Method, device and medium for evaluating post-earthquake driving vulnerability of high-speed railway bridge

Abstract

This invention relates to the field of post-earthquake assessment technology for railway bridges, specifically providing a method, equipment, and medium for assessing the post-earthquake vulnerability of high-speed railway bridges. The method includes: establishing a seismic response analysis model for the track-bridge system and a three-dimensional coupled dynamic model of the train-track-bridge system; constructing a post-earthquake composite track surface irregularity sample library; proposing a track surface smoothness index based on high-speed train comfort; establishing a mapping relationship between the track surface smoothness index and post-earthquake train performance indices; classifying the track surface smoothness index into four levels based on the post-earthquake train performance loss state of the track-bridge system; and establishing vulnerability curves of the track-bridge system based on train performance under different train performance loss states. This invention achieves quantitative assessment of performance-oriented functional loss; it can quantitatively provide the probability of occurrence of each level of train performance loss under different seismic intensities, providing a scientific probabilistic basis for rapid post-earthquake assessment, repair decisions, and seismic design of high-speed railway bridges.

Description

Technical Field

[0001] This invention relates to the field of post-earthquake assessment technology for railway bridges, and in particular to a method, equipment, and medium for assessing the post-earthquake vulnerability of high-speed railway bridges. Background Technology

[0002] As a core infrastructure of high-speed railways, the track-bridge system's structural performance directly affects the smoothness, comfort, and safety of train operation. Damage to the track structure under seismic loads can lead to degradation of train operation functions, and in severe cases, even cause major safety accidents such as derailments. Therefore, ensuring the operational safety of the track-bridge system and its post-earthquake functional repairability has become an important topic in high-speed railway seismic resistance research.

[0003] In recent years, seismic vulnerability analysis has gradually become an important tool for assessing the seismic performance of structures. It uses probabilistic methods to describe the likelihood of a structure reaching various damage states under different seismic intensities, providing a quantitative basis for risk control and seismic decision-making. However, most existing seismic vulnerability studies focus on the dynamic response analysis of the structure itself, neglecting the degradation patterns and probabilistic assessments of the operational functions of track-bridge systems under seismic loading. For high-speed railway systems, focusing solely on structural bearing capacity is far from sufficient to meet operational safety requirements; seismic damage assessment methods based solely on structural safety cannot evaluate the post-earthquake performance loss of the track-bridge system.

[0004] In view of the above problems, there is an urgent need to propose a method, equipment and medium for assessing the post-earthquake vulnerability of high-speed railway bridges based on train performance. Summary of the Invention

[0005] The purpose of this invention is to provide a method, equipment, and medium for assessing the post-earthquake vulnerability of high-speed railway bridges. The specific technical solution is as follows: The method for assessing the post-earthquake vulnerability of high-speed railway bridges includes the following steps: S1. Determine the research object and establish a seismic response analysis model for the track-bridge system and a three-dimensional coupled dynamic model for the train-track-bridge system, respectively; S2. Calculate the seismic residual geometric irregularities and seismic dynamic irregularities using the seismic response analysis model of the track-bridge system, and construct a sample library of post-earthquake composite track surface irregularities by combining the initial track irregularities. S3. Propose a track surface smoothness index based on high-speed driving comfort; S4. Based on the post-earthquake track surface composite irregularity sample library, establish the mapping relationship between track surface smoothness index and post-earthquake train performance index, and fit the relationship between the mapping relationship and train running speed. S5. The lateral acceleration of the car body is used as the evaluation index for the loss of train operation function after the earthquake. The loss state of train operation function of the track-bridge system after the earthquake is divided into four levels. According to the mapping relationship between the track surface smoothness index and the lateral acceleration of the car body, the track surface smoothness index is used instead of the lateral acceleration of the car body as the evaluation index for the loss of train operation function after the earthquake. Based on the loss state of train operation function of the track-bridge system after the earthquake, the track surface smoothness index is divided into four levels, and the limit values ​​of the track surface smoothness index under different levels of loss of train operation function are obtained. S6. Establish vulnerability curves of the track-bridge system based on train performance under different train function loss states, and obtain the probability of train function loss level.

[0006] Furthermore, in S2, several near-fault ground motion records are acquired, and these records are input into the track-bridge system seismic response analysis model. Seismic residual geometric irregularities and seismic dynamic irregularities are extracted, and combined with the initial track irregularities, a post-earthquake track surface composite irregularity sample library is constructed.

