space provides the mathematical basis for describing the deformation state of the structure. When a structure is damaged, its stiffness characteristics will change, and this change will be directly reflected in the changes of eigenvalues ​​and eigenvectors. By comparing the difference between the current state and the healthy baseline state, the occurrence of damage can be accurately identified, and the location of the damage can be further located. This damage identification method based on spectrum analysis has high sensitivity and can detect early damage that is difficult to detect by traditional methods.

[0021] Step 3: Perform the same spectral analysis on the stiffness matrix of the target steel pipe pile high pile wharf to obtain the current spectrum and the current vector space. By calculating the distance between the current spectrum and the reference spectrum in a probabilistic statistical sense, a global damage index is generated. The global damage index is calculated using a spectrum-based probability distribution divergence metric, specifically including: Define the reference spectrum as and define the current spectrum as , Indicates the current moment. It is the transpose symbol; The baseline spectrum is the sequence of eigenvalues ​​of the structure in a healthy state, and the current spectrum is the sequence of eigenvalues ​​measured at the current time t. These eigenvalues ​​represent the stiffness contribution of the structure in different modes. The discrete eigenvalue sequences are organized into ordered mathematical vectors to facilitate subsequent probability and statistical operations. The transpose symbol is explicitly represented in column vector form, which conforms to the linear algebra operation norm and ensures the dimensionality consistency of subsequent matrix and vector operations. The eigenvalue sequences of the baseline spectrum and the current spectrum are normalized into probability distributions, and the probability distributions of the baseline spectrum and the current spectrum are calculated using the following formulas: ; in, To prevent division by zero constant, , These represent the order in the reference spectrum. The scalar weight of the current position, and its ranking in the current spectrum. scalar weights of bits This represents the sorting order of the scalar weights in the eigenvalue sequence, and , The total number of eigenvalues ​​in the eigenvalue sequence. and They are respectively ranked in the reference spectrum at the 1st The scalar weighted normalized probability value of the current position, and the position ranked in the current spectrum. The scalar weighted normalized probability value of the bit; and It reflects the relative importance of each scalar weight in the overall spectrum, transforming absolute stiffness eigenvalues ​​into relative weight probability values. The larger the value, the higher the ranking in terms of health status. The greater the contribution of the vibration mode corresponding to the scalar weight of the position, the greater its contribution to the overall stiffness. The larger the value, the higher the rank (in digits) at the current time. The vibration modes corresponding to the scalar weights of the bits remain important in real-time structures; When a certain Compared to When the probability distribution decreases significantly, it indicates a reduction in the stiffness contribution of the corresponding vibration mode, suggesting damage in the relevant region of that mode. When the overall shape of the probability distribution changes, it reflects a change in the stiffness distribution characteristics of the structure. or The larger the value, the more corresponding or The larger the value, the stronger the positive correlation. The sum of all probability values ​​is 1, ensuring the formation of a complete probability distribution. Transform the sequence of eigenvalues ​​into a probability distribution such that the proportion of each eigenvalue in the sum of all eigenvalues ​​is used as its probability. Calculate the intermediate distribution The global damage exponent at the current time step is calculated using the Jensen-Shannon divergence: ; in, The global damage index at the current moment has a range of values. The larger the value, the higher the degree of damage, and the base of the logarithm is 2. , To avoid a pre-defined constant with a denominator of 0; The intermediate distribution serves as the benchmark distribution for Jensen-Shannon divergence calculation, providing a reference point for measuring probability differences. It establishes a compromise reference system between the health state and the current state, ensuring the symmetry and fairness of damage assessment, avoiding assessment bias caused by using any single state as the benchmark alone, and improving the reliability of damage identification. It reflects the overall degree of difference between the baseline spectrum and the current spectrum in terms of probability distribution, and its quantitative structure reflects the overall degree to which the current state deviates from the healthy state. A value close to 0 indicates that the probability distribution of the current spectrum is highly similar to that of the baseline spectrum, and the structure is in a healthy state. A gradually increasing value indicates that the stiffness characteristics of the structure are undergoing a systematic change. A value close to 1 indicates that the structure has suffered severe overall damage; A sustained, slow increase indicates accumulated structural damage or material degradation. A sudden, rapid increase indicates that the structure has suffered sudden damage or localized destruction. The fluctuations at different times reflect the temporal variability of the structural state; when and The greater the difference, the larger the absolute value of the corresponding logarithmic term. The value increases accordingly, when all i correspond to and When the differences are small, the logarithmic terms approach 0. The value approaches 0; Ensure that the calculation remains stable when the probability value is 0; Preventing zero constant Choose a positive real number much smaller than the smallest eigenvalue; usually, the average of the eigenvalues ​​is used. The magnitude ensures stable computation even in special cases where the sum of eigenvalues ​​is extremely small; it also prevents constants with zero denominators. Choose a sufficiently small positive real number, usually taking... The order of magnitude is such that, while ensuring computational stability, the impact on the original probability distribution is minimized as much as possible.

