Method and system for evaluating bridge damage caused by ship impact and medium

Abstract

The invention provides a method and system for evaluating bridge damage caused by ship collision and a medium, and relates to the technical field of bridge health monitoring, and the method comprises the steps: collecting acceleration response signal arrays at different heights and positions of a bridge pier, and generating a time sequence matrix; drawing time-frequency coherence spectrums under different primary functions, and obtaining coherence spectrum entropies; based on an information entropy principle, determining an optimal primary function; obtaining a local correlation coefficient of the time sequence matrix in a time-frequency space under the optimal primary function, and drawing a time-frequency coherence spectrum; according to the local correlation coefficient and the time-frequency coherence spectrum, evaluating the correlation dependence degree between the time sequences, and judging whether the ship and bridge collision damage occurs or not; if collision damage occurs, time-frequency coherent damage factors at different positions of the time sequence matrix are calculated, and the collision damage position and the collision damage degree are determined according to the convex maximum value in a time-frequency coherent damage factor trajectory curve. According to the method, the influence of environmental factors can be effectively separated, and a basic method support is provided for establishing a ship and bridge collision damage evaluation technology.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge health monitoring, and in particular to a method, system and medium for evaluating bridge damage caused by ship collision. Background Art

[0002] Under the influence of complex climatic conditions and human factors, ship-bridge collision accidents occur frequently. In ship-bridge accidents, cracks are prone to form in the local crushing area of ​​the bridge caused by the collision of the ship. If hidden cracks are not discovered in time, they will pose a potential threat to the safety of the bridge. At present, sensors usually collect acceleration response signals, but due to the influence of environmental factors, the causes of abnormal signal characteristics are difficult to distinguish, and the real damage characteristics are mixed with complex environmental influences and cannot be effectively identified. Therefore, in damage identification research, it is crucial to effectively eliminate environmental factors for ship-bridge collision damage identification research.

[0003] There is almost no research on the identification of local hidden cracks in bridges caused by ship collisions. Most of the current methods are limited to evaluating the impact damage effect of bridges from comprehensive indicators such as pier top displacement and rotation angle, and determining whether the bridge is damaged by the ship collision. However, there is a lack of an effective detection method for local identification of hidden cracks after bridge collision, accurately capturing its dynamic characteristics, and locating and identifying the location and degree of cracks. Summary of the invention

[0004] To solve the above problems, the present invention provides a method for assessing bridge damage caused by ship collision. The method effectively separates environmental variables and realizes rapid and accurate extraction of bridge dynamic information, breaking through the limitation of existing collision damage identification methods that cannot distinguish whether the damage characteristics are caused by real damage.

[0005] To achieve the above object, the present invention provides the following technical solutions.

[0006] A method for assessing bridge damage caused by ship collision comprises the following steps:

[0007] Collecting acceleration response signal arrays at different heights and positions of the bridge piers impacted by the ship, and generating a time series matrix of the acceleration response signals according to the acceleration response signal arrays;

[0008] The time-frequency coherence spectrum under different basis functions is plotted according to the time series matrix, and the coherence spectrum entropy is obtained; based on the principle of information entropy, the information volume of the time-frequency coherence spectrum under different basis function spaces is measured according to the coherence spectrum entropy, and the optimal basis function is determined;

[0009] Obtain the local correlation coefficient of the time series matrix in the time-frequency space under the optimal basis function, and draw the time-frequency coherence spectrum; evaluate the correlation dependence between time series based on the local correlation coefficient and the time-frequency coherence spectrum, and judge whether the ship bridge collision damage occurs;

[0010] If collision occurs, calculate the time-frequency coherence impairment factors at different positions of the time series matrix and draw the trajectory curve of the time-frequency coherence impairment factor; determine the collision position and degree of collision according to the maximum value of the time-frequency coherence impairment factor trajectory curve.

[0011] Preferably, the acquisition of acceleration response signal arrays at different heights and positions of the bridge struck by the ship comprises the following steps:

[0012] According to the characteristics of the target bridge pier to be measured, a wall-climbing robot is installed; the wall-climbing robot is evenly spaced with at least one acceleration sensor on each side of the bridge pier;

[0013] The wall-climbing robot is driven to move along the pier from top to bottom or from bottom to top to scan the pier. The acceleration response signal array at different heights and positions of the pier is collected by the acceleration sensor to generate a time series matrix.