[0007] Furthermore, S3 includes: Based on sample data from the post-earthquake rail surface composite irregularity sample library, the post-earthquake rail surface composite irregularity variation rate was calculated. And the rate of change of composite irregularities on the track surface after the earthquake. Perform a discrete Fourier transform; Calculate the one-sided amplitude spectrum of the post-earthquake combined track surface irregularity variation rate. and the average value of the single-sided amplitude spectrum within the specified frequency range. ; based on Propose a track surface smoothness index based on high-speed driving comfort .

[0008] Furthermore, the post-earthquake composite irregularity variation rate was investigated. Perform a discrete Fourier transform and express it as... : ; in: The rate of change of composite irregularities on the rail surface after the earthquake; Indicates the data point number. ; For the specified frequency; Represents the natural constant. Represents the imaginary unit. This represents the discrete Fourier transform.

[0009] Furthermore, the one-sided amplitude spectrum of the post-earthquake track surface composite irregularity variation rate. for: ; Average value of the single-sided amplitude spectrum within the specified frequency range for: ; in: Indicates the upper limit of the specified frequency range; Indicates the lower limit of the specified frequency range; Rail surface smoothness index for: ; in: Indicators of track surface smoothness The lower limit of the specified frequency range, Indicators of track surface smoothness The upper limit of the specified frequency range.

[0010] Furthermore, in S4, the post-earthquake driving performance indicators include the lateral acceleration of the vehicle body; the sample data in the post-earthquake track surface composite irregularity sample library are input into the three-dimensional coupled dynamic model of train-track-bridge to obtain the lateral acceleration of the vehicle body at different train operating speeds; The mapping relationship between track surface smoothness index and post-earthquake train performance index is established as follows: ; in: Indicates the lateral acceleration of the vehicle body. Denotes the undetermined coefficients of the linear term. Indicates the undetermined coefficients of the constant term; The mapping relationship between train speed and undetermined coefficients is established as follows: ; in: This indicates the train's speed.

[0011] Furthermore, S6 includes: S6.1 Construct a sample library of post-earthquake composite rail surface irregularities under different seismic motion intensities, and calculate the rail surface smoothness index. ; S6.2, Constructing track surface smoothness index Peak ground acceleration index The linear relationship between the two was established, and the vulnerability curves of the track-bridge system based on the train performance were established under different train function loss states to obtain the probability of train function loss level.

[0012] Furthermore, S6.2 specifically states: Constructing track surface smoothness indicators Peak ground acceleration index The linear regression equation between them is as follows: ; Construct a fragility curve: ; in: The performance level limit for the ultimate damage state is defined, i.e., the limit for track surface comfort index. Peak ground acceleration index The median value of the track surface smoothness index for the corresponding sample; Indicates the probability of reliability. This represents the probability of failure when the structure exceeds its target performance limit. and If all follow a log-normal distribution, then: ; in: The probability that the track surface smoothness requirement exceeds the limit state under a given peak ground acceleration; , These are the uncertainty parameters for structural capacity and demand, respectively. ; It follows a standard normal distribution, represented as: ; in, For integration variables, It is the standard normal distribution function; By combining the track surface comfort index limits under different levels of train function loss states and the linear regression equation between the peak ground acceleration (PGA) index and the track surface comfort index, the probability of the track-bridge system exceeding the limit state under a given PGA is calculated, thus obtaining the vulnerability curves of the track-bridge system based on train performance under different train function loss states: ; Based on the vulnerability curves of the track-bridge system under different loss states of train function, the probability of train function loss level under different peak ground accelerations is obtained.

[0013] An electronic device includes a memory and a processor, wherein the memory stores a computer program; the processor executes the computer program to implement the post-earthquake vulnerability assessment method for high-speed railway bridges as described above.

[0014] A readable storage medium storing a computer program, wherein a processor executes the computer program to implement the post-earthquake vulnerability assessment method for high-speed railway bridges as described above.