[0022] The specific data for some time numbers and advantage estimates are shown in Table 1.

[0023] Table 1 Global Damage Index:

[0024] Through data analysis, it was observed that there are certain correlations between different characteristic parameters. For example, it can be seen from the data that there is a clear correlation between the current probability value and the global damage index. As the monitoring time progresses, the current probability value shows fluctuating changes, while the global damage index shows a complex response accordingly. When analyzing the relationship between the current probability value and the global damage index, the global damage index tends to increase when the current probability value deviates from the baseline probability value. For example, at time number 2, the current probability value is 0.162, which is higher than the baseline value, and the global damage index is 0.0158. However, at time number 3, the current probability value drops to 0.135, and the global damage index further increases to 0.0253. This shows that no matter which direction the current probability value deviates from the baseline value, it may lead to a change in the structural state, thereby affecting the magnitude of the global damage index. Further observation of the relationship between the intermediate distribution and the global damage index reveals that when the intermediate distribution value is small, the corresponding global damage index tends to be large. For example, at time number 9, the intermediate distribution value is 0.13, and the global damage index reaches 0.0715. However, at time number 14, the intermediate distribution value further decreases to 0.12, while the global damage index rises to 0.1514. This is because the intermediate distribution reflects the degree of deviation of the structural state, and a larger deviation will lead to a significant increase in the damage index. From an overall trend perspective, there is a complex nonlinear relationship between the current probability value change pattern and the response of the global damage index. For example, during the period from time number 6 to time number 8, the current probability value first decreased and then increased, while the global damage index showed a corresponding change of first increasing and then decreasing. This complex response relationship indicates that changes in the structural state will affect the final damage assessment result through the combined effect of multiple parameters. It is necessary to comprehensively consider the interaction of various parameters in engineering monitoring in order to accurately assess the health status of the structure.