[0014] Preferably, the time series matrix is ​​as shown below:

[0015] X ij =[x 1 x 2 ...x l ]

[0016] Among them, m is the total number of pier sensor levels, 1≤i≤m; n is the total number of array sensors in each layer, 1≤j≤n; l is the total length of the acquisition time series.

[0017] Preferably, the local correlation coefficient is calculated as shown below:

[0018]

[0019] In the formula, R 2 (a, b) is the local time-frequency correlation coefficient between the two sequences, S is the smoothing operator, and The time series X ij and X ik The wavelet coefficient of , a is the scale factor of the time-frequency transform, and b is the translation factor;

[0020] In the formula, when j≠k, is about the time series X ij and X ik The cross wavelet transform function is represents its cross wavelet power; when j = k, is about the time series X ij and X ik The autocorrelation wavelet transform function is as shown below:

[0021]

[0022] In the formula, * represents complex conjugation.

[0023] Preferably, it also includes:

[0024] The wavelet function is used as the basis function to calculate the time-frequency coherence value R between time series. 2 Undetermined wavelet coefficients in (a,b) As shown below:

[0025]

[0026] Where ψ is the selected wavelet basis function.

[0027] Preferably, the calculation of the coherent spectral entropy comprises the following steps:

[0028] The time-frequency coherence spectrum is divided into N time-frequency planes of equal area. The number of correlation coefficients in each time-frequency plane that pass the 95% significance test is ζ w , (w=1,…,N), the total number of A of the entire time-frequency coherence spectrum that passes the 95% significance test, normalize each area, and get:

[0029]

[0030] Based on the idea of ​​information entropy, the coherence spectrum entropy H of the time-frequency coherence spectrum is calculated using the following formula: c :

[0031]

[0032] Among them, the coherent spectral entropy H c It represents the intrinsic information content of the time-frequency coherence spectrum. If the entropy value is larger, it means that the time-frequency coherence spectrum contains more information, and its information value is higher.

[0033] Preferably, the calculation of the time-frequency coherence impairment factor comprises the following steps:

[0034] The time-frequency coherence loss factor ∈ is defined as follows:

[0035] ∈=(AWC Intact -AWC Input ) / AWC Intact

[0036] Where, AWC Intact It refers to the average value of the time-frequency coherence value of an undamaged structure within a certain time-frequency range; AWC Input It refers to the average value of the time-frequency coherence value of the structure to be tested within a certain time-frequency range.

[0037] Preferably, determining the damage position and damage degree according to the maximum value of the bump in the time-frequency coherence impairment factor trajectory curve comprises the following steps:

[0038] Based on the local correlation coefficient of the time series matrix in the time-frequency space, the Monte Carlo method is used to calculate the coherence of the time series at a 95% significance level, and the time-frequency coherence spectrum is plotted;

[0039] The time-frequency coherence spectrum fluctuates within a certain time-frequency range. When the degree of fluctuation cannot be restored to stability, it is judged that the bridge collision damage occurs. The degree of fluctuation is represented by the ratio of the number of time-frequency coherence spectra that pass the 95% significance test to the total number.

[0040] Based on the characteristics of the change of the time-frequency coherence damage factor at the damage location, a trajectory curve of the time-frequency coherence damage factor is drawn. When the bridge is damaged, the time-frequency coherence damage factor will increase suddenly near the damage location, and the damage factor will be almost 0 far away from the damage location. The level where the curve has the maximum value is considered to be the damage location.

[0041] A bridge damage assessment system caused by ship collision, the system comprising:

[0042] processor;

[0043] a memory having stored thereon a computer program executable on the processor;

[0044] Wherein, when the computer program is executed by the processor, the steps of the method for assessing bridge damage caused by ship collision are implemented.

[0045] A computer-readable storage medium stores a data processing program, and when the data processing program is executed by a processor, the steps of the bridge damage assessment method caused by ship collision are implemented.