[0015] The application of the technical solution of the present invention has at least the following beneficial effects: This invention constructs a post-earthquake composite track surface irregularity sample library, including seismically induced residual geometric irregularities, seismically induced dynamic irregularities, and initial track irregularities. It also establishes a mapping relationship between track surface smoothness indices based on high-speed train comfort and post-earthquake train performance indices, achieving a quantitative assessment of functional losses oriented towards train performance. Furthermore, it utilizes track surface smoothness indices to replace lateral acceleration of the train body as a post-earthquake train performance loss assessment indicator, establishing a correspondence between this indicator and four levels of train performance loss states at different train operating speeds. It obtains track surface smoothness index limits for different levels of train performance loss and, combined with a linear regression model of track surface smoothness indices and peak ground acceleration, constructs vulnerability curves under different train performance loss states. This allows for the quantitative determination of the probability of occurrence of each level of train performance loss under different seismic intensities, providing a scientific probabilistic basis for rapid post-earthquake assessment, repair decisions, and seismic design of high-speed railway bridges.

[0016] In addition to the objectives, features, and advantages described above, the present invention has other objectives, features, and advantages. The invention will now be described in further detail with reference to the figures. Attached Figure Description

[0017] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a flowchart illustrating the post-earthquake vulnerability assessment method for high-speed railway bridges in an embodiment of the present invention. Figure 2(a) shows the mapping relationship between the track surface smoothness index and the lateral acceleration of the car body at a train operating speed of 200 km / h. Figure 2(b) shows the mapping relationship between the track surface smoothness index and the lateral acceleration of the car body at a train operating speed of 250 km / h. Figure 2(c) shows the mapping relationship between the track surface smoothness index and the lateral acceleration of the car body at a train operating speed of 300 km / h. Figure 2(d) shows the mapping relationship between the track surface smoothness index and the lateral acceleration of the car body at a train operating speed of 350 km / h. Figure 3(a) shows the mapping relationship between train speed and the undetermined coefficients of the linear term; Figure 3(b) shows the mapping relationship between train speed and the undetermined coefficients of the constant term; Figure 4 Vulnerability curves of the track-bridge system based on train performance under different train function loss states. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0019] In the description of this invention, it should be noted that the terms "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", "front", "back", "lateral", "longitudinal", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0020] Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0021] Example: See Figure 1 This invention proposes a method for assessing the post-earthquake vulnerability of high-speed railway bridges, comprising the following steps: S1. Determine the research object and establish a seismic response analysis model for the track-bridge system and a three-dimensional coupled dynamic model for the train-track-bridge system, respectively; In this embodiment, the CRTS II type ballastless track-simply supported beam system is taken as the research object. A seismic response analysis model of the track-bridge system and a three-dimensional coupled dynamic model of the train-track-bridge are established. Both models are existing technologies and can be found in the reference: Shaohui L, Lizhong J, Wangbao Z, et al. Study on the equivalent coefficients of seismic-induced track dynamic irregularities based on post-seismic running performance[C] / / Structures. Elsevier, 2024, 68: 107225.

[0022] S2. Calculate the seismic residual geometric irregularities and seismic dynamic irregularities using the seismic response analysis model of the track-bridge system, and construct a sample library of post-earthquake composite track surface irregularities by combining the initial track irregularities. Taking the CRTS II type ballastless track-simply supported beam system as the research object, 40 near-fault ground motion records (including 10 forward-direction effect ground motions, 10 slip-thrust effect ground motions and 20 near-field pulseless ground motions) were selected from the PEER database. The selected 40 ground motion records were input into the track-bridge system seismic response analysis model in S1, and the seismic residual geometric irregularities and seismic dynamic irregularities were extracted. Combined with the initial track irregularities, a post-earthquake track surface composite irregularity sample library was constructed.

[0023] S3. Propose track surface smoothness indicators based on high-speed driving comfort; specifically including: ① Based on sample data from the post-earthquake rail surface composite irregularity sample library, the rate of change of post-earthquake rail surface composite irregularity is calculated using the finite difference method. And the rate of change of composite irregularities on the track surface after the earthquake. Perform a discrete Fourier transform, which is represented as : ; in: The rate of change of composite irregularities on the rail surface after the earthquake; Indicates the data point number. ; For the specified frequency; Represents the natural constant. Represents the imaginary unit. This represents the discrete Fourier transform.

[0024] ② Calculate the single-sided amplitude spectrum of the post-earthquake combined track surface irregularity variation rate. and the average value of the single-sided amplitude spectrum within the specified frequency range. ; One-sided amplitude spectrum of the post-earthquake rail surface composite irregularity variation rate for: ; Average value of the single-sided amplitude spectrum within the specified frequency range for: ; in: Indicates the upper limit of the specified frequency range; This indicates the lower limit of the specified frequency range.