[0025] Step 4: If the global damage index exceeds the preset threshold, damage is determined to have occurred. The deviation between each orthogonal basis vector in the current vector space and the corresponding orthogonal basis vector in the reference vector space is calculated by projection operation. The orthogonal basis vector with abnormally high deviation is reverse-mapped back to its corresponding physical space coordinates, thereby achieving accurate location of the damage. Calculate the guarantee criterion value of the orthogonal basis vector corresponding to the i-th scalar weight in the current spectrum. : ; in, Let be the orthonormal basis vector in the reference vector space corresponding to the scalar weight of the i-th position of the reference spectrum. Let i be the orthonormal basis vector in the current vector space corresponding to the i-th scalar weight of the current spectrum. This represents the dot product of vectors; the absolute value is used to eliminate sign uncertainty. Represents the L2 norm; It reflects the similarity in direction between the health status and the current state of the orthogonal basis vectors corresponding to the i-th scalar weight, and quantifies the angular relationship between the two vectors in space. The value is 1 when they are completely in the same direction and 0 when they are completely orthogonal. A value close to 1 indicates that the current state's orthogonal basis vectors are highly consistent with the healthy baseline, and the corresponding vibration mode has not changed significantly. A value significantly less than 1 indicates that the direction of the orthogonal basis vector has changed, and the corresponding structural vibration characteristics are abnormal. When a structure suffers localized damage, the orthogonal basis vectors in the affected area will shift in direction. The more severe the damage, the greater the change in the direction of the corresponding orthogonal basis vectors. The smaller the value, the more different sorting positions i... The pattern of change can reflect the type and location characteristics of the damage; the larger the inner product of the two vectors, the better. The larger the value, the stronger the positive correlation. The product of the vector norms serves as a normalization factor to ensure the result is within the normal range. Within the specified range, absolute value operations eliminate the effects of uncertainty in the sign of vector direction; Define the deviation of the orthogonal basis vector corresponding to the i-th scalar weight in the current spectrum as: ,in ; The degree of change in the direction of the orthogonal basis vector corresponding to the i-th scalar weight is directly quantified, transforming the similarity measure into a difference measure, which facilitates damage sensitivity analysis. A value close to 0 indicates that the direction of the orthonormal basis vector remains essentially unchanged, and the corresponding structural region is intact. A value significantly greater than 0 indicates a significant deflection in the direction of the orthogonal basis vector, suggesting damage in the corresponding structural region. A value close to 1 indicates a fundamental change in the direction of the orthogonal basis vector, corresponding to severe damage; Different sorting positions The value change pattern has a clear physical meaning, and the lower sort order (smaller i) An increase usually reflects a degradation in overall stiffness, especially for higher ranking positions (larger i). An increase usually reflects localized damage, specifically in a particular order. A sudden increase indicates damage to the sensitive area of ​​the corresponding vibration mode. The smaller the value, The larger the value, the stronger the negative correlation. This linear transformation ensures the monotonicity and consistency of damage sensitivity. Using the pre-calibrated unit sensitivity matrix Calculate the positioning score of each unit j at the current time. Its formula is: ; in, For the orthogonal basis vectors sorted at position i, the first one is the first one. The projection coefficients of each element are obtained by performing finite element analysis on each orthogonal basis vector in the reference vector space under healthy and undamaged conditions. The absolute value is used to eliminate the projection sign cancellation effect, and j is the index of the element in the target steel pipe pile high pile wharf. It comprehensively reflects the weighted contribution of the j-th unit to the deviation of all orthogonal basis vectors, and quantifies the degree of participation of each unit in the overall damage mode; The higher the value, the more involved the element is in all vibration modes, and the greater the likelihood of damage. A value close to 0 indicates that the element remains essentially unchanged across various vibration modes and is in good working order. The spatial distribution pattern can visually display the concentrated areas of damage; Damaged elements typically exhibit abnormalities in multiple vibration modes, resulting in a significant increase in their localization scores. The spatial gradient variation of localization scores can help determine the damage boundary, and the relative magnitude of localization scores among different elements can assess the distribution of damage severity. The larger the value, the better. The greater the contribution, the stronger the positive correlation. The larger the value, the higher the sensitivity of the j-th unit to the i-th orthonormal basis vector. The greater the impact of the deviation of this vector on the unit score, the absolute value operation ensures that the contribution of each orthonormal basis vector is positive and avoids mutual cancellation. The projection coefficients of the orthogonal basis vector ranked at position i onto the element j are obtained by performing finite element analysis on each orthogonal basis vector in the reference vector space under healthy and non-destructive conditions. Each orthogonal basis vector describes a basic vibration mode of the structure, which is represented as a nodal displacement mode in the finite element model. For each orthogonal basis vector, its displacement components at relevant nodes of each element are extracted, and the sensitivity coefficient of the vector to each element is obtained by weighted averaging. The larger the value, the more obvious the vibration mode described by the i-th orthogonal basis vector is at the j-th element. Once this matrix is ​​established in a healthy state, it can be used as a benchmark reference system for damage localization. Positioning score The element with the highest value is identified as the damage location. By combining the node coordinates of the element with the geographical mapping relationship of the actual structure, the damage can be located. Positioning score The score is a quantitative index calculated by integrating the deviation information of all orthogonal basis vectors. This score reflects the degree of abnormality of the j-th unit relative to the healthy state at the current time. The score is calculated based on a pre-calibrated sensitivity matrix S, which establishes the correspondence between orthogonal basis vectors and structural units. The elements of the sensitivity matrix... It characterizes the response intensity of the vibration mode corresponding to the i-th orthogonal basis vector at the j-th element, which essentially reflects the sensitivity of different vibration modes to each structural element; The element with the highest location score is identified as the damage location. This judgment is based on the basic principle of structural dynamics: when a structure suffers local damage, the stiffness characteristics of the damaged area will change. This change will affect all vibration modes passing through the area. Different vibration modes have different sensitivities to the same damage. The location score integrates the abnormal information of all vibration modes through a weighted summation, thereby accurately identifying the element most likely to be damaged. Suppose that a crack appears in a certain part of the pile body of pile No. 15 in a steel pipe pile wharf. In dynamic testing, this crack will cause the vibration mode of multiple modes to show obvious shape changes near the crack location. By calculating the positioning score of each element, it will be found that the element score of the corresponding position of pile No. 15 is significantly higher than that of other elements, thus locking the damage location. Establishing a mapping relationship between the coordinates of unit nodes and the geographical location of the actual structure is a key step in moving damage localization from mathematical space to physical space. This involves several levels: First, in the finite element modeling stage, it is necessary to establish the correspondence between the model coordinate system and the actual engineering coordinate system. The node coordinates of each element should include not only its relative position in the model but also its absolute position in the global coordinate system. For steel pipe pile high-pile wharves, this usually includes information such as latitude and longitude and elevation in the geodetic coordinate system. Second, it is necessary to establish the correspondence between the elements and specific structural components. For example, a beam element corresponds to a certain section of a certain beam, and a shell element corresponds to a certain part of a certain panel area. This correspondence needs to be clearly recorded in the modeling stage to form a complete element-component mapping table. Determining the occurrence of damage also includes a confirmation process in the time domain, namely, for By performing an exponentially weighted moving average filter, the smoothed global damage index is obtained: ; in, The smoothed global damage index. for The smoothed global damage index at time step 1. Forgetting factor, The sampling interval; It reflects the trend changes of the global damage index, filters out random fluctuations, and provides a smooth observation sequence of structural state evolution. A continuous increase indicates that structural damage is accumulating and developing. "Remaining stable" means that the structural state is relatively stable. A sudden change indicates that the structure has suffered sudden damage; The larger the value, the higher the weight of historical data. The more gradual the change, The smaller the value, the higher the weight of the current data. The more sensitive to immediate changes, When the value increases, The corresponding increase, but the rate of change is affected. control; , , ; For the lower limit , A value that is too small will result in insufficient filtering and an inability to effectively smooth random fluctuations. To ensure that enough historical information is preserved, the upper limit should be considered. , An excessively large value can cause the system to respond too slowly to actual damage. To ensure that new monitoring data can promptly influence the filtering results, an excessively large value is detrimental. The value will cause the filtering result to have too much inertia, making it difficult to reflect rapid changes in state; The time interval between two consecutive monitoring analyses. ,in , For the lower limit As a large-scale civil engineering structure, the dynamic response and damage development of steel pipe pile high pile wharf have a long time constant. Excessively high sampling frequency cannot provide additional effective information. Spectral analysis and damage index calculation require considerable computing resources. Reasonable intervals avoid unnecessary computational load. Too short sampling intervals will lead to high correlation between adjacent samples, reducing the effectiveness of information. Appropriate time intervals help to smooth the impact of short-term environmental fluctuations such as wind, waves, and traffic loads. For the upper limit This ensures that significant structural changes throughout the day can be captured, and the 24-hour cycle covers environmental influences such as diurnal temperature variations and tidal changes, conforming to the standard operating cycle for engineering monitoring; for steel pipe pile high-pile wharves, Set between 1 hour and 6 hours; when A damage alarm is triggered when the number of consecutive samplings exceeding a preset threshold reaches N, where N is a preset positive integer greater than 1; N and The alarm response time was jointly determined as follows ; ,in , For the lower limit A single exceedance is due to measurement noise or transient interference; two consecutive exceedances improve reliability, especially for the upper limit. To avoid delaying important alarms due to excessive consecutive over-limit requests; By continuously exceeding limits, the reliability and anti-interference capability of the alarm are ensured. The value of N is determined comprehensively based on the importance of the project, the level of environmental noise, and the sampling frequency. A circular buffer is established to record the N most recent sampling times. Value, used to determine continuous exceedance situations in real time; The logic for obtaining the preset threshold is as follows: multiple measurements are taken on the target steel pipe pile high pile wharf in a healthy and undamaged state to obtain a series of historical data of global damage index to form a historical dataset. The mean and standard deviation of the historical dataset are calculated, and the mean plus three times the standard deviation is used as the preset threshold. Based on the assumption of normal distribution, the threshold of mean plus three standard deviations corresponds to a confidence level of 99.73%, ensuring that the probability of false alarms is less than 0.27% in a healthy state, while maintaining sensitivity to actual damage. The threshold is set based on actual measurement data to avoid the influence of subjective experience. Statistical methods ensure the objectivity and reliability of the threshold setting, and the three standard deviation criterion achieves a good balance between sensitivity and reliability.