[0046] Beneficial effects of the present invention:

[0047] The present invention proposes a method for assessing bridge damage caused by ship collision. The method is based on massive sensor signals collected by a wall-climbing robot, calculates the time-frequency coherence spectral entropy between signals under different basis functions, optimizes the basis function, and then plots the time-frequency coherence spectrum under the optimal basis function time-frequency space. This method effectively separates environmental variables and realizes rapid and accurate extraction of bridge dynamic information, breaking through the limitation of existing collision damage identification methods that cannot distinguish whether damage characteristics are caused by real damage. The present invention establishes a time-frequency coherence impairment factor based on the characteristics of the change in the local time-frequency correlation coefficient near the collision damage location, identifies the location and degree of ship-bridge collision damage through its trajectory curve, and provides basic methodological support for the establishment of ship-bridge collision damage assessment technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a flow chart of a bridge damage assessment method caused by ship collision according to an embodiment of the present invention;

[0049] Figure 2 Schematic diagram of the numerical simulation pier column structure and the wall-climbing robot structure of an embodiment of the present invention;

[0050] Figure 3 is a schematic diagram of an acceleration signal acquisition node array according to an embodiment of the present invention, wherein: Figure 3 (a) is the overall schematic diagram of the acquisition node array. Figure 3 (b) is a schematic diagram of the array of acquisition nodes at each layer;

[0051] Figure 4 is the time-frequency coherence spectrum of different wavelet basis functions of the embodiment of the present invention, wherein, Figure 4 (a) is the Morlet wavelet basis function, Figure 4 (b) is the Dog wavelet basis function, Figure 4 (c) is the 4th order Paul wavelet basis function;

[0052] Figure 5 is a schematic diagram of the time-frequency coherence spectrum of the symmetric nodes 2 and 4 according to an embodiment of the present invention, wherein: Figure 5 (a) is an undamaged pier. Figure 5 (b) is a damaged pier;

[0053] Figure 6 is a trajectory curve diagram of time-frequency coherence impairment factors between different nodes at different crack depths according to an embodiment of the present invention;

[0054] Figure 7 It is a trajectory curve diagram of the time-frequency coherence impairment factor of the symmetrical nodes 2 and 4 at different array levels at different crack positions according to an embodiment of the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0056] Example 1

[0057] The present invention provides a bridge damage assessment method caused by ship collision, the specific process is as follows: Figure 1 As shown, the following steps are included:

[0058] S1: Collect acceleration response signal arrays at different heights and positions of the bridge piers hit by the ship, and generate a time series matrix of the acceleration response signals according to the acceleration response signal arrays.

[0059] S2: Draw the time-frequency coherence spectrum under different basis functions according to the time series matrix, and obtain the coherence spectrum entropy; based on the principle of information entropy, measure the information volume of the time-frequency coherence spectrum under different basis function spaces according to the coherence spectrum entropy, and determine the optimal basis function.

[0060] S3: Obtain the local correlation coefficient of the time series matrix in the time-frequency space under the optimal basis function, and draw the time-frequency coherence spectrum; evaluate the degree of correlation dependence between time series based on the local correlation coefficient and the time-frequency coherence spectrum, and determine whether the ship bridge collision damage occurs.

[0061] S4: If collision occurs, calculate the time-frequency coherence impairment factor at different positions of the time series matrix and draw the trajectory curve of the time-frequency coherence impairment factor; determine the collision position and degree of collision according to the maximum value of the time-frequency coherence impairment factor trajectory curve.

[0062] Specifically, in S1, the acceleration response signal arrays at different heights and positions of the bridge hit by the ship are collected, including the following steps:

[0063] A wall-climbing robot is installed according to the characteristics of the target bridge pier to be tested; the wall-climbing robot is composed of multiple acceleration sensors, climbing units and control units. If the number of sensors is sufficient to cover, a digital inspection skin can be established through a vertical scan by the wall-climbing robot.

[0064] The wall-climbing robot is driven to move along the pier from top to bottom or from bottom to top to scan the pier. The acceleration response signal array at different heights and positions of the pier is collected by the acceleration sensor to generate a time series matrix.

[0065] Furthermore, in S1, the solution of the time series matrix is ​​as follows:

[0066] X ij =[x 1 x 2 ...x l ]

[0067] Among them, m is the total number of pier sensor levels, 1≤i≤m; n is the total number of array sensors in each layer, 1≤j≤n; l is the total length of the acquisition time series.

[0068] Furthermore, the calculation of the local correlation coefficient in S3 is as follows:

[0069]

[0070] In the formula, R 2 (a, b) is the local time-frequency correlation coefficient between the two sequences, S is the smoothing operator, and The time series X ij and X ik The wavelet coefficient of , a is the scale factor of time-frequency transform, and b is the translation factor.

[0071] In the formula, when j≠k, is about the time series X ij and X ik The cross wavelet transform function is represents its cross wavelet power; when j = k, is about the time series X ij and X ik The autocorrelation wavelet transform function is as shown below:

[0072]

[0073] In the formula, * represents complex conjugation.