[0025] ③Based on Propose a track surface smoothness index based on high-speed driving comfort ; ; in: Indicators of track surface smoothness The lower limit of the specified frequency range, Indicators of track surface smoothness The upper limit of the specified frequency range.

[0026] In this embodiment, for Vibration-induced uneven wavelength The range is specified to be within 20-200m, because wavelength and frequency are inversely related. Therefore Corresponding frequency range ~ (0.005, 0.5) .

[0027] S4. Based on the post-earthquake track surface composite irregularity sample library, establish the mapping relationship between track surface smoothness index and post-earthquake train performance index, and fit the relationship between this mapping relationship and train running speed; specifically: In this embodiment, the post-earthquake driving performance index includes the vehicle body lateral acceleration; The sample data from the post-earthquake track surface composite irregularity sample library were input into the three-dimensional coupled dynamic model of train-track-bridge to obtain the lateral acceleration of the car body at different train speeds. The mapping relationship between track surface smoothness index and post-earthquake train performance index is established as follows: ; in: Indicates the lateral acceleration of the vehicle body. Denotes the undetermined coefficients of the linear term. Indicates the undetermined coefficients of the constant term; Referring to Figures 2(a)-2(d), the mapping relationship between the track surface smoothness index and the lateral acceleration of the car body under different train operating speeds is obtained.

[0028] As shown in Figures 3(a) and 3(b), the mapping relationship between train speed and undetermined coefficients is established as follows: ; in: This indicates the train's speed.

[0029] S5. Using the lateral acceleration of the car body as the indicator for assessing post-earthquake operational function loss, the post-earthquake operational function loss state of the track-bridge system is divided into four levels; based on the mapping relationship between the track surface smoothness index and the lateral acceleration of the car body, the track surface smoothness index is used instead of the lateral acceleration of the car body as the indicator for assessing post-earthquake operational function loss. Based on the post-earthquake operational function loss state of the track-bridge system, the track surface smoothness index is divided into four levels, and the limit values ​​of the track surface smoothness index under different operational function loss levels are obtained; specifically: Using the lateral acceleration of the vehicle body as the indicator for assessing post-earthquake operational function loss, the post-earthquake operational function loss state of the track-bridge system is divided into four levels: DS1 (intact, 0 < 0.5%). < 0.6 m / s 2 DS2 (Good, 0.6 ≤ <0.8 m / s 2 DS3 (Medium, 0.8 ≤ < 1.0 m / s 2 DS4 (failed) ≥ 1.0 m / s 2 ); Based on the mapping relationship between track surface smoothness index and lateral acceleration of the vehicle body, and considering the post-earthquake operational function loss status of the track-bridge system at different train operating speeds, the track surface smoothness index is also divided into four levels. The limit values ​​of the track surface smoothness index under different operational function loss levels are calculated, as shown in Table 1. Table 1. Track surface smoothness index limits under different train operating speeds and different functional loss levels. S6. Establish vulnerability curves for the track-bridge system based on train performance under different train function loss states, and obtain the probability of train function loss level. Specifically: S6.1 Construct a sample library of post-earthquake composite rail surface irregularities under different seismic motion intensities, and calculate the rail surface smoothness index. ; Each of the 40 selected seismic ground motion records in S2 was adjusted to a peak ground acceleration ratio of 0.2g, 0.3g, 0.4g, 0.5g, 0.6g, 0.8g, and 1.0g. The amplitude-adjusted seismic ground motion records were then input into the track-bridge system seismic response analysis model in S1 to construct a post-earthquake composite track surface irregularity sample library under different seismic ground motion intensities, and the track surface smoothness index was calculated. ; S6.2, Constructing track surface smoothness index Peak ground acceleration index The linear relationship between the two is established, and the vulnerability curves of the track-bridge system based on the train performance are established under different train function loss states to obtain the probability of train function loss level. The IM index was selected as the peak ground acceleration (PGA). EDP ​​index is a track surface smoothness index. The PSDM model is constructed based on log-linear regression and uses the least squares method to... and Perform linear fitting, where Based on the median of 40 EDP indicators at each IM level, a track surface smoothness index is constructed. Peak ground acceleration index The linear regression equation between them is as follows: ; Constructing a vulnerability curve: The structural vulnerability curve represents the conditional probability that the structural response exceeds the structural bearing capacity defined in the failure stage under earthquakes of different intensities, and the probability of failure when the structure exceeds its target ultimate performance. for: ; in: The performance level limit for the determined ultimate damage state corresponds to the values ​​in Table 1, namely the track surface smoothness index limit. Peak ground acceleration index The median value of the track surface smoothness index for the corresponding sample; Indicates the probability of reliability; because and If all follow a log-normal distribution, then a specific failure probability can be expressed as: ; in: The probability that the post-earthquake track smoothness requirement exceeds the limit state under a given peak ground acceleration; , These are the uncertainty parameters for structural capacity and demand, respectively. ; It follows a standard normal distribution, represented as: ; in, For integration variables, It is the standard normal distribution function; Combining the track surface comfort index limits under different levels of train function loss in Table 1 with the linear regression equation between peak ground acceleration and track surface comfort index, the probability of the track-bridge system exceeding the limit state for a given peak ground acceleration is calculated, thus obtaining the vulnerability curves of the track-bridge system based on train performance under different train function loss states: ; Based on train speed For example, the vulnerability curves of the track-bridge system based on train performance under different train function loss states are obtained as follows: Figure 4 As shown; Based on the vulnerability curves of the track-bridge system under different loss states of train function, the probability of loss level of train function under different peak ground accelerations is obtained, so as to realize the post-earthquake vulnerability assessment of the train function of the track-bridge system.