[0026] Please see Figure 6 The present invention also provides a damage assessment system for high-pile steel pipe pile wharves, the system being used to execute the above-described damage assessment method for high-pile steel pipe pile wharves, comprising: The matrix construction module is used to construct an abstract mathematical object representing the overall mechanical properties of the target steel pipe pile high pile wharf based on the current data parameters of the target steel pipe pile high pile wharf. This abstract mathematical object is a stiffness matrix, which is based on the current data parameters of each unit of the wharf, that is, determined by the geometric topology, material constants and boundary constraints of the high pile wharf structure through mapping relationships. The data analysis module is used to perform spectral analysis on the stiffness matrix of the target steel pipe pile high pile wharf in a healthy and undamaged state, so as to decompose it into a set of orthogonal basis vectors and their corresponding scalar weights, arrange all the scalar weights in order and define them as the reference spectrum, and form the reference vector space by the set of orthogonal basis vectors. The damage calculation module is used to perform the same spectral analysis on the stiffness matrix of the target steel pipe pile high pile wharf, obtain the current spectrum and the current vector space, and generate a global damage index by calculating the distance between the current spectrum and the reference spectrum in a probabilistic statistical sense. The location determination module is used to determine that damage has occurred if the global damage index exceeds a preset threshold. It calculates the deviation of each orthogonal basis vector in the current vector space from the corresponding orthogonal basis vector in the reference vector space through projection operation. Based on the deviation of all orthogonal basis vectors, it calculates the positioning score of each unit and determines the physical space coordinates corresponding to the unit with the highest positioning score as the damage location, thereby achieving accurate positioning.