[0074] Specifically, the wavelet function is used as the basis function to calculate the time-frequency coherence value R between time series. 2 Undetermined wavelet coefficients in (a,b) As shown below:

[0075]

[0076] Where ψ is the selected wavelet basis function.

[0077] Further, in S2, the calculation of the coherent spectral entropy includes the following steps:

[0078] The time-frequency coherence spectrum is divided into N time-frequency planes of equal area. The number of correlation coefficients in each time-frequency plane that pass the 95% significance test is ζ w , (w=1,…,N), the total number of A of the entire time-frequency coherence spectrum that passes the 95% significance test, normalize each area, and get:

[0079]

[0080] Based on the idea of ​​information entropy, the coherence spectrum entropy H of the time-frequency coherence spectrum is calculated using the following formula: c :

[0081]

[0082] Among them, the coherent spectral entropy H c It represents the intrinsic information content of the time-frequency coherence spectrum. If the entropy value is larger, it means that the time-frequency coherence spectrum contains more information, and its information value is higher.

[0083] Furthermore, in S4, the calculation of the time-frequency coherence impairment factor includes the following steps:

[0084] The time-frequency coherence loss factor ∈ is defined as follows:

[0085] ∈=(AWC Intact -AWC Input ) / AWC Intact

[0086] Where, AWC Intact It refers to the average value of the time-frequency coherence value of an undamaged structure within a certain time-frequency range; AWC Input It refers to the average value of the time-frequency coherence value of the structure to be tested within a certain time-frequency range.

[0087] Further, in S4, the damage position and damage degree are determined according to the maximum value of the convexity in the time-frequency coherence impairment factor trajectory curve, including the following steps:

[0088] Based on the local correlation coefficient of the time series matrix in the time-frequency space, the Monte Carlo method is used to calculate the coherence of the time series at a 95% significance level, and the time-frequency coherence spectrum is plotted.

[0089] The time-frequency coherence spectrum fluctuates within a certain time-frequency range. When the degree of fluctuation cannot be restored to stability, it is judged that the bridge collision damage occurs. The degree of fluctuation is represented by the ratio of the number of time-frequency coherence spectra that pass the 95% significance test to the total number.

[0090] Based on the characteristics of the change of the time-frequency coherence damage factor at the collision position, the time-frequency coherence damage factor trajectory curve is drawn. When the bridge is damaged, the time-frequency coherence damage factor will increase sharply near the collision position, and the damage factor far away from the collision position is almost 0. The level where the curve has the maximum value is considered to be the collision position. At the same time, as the degree of damage to the bridge deepens, the time-frequency coherence damage factor increases significantly, which can effectively identify the location and degree of damage to the ship-bridge collision.

[0091] In this embodiment, the feasibility of the present invention is verified by conducting a response analysis of the bridge pier under a ship impact load:

[0092] S1: Construct a numerical model of the bridge pier. The dimensions of the finite element model of the pier are length (L=6m), width (W=3m), height (H=16m), the bottom is fixed, and the top is free.

[0093] S2: According to the damage characteristics of bridge collision, the damage is set to breathing crack.

[0094] The state of the crack in the structure is related to the force it is subjected to. Generally, the crack is not always in an open state, but rather performs a nonlinear behavior of periodic opening and closing with the vibration of the structure. The opening and closing behavior of breathing cracks is usually considered to be a contact problem between the surfaces at the crack location of the structure, that is, its behavior can be defined by surface-to-surface contact.

[0095] In surface-to-surface contact, the target surface is allowed to penetrate the contact surface, but the contact surface is not allowed to penetrate the target surface. During the vibration of the pier column, there are three states of breathing cracks, namely, fully open state (no contact between nodes), transition state (partial contact between nodes), and fully closed state (full contact between nodes).

[0096] S3: The crack is located at a height of h = 4.5m from the bottom of the pier. The crack length is set to a, the width is set to b, and no extension occurs. In order to facilitate the definition of the damage degree, the damage degree is defined as:

[0097]

[0098] In the formula, p is the relative depth of the crack, a is the crack length, and L is the pier length. Three damage levels are set, namely p = 0.2, p = 0.5, and p = 0.8, and an undamaged pier is set as a control.

[0099] S4: Apply a uniform force F near the crack location, where F is the ship-bridge impact force obtained during the ship-bridge collision simulation.