[0030] The present invention also provides an electronic device corresponding to the above embodiments. The electronic device may be a processing device for a client, such as a mobile phone, a laptop, a tablet computer, a desktop computer, etc., to execute the methods of the above embodiments.

[0031] The electronic device of this embodiment includes a memory, a processor, and a computer program stored in the memory; the processor executes the computer program in the memory to implement the steps of the method described in the above embodiment.

[0032] In some implementations, the memory may be high-speed random access memory (RAM), and may also include nonvolatile memory, such as at least one disk storage device.

[0033] In other implementations, the processor can be any type of general-purpose processor, such as a central processing unit (CPU) or a digital signal processor (DSP), and there is no limitation here.

[0034] The present invention also provides a readable storage medium corresponding to the above embodiments, wherein a computer program / instructions are stored thereon. When the computer program / instructions are executed by a processor, they implement the steps of the methods described in the above embodiments.

[0035] A computer-readable storage medium can be a tangible device that holds and stores instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof.

[0036] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of this application can be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0037] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0038] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0039] The above description is only a preferred embodiment of the present invention and does not limit the scope of the present invention. All equivalent structural transformations made under the inventive concept of the present invention using the contents of the present invention specification and drawings, or direct / indirect applications in other related technical fields, are included within the protection scope of the present invention.

Claims

1. A method for assessing the post-earthquake vulnerability of high-speed railway bridges, characterized in that... Includes the following steps: S1. Determine the research object and establish a seismic response analysis model for the track-bridge system and a three-dimensional coupled dynamic model for the train-track-bridge system, respectively; S2. Calculate the seismic residual geometric irregularities and seismic dynamic irregularities using the seismic response analysis model of the track-bridge system, and construct a sample library of post-earthquake composite track surface irregularities by combining the initial track irregularities. S3. Propose a track surface smoothness index based on high-speed driving comfort; S4. Based on the post-earthquake track surface composite irregularity sample library, establish the mapping relationship between track surface smoothness index and post-earthquake train performance index, and fit the relationship between the mapping relationship and train running speed. S5. The lateral acceleration of the car body is used as the evaluation index for the loss of train operation function after the earthquake. The loss state of train operation function of the track-bridge system after the earthquake is divided into four levels. According to the mapping relationship between the track surface smoothness index and the lateral acceleration of the car body, the track surface smoothness index is used instead of the lateral acceleration of the car body as the evaluation index for the loss of train operation function after the earthquake. Based on the loss state of train operation function of the track-bridge system after the earthquake, the track surface smoothness index is divided into four levels, and the limit values ​​of the track surface smoothness index under different levels of loss of train operation function are obtained. S6. Establish vulnerability curves of the track-bridge system based on train performance under different train function loss states, and obtain the probability of train function loss level.

2. The method for assessing the post-earthquake vulnerability of high-speed railway bridges as described in claim 1, characterized in that, In S2, several near-fault ground motion records are acquired. These ground motion records are then input into the track-bridge system seismic response analysis model. Seismic-induced residual geometric irregularities and seismic-induced dynamic irregularities are extracted. Combined with the initial track irregularities, a post-earthquake track surface composite irregularity sample library is constructed.