[0027] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0028] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0029] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0030] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for determining damage to a high-pile steel pipe pile wharf, characterized in that, The specific steps include: Step 1: Based on the current data parameters of the target steel pipe pile high pile wharf, construct an abstract mathematical object representing its overall mechanical properties. This abstract mathematical object is a stiffness matrix, which is based on the current data parameters of each unit of the wharf, i.e., determined by the geometric topology, material constants and boundary constraints of the high pile wharf structure through mapping relationships. Step 2: Perform spectral analysis on the stiffness matrix of the target steel pipe pile high pile wharf in a healthy and undamaged state to decompose it into a set of orthogonal basis vectors and their corresponding scalar weights. Arrange all scalar weights in order and define them as the reference spectrum. Then, form a reference vector space from the set of orthogonal basis vectors. Step 3: Perform the same spectral analysis on the stiffness matrix of the target steel pipe pile high pile wharf to obtain the current spectrum and the current vector space. By calculating the distance between the current spectrum and the reference spectrum in a probabilistic statistical sense, a global damage index is generated. Step 4: If the global damage index exceeds the preset threshold, damage is determined to have occurred. The deviation of each orthogonal basis vector in the current vector space from the corresponding orthogonal basis vector in the reference vector space is calculated through projection operation. Based on the deviation of all orthogonal basis vectors, the positioning score of each unit is calculated. The physical space coordinates corresponding to the unit with the highest positioning score are determined as the damage location, thereby achieving accurate positioning.