[0100] S5: Install a wall-climbing robot on the target bridge pier, set up a sensor collection device for each side of the pier, that is, collect the acceleration response of symmetrical nodes 1, 3, 2, and 4 at each height. The wall-climbing robot moves from top to bottom and collects once every 2m. Define different height positions as a, b, c, ..., i, a total of 9 height positions, and construct a 9*4 acceleration time series H. The sensor collection positions are as follows: Figure 3 shown.

[0101] S6: Taking the symmetric nodes 2 and 4 at the height position f as an example, draw the time-frequency coherence spectrum of the two node sequences under different basis functions, and calculate their coherence spectrum entropy H respectively c ,like Figure 4 As shown, Figure 4 (a) is the Morlet wavelet basis function, and the coherent spectral entropy is 10.6157; Figure 4 (b) is the Dog wavelet basis function, and the coherent spectral entropy is 6.8329; Figure 4 (c) is the 4th order Paul wavelet basis function, and the coherent spectral entropy is 8.2761. It can also be observed from the figure that (a) has more fluctuation information than (b) and (c), which is also important information for judging the damage of the bridge. Based on this, the optimal basis function is selected to calculate the local coefficient of the time series in the time-frequency space.

[0102] S7: Taking symmetric nodes 2 and 4 as examples, calculate the local correlation coefficient of the time series in the time-frequency space under the optimal basis function and draw the time-frequency coherence spectrum. Figure 5 As shown, Figure 5 (a) is an undamaged pier. Figure 5(b) is a damaged pier. When the pier structure is undamaged, the time-frequency coherence spectrum has no fluctuations, and the local time-frequency correlation coefficient is 1. In contrast, the time-frequency coherence spectrum of the damaged structure shows periodic fluctuations within a certain time-frequency range, which is caused by the nonlinear behavior of the breathing crack when the pier column vibrates. Based on this, this method can clearly determine the occurrence of ship-bridge collision damage.

[0103] S8: If it is determined that the bridge collision occurs, calculate the time-frequency coherence damage factor ∈ and draw the damage factor trajectory curve. Figure 6 , 7 It can be seen that in the absence of damage, the time-frequency loss factor is almost 0. As the degree of cracks increases, the fluctuation of the time-frequency coherence spectrum deepens, and the time-frequency loss factor between different nodes gradually increases, which can effectively characterize the degree of damage to the bridge. At the same time, the damage location can be accurately identified by highlighting the damage factor trajectory curve at different heights.

[0104] The above-mentioned embodiments have confirmed the effectiveness of the present invention in identifying the characteristics of ship-bridge collision damage, and provided a basic methodological support for establishing ship-bridge collision damage assessment technology.

[0105] The above is a bridge damage assessment method caused by ship collision provided by one embodiment of this embodiment. Based on the same idea, this embodiment also provides a corresponding bridge damage assessment system caused by ship collision. The specific definition of the bridge damage assessment system caused by ship collision can refer to the definition of the bridge damage assessment method caused by ship collision in the above text, which will not be repeated here. Each module in the above-mentioned bridge damage assessment system caused by ship collision can be fully or partially implemented by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0106] This embodiment also provides a computer-readable storage medium, which stores a computer program, which can be used to execute the above Figure 1 A bridge damage assessment method induced by ship impact is provided.

[0107] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0108] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for assessing bridge damage caused by ship collision, characterized in that: The following steps are involved: Collecting acceleration response signal arrays at different heights and positions of the bridge piers hit by the ship, and generating a time series matrix of the acceleration response signals according to the acceleration response signal arrays; According to the time series matrix, the time-frequency coherence spectrum under different basis functions is plotted, and the coherence spectrum entropy is obtained; Based on the principle of information entropy, the information volume of the time-frequency coherence spectrum in different basis function spaces is measured according to the coherence spectrum entropy to determine the optimal basis function; Obtain the local correlation coefficient of the time series matrix in the time-frequency space under the optimal basis function, and draw the time-frequency coherence spectrum; evaluate the correlation dependence between time series based on the local correlation coefficient and the time-frequency coherence spectrum, and judge whether the ship bridge collision damage occurs; If collision occurs, calculate the time-frequency coherence impairment factor at different positions of the time series matrix and draw the trajectory curve of the time-frequency coherence impairment factor; The damage position and damage degree are determined according to the maximum value of the time-frequency coherence impairment factor trajectory curve.