3. The method for assessing the post-earthquake vulnerability of high-speed railway bridges as described in claim 2, characterized in that, S3 include: Based on sample data from the post-earthquake rail surface composite irregularity sample library, the post-earthquake rail surface composite irregularity variation rate was calculated. And the rate of change of composite irregularities on the track surface after the earthquake. Perform a discrete Fourier transform; Calculate the one-sided amplitude spectrum of the post-earthquake combined track surface irregularity variation rate. and the average value of the single-sided amplitude spectrum within the specified frequency range. ; based on Propose a track surface smoothness index based on high-speed driving comfort .

4. The method for assessing the post-earthquake vulnerability of high-speed railway bridges as described in claim 3, characterized in that, Post-earthquake combined track surface irregularity variation rate Perform a discrete Fourier transform and express it as... : ； in: The rate of change of composite irregularities on the rail surface after the earthquake; Indicates the data point number. ; For the specified frequency; Represents the natural constant. Represents the imaginary unit. This represents the discrete Fourier transform.

5. The method for assessing the post-earthquake vulnerability of high-speed railway bridges as described in claim 4, characterized in that, One-sided amplitude spectrum of the post-earthquake rail surface composite irregularity variation rate for: ； Average value of the single-sided amplitude spectrum within the specified frequency range for: ； in: Indicates the upper limit of the specified frequency range; Indicates the lower limit of the specified frequency range; Rail surface smoothness index for: ； in: Indicators of track surface smoothness The lower limit of the specified frequency range, Indicators of track surface smoothness The upper limit of the specified frequency range.

6. The method for assessing the post-earthquake vulnerability of high-speed railway bridges as described in claim 5, characterized in that, In S4, the post-earthquake driving performance index includes the lateral acceleration of the vehicle body; the sample data in the post-earthquake track surface composite irregularity sample library is input into the three-dimensional coupled dynamic model of train-track-bridge to obtain the lateral acceleration of the vehicle body at different train running speeds; The mapping relationship between track surface smoothness index and post-earthquake train performance index is established as follows: ； in: Indicates the lateral acceleration of the vehicle body. Denotes the undetermined coefficients of the linear term. Indicates the undetermined coefficients of the constant term; The mapping relationship between train speed and undetermined coefficients is established as follows: ； in: This indicates the train's speed.

7. The method for assessing the post-earthquake vulnerability of high-speed railway bridges as described in claim 6, characterized in that, S6 include: S6.1 Construct a sample library of post-earthquake composite rail surface irregularities under different seismic motion intensities, and calculate the rail surface smoothness index. ; S6.2, Constructing track surface smoothness index Peak ground acceleration index The linear relationship between the two was established, and the vulnerability curves of the track-bridge system based on the train performance were established under different train function loss states to obtain the probability of train function loss level.

8. The method for assessing the post-earthquake vulnerability of high-speed railway bridges as described in claim 7, characterized in that, S6.2 specifically means: Constructing track surface smoothness indicators Peak ground acceleration index The linear regression equation between them is as follows: ； Construct a fragility curve: ； in: The performance level limit for the ultimate damage state is defined, i.e., the limit for track surface comfort index. Peak ground acceleration index The median value of the track surface smoothness index for the corresponding sample; Indicates the probability of reliability. This represents the probability of failure when the structure exceeds its target performance limit. and If all follow a log-normal distribution, then: ； in: The probability that the track surface smoothness requirement exceeds the limit state under a given peak ground acceleration; , These are the uncertainty parameters for structural capacity and demand, respectively. ; It follows a standard normal distribution, represented as: ； in, For integration variables, It is the standard normal distribution function; By combining the track surface comfort index limits under different levels of train function loss states and the linear regression equation between the peak ground acceleration (PGA) index and the track surface comfort index, the probability of the track-bridge system exceeding the limit state under a given PGA is calculated, thus obtaining the vulnerability curves of the track-bridge system based on train performance under different train function loss states: ； Based on the vulnerability curves of the track-bridge system under different loss states of train function, the probability of train function loss level under different peak ground accelerations is obtained.

9. An electronic device, characterized in that, The device includes a memory and a processor, wherein the memory stores a computer program; the processor executes the computer program to implement the post-earthquake vulnerability assessment method for high-speed railway bridges as described in any one of claims 1-8.

10. A readable storage medium, characterized in that, The readable storage medium stores a computer program, and the processor executes the computer program to implement the post-earthquake vulnerability assessment method for high-speed railway bridges as described in any one of claims 1-8.

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