2. The method for determining damage to a high-pile steel pipe pile wharf according to claim 1, characterized in that: Based on the data parameters of the target steel pipe pile high-pile wharf, the logic for constructing an abstract mathematical object representing its overall mechanical properties is as follows: The entire steel pipe pile high-pile wharf structure is discretized into multiple finite element model elements, including pile elements for simulating steel pipe piles, beam elements for simulating crossbeams, and plate elements for simulating panels. The data parameters include the geometric topology, material constants, and boundary constraints of all elements in the target steel pipe pile high pile wharf. The geometric topology includes geometric dimensions and their spatial layout spacing, wherein the spatial layout spacing is defined by the node coordinates and element connection relationships in the finite element model elements. The material constants include the elastic modulus and Poisson's ratio. The boundary constraints simulate the pile-soil interaction by setting the equivalent spring stiffness of the soil at the pile bottom. Based on the geometric dimensions and material constants of each element, the element stiffness matrix is ​​calculated according to the principles of structural mechanics. For pile elements, the geometric dimensions are pile length, diameter and wall thickness. For beam and slab elements, the geometric dimensions are their cross-sectional dimensions. Based on the connection relationship between the node coordinates and the elements, the stiffness matrices of all elements are assembled into the initial global stiffness matrix of the steel pipe pile high pile wharf structure. Then, according to the boundary constraints, the initial global stiffness matrix is ​​subjected to boundary condition processing to eliminate rigid displacement, and finally a symmetric positive definite stiffness matrix is ​​generated.

3. The method for determining damage to a high-pile steel pipe pile wharf according to claim 2, characterized in that: The logic for performing spectral analysis on the stiffness matrix of a high-pile wharf in a healthy and undamaged state is as follows: The stiffness matrix is ​​decomposed into a spectral matrix to obtain a set of orthonormal basis vectors and eigenvalues ​​corresponding to each orthonormal basis vector. The eigenvalues ​​are scalar weights. The eigenvalues ​​are arranged in descending order to form an eigenvalue sequence that serves as the reference spectrum. This set of orthonormal basis vectors is defined as the reference vector space.

4. The method for determining damage to a high-pile steel pipe pile wharf according to claim 3, characterized in that: The global damage index is calculated using a spectrum-based probability distribution divergence metric, specifically including: Define the reference spectrum as and define the current spectrum as , Indicates the current moment. It is the transpose symbol; The eigenvalue sequences of the baseline spectrum and the current spectrum are normalized into probability distributions, and the probability distributions of the baseline spectrum and the current spectrum are calculated using the following formulas: ； in, To prevent division by zero constant, , These represent the order in the reference spectrum. The scalar weight of the current position, and its ranking in the current spectrum. scalar weights of bits This represents the sorting order of the scalar weights in the eigenvalue sequence, and , The total number of eigenvalues ​​in the eigenvalue sequence. and They are respectively ranked in the reference spectrum at the 1st The scalar weighted normalized probability value of the current position, and the position ranked in the current spectrum. The scalar weighted normalized probability value of the bit; Calculate the intermediate distribution The global damage exponent at the current time is calculated using the Jensen-Shannon divergence: ； in, The global damage index at the current moment has a range of values. The larger the value, the higher the degree of damage, and the base of the logarithm is 2. , To avoid a preset constant with a denominator of 0.