2. The bridge damage assessment method caused by ship collision according to claim 1, characterized in that: The method of collecting acceleration response signal arrays at different heights and positions of the bridge struck by a ship comprises the following steps: According to the characteristics of the target bridge pier to be measured, a wall-climbing robot is installed; the wall-climbing robot is evenly spaced with at least one acceleration sensor on each side of the bridge pier; The wall-climbing robot is driven to move from top to bottom or from bottom to top along the bridge pier to scan the bridge pier. The acceleration response signal array at different heights and positions of the bridge pier is collected by the acceleration sensor to generate a time series matrix.

3. The bridge damage assessment method caused by ship collision according to claim 2, characterized in that: The time series matrix is ​​shown as follows: Among them, m is the total number of pier sensor levels, 1≤i≤m; n is the total number of array sensors in each layer, 1≤j≤n; l is the total length of the acquisition time series.

4. The bridge damage assessment method caused by ship collision according to claim 1, characterized in that: The calculation of the local correlation coefficient is shown in the following formula: In the formula, R 2 (a, b) is the local time-frequency correlation coefficient between the two sequences, S is the smoothing operator, and The time series X ij and X ik The wavelet coefficient of , a is the scale factor of the time-frequency transform, and b is the translation factor; In the formula, when j≠k, is about the time series X ij and X ik The cross wavelet transform function is represents its cross wavelet power; when j = k, is about the time series X ij and X ik The autocorrelation wavelet transform function is as shown below: In the formula, * represents complex conjugation.

5. The bridge damage assessment method caused by ship collision according to claim 4 is characterized in that: Also includes: The wavelet function is used as the basis function to calculate the time-frequency coherence value R between time series. 2 Undetermined wavelet coefficients in (a,b) As shown below: Where ψ is the selected wavelet basis function.

6. The bridge damage assessment method caused by ship collision according to claim 5, characterized in that: The calculation of the coherent spectral entropy comprises the following steps: The time-frequency coherence spectrum is divided into N time-frequency planes of equal area. The number of correlation coefficients in each time-frequency plane that pass the 95% significance test is ζ w , (w=1,…,N), the total number of A of the entire time-frequency coherence spectrum that passes the 95% significance test, normalize each area, and get: Based on the idea of ​​information entropy, the coherence spectrum entropy H of the time-frequency coherence spectrum is calculated using the following formula: c : Among them, the coherent spectral entropy H c It represents the intrinsic information content of the time-frequency coherence spectrum. If the entropy value is larger, it means that the time-frequency coherence spectrum contains more information, and its information value is higher.

7. The bridge damage assessment method caused by ship collision according to claim 1, characterized in that: Calculation of the time-frequency coherence impairment factor The following steps are involved: The time-frequency coherence loss factor ∈ is defined as follows: ∈=(AWC Intact - AWC Input ) / AWC Intact Where, AWC Intact It refers to the average value of the time-frequency coherence value of an undamaged structure within a certain time-frequency range; AWC Input It refers to the average value of the time-frequency coherence value of the structure to be tested within a certain time-frequency range.

8. The bridge damage assessment method caused by ship collision according to claim 1, characterized in that: The method of determining the damage position and damage degree according to the maximum value of the bump in the time-frequency coherence impairment factor trajectory curve comprises the following steps: Based on the local correlation coefficient of the time series matrix in the time-frequency space, the Monte Carlo method is used to calculate the coherence of the time series at a 95% significance level, and the time-frequency coherence spectrum is plotted; The time-frequency coherence spectrum fluctuates within a certain time-frequency range. When the degree of fluctuation cannot be restored to stability, it is judged that the bridge collision damage occurs. The degree of fluctuation is represented by the ratio of the number of time-frequency coherence spectra that pass the 95% significance test to the total number. Based on the characteristics of the change of the time-frequency coherence damage factor at the damage location, a trajectory curve of the time-frequency coherence damage factor is drawn. When the bridge is damaged, the time-frequency coherence damage factor will increase suddenly near the damage location, and the damage factor will be almost 0 far away from the damage location. The level where the curve has the maximum value is considered to be the damage location.

9. A bridge damage assessment system caused by ship collision, characterized in that: The system comprises: processor; a memory having stored thereon a computer program executable on the processor; Wherein, when the computer program is executed by the processor, the steps of the bridge damage assessment method caused by ship collision as described in any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a data processing program, and when the data processing program is executed by a processor, the steps of the bridge damage assessment method caused by a ship collision as described in any one of claims 1 to 8 are implemented.

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