5. The method for determining damage to a high-pile steel pipe pile wharf according to claim 4, characterized in that: Calculate the guarantee criterion value of the orthogonal basis vector corresponding to the i-th scalar weight in the current spectrum. : ； in, Let be the orthonormal basis vector in the reference vector space corresponding to the scalar weight of the i-th position of the reference spectrum. Let i be the orthonormal basis vector in the current vector space corresponding to the i-th scalar weight of the current spectrum. This represents the dot product of vectors; the absolute value is used to eliminate sign uncertainty. Represents the L2 norm; Define the deviation of the orthogonal basis vector corresponding to the i-th scalar weight in the current spectrum as: ,in ; Using the pre-calibrated unit sensitivity matrix Calculate the positioning score of each unit j at the current time. Its formula is: ； in, For the orthogonal basis vectors sorted at position i, the first one is the first one. The projection coefficient of each element, the absolute value of which is used to eliminate the projection sign cancellation effect, and j is the index of the element in the target steel pipe pile high pile wharf; Positioning score The element with the highest value is identified as the damage location. By combining the element's node coordinates with the geographic mapping relationship of the actual structure, damage localization is achieved.

6. The method for determining damage to a high-pile steel pipe pile wharf according to claim 5, characterized in that: Determining the occurrence of damage also includes a confirmation process in the time domain, namely, for By performing an exponentially weighted moving average filter, the smoothed global damage index is obtained: ； in, The smoothed global damage index. for The smoothed global damage index at time step 1. Forgetting factor, The sampling interval; when When the number of consecutive samplings exceeding the preset threshold reaches N, a damage alarm is triggered, where N is a preset positive integer greater than 1.

7. The method for determining damage to a high-pile steel pipe pile wharf according to claim 6, characterized in that: The logic for obtaining the preset threshold is as follows: multiple measurements are performed on the target steel pipe pile high pile wharf in a healthy and undamaged state to obtain a series of historical data of global damage index to form a historical dataset. The mean and standard deviation of the historical dataset are calculated, and the mean plus three times the standard deviation is used as the preset threshold.

8. A damage assessment system for high-pile steel pipe pile wharves, characterized in that: The system is used to execute a method for determining damage to a high-pile steel pipe pile wharf as described in any one of claims 1-7, including: The matrix construction module is used to construct an abstract mathematical object representing the overall mechanical properties of the target steel pipe pile high pile wharf based on the current data parameters of the target steel pipe pile high pile wharf. This abstract mathematical object is a stiffness matrix, which is based on the current data parameters of each unit of the wharf, that is, determined by the geometric topology, material constants and boundary constraints of the high pile wharf structure through mapping relationships. The data analysis module is used to perform spectral analysis on the stiffness matrix of the target steel pipe pile high pile wharf in a healthy and undamaged state, so as to decompose it into a set of orthogonal basis vectors and their corresponding scalar weights, arrange all the scalar weights in order and define them as the reference spectrum, and form the reference vector space by the set of orthogonal basis vectors. The damage calculation module is used to perform the same spectral analysis on the stiffness matrix of the target steel pipe pile high pile wharf, obtain the current spectrum and the current vector space, and generate a global damage index by calculating the distance between the current spectrum and the reference spectrum in a probabilistic statistical sense. The location determination module is used to determine that damage has occurred if the global damage index exceeds a preset threshold. It calculates the deviation of each orthogonal basis vector in the current vector space from the corresponding orthogonal basis vector in the reference vector space through projection operation. Based on the deviation of all orthogonal basis vectors, it calculates the positioning score of each unit and determines the physical space coordinates corresponding to the unit with the highest positioning score as the damage location, thereby achieving accurate positioning.

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