Railway roadbed dynamic safety assessment method combined with train-rail coupling analysis

Abstract

The invention discloses a railway roadbed dynamic safety assessment method combined with train-rail coupling analysis, and relates to the technical field of safety assessment, and the method comprises the steps: carrying out retrieval to obtain K unit train marshalling models of K passing trains and K train correlation parameter information; performing track state detection to obtain a track geometric flatness spectrum; obtaining roadbed mechanical parameter information of the local roadbed; establishing a roadbed-rail coupling model; integrating the K unit train marshalling models into the roadbed-rail coupling model to obtain a train-rail coupling dynamic model; and adopting the target construction task to drive the vehicle-rail coupling kinetic model, performing roadbed external disturbance simulation, and outputting a critical working condition space as a railway roadbed safety assessment result. According to the method, the technical problem that the railway roadbed dynamic safety assessment is not accurate enough in the prior art is solved, and the technical effect of improving the railway roadbed dynamic safety assessment precision is achieved by establishing the vehicle-rail coupling dynamic model and performing external disturbance simulation.

Description

Technical Field

[0001] The invention relates to the technical field of safety assessment, and in particular to a method for dynamic safety assessment of railway subgrade combined with vehicle-track coupling analysis. Background Art

[0002] With the continuous expansion of the railway transportation network and the increase in train speed, the dynamic safety assessment of railway subgrade has become particularly important. As an important supporting structure for train operation, the railway subgrade is subjected to a variety of external factors such as train loads, natural environmental impacts, and construction disturbances for a long time, and is prone to settlement, deformation, and decreased stability. Ensuring the safety of the railway subgrade in a complex dynamic environment is crucial to ensuring the stability of train operation and reducing operational risks.

[0003] However, the existing railway subgrade dynamic safety assessment methods mainly rely on static mechanical analysis or limited monitoring data for prediction, lacking accurate dynamic modeling of the train-track-subgrade interaction, and it is difficult to effectively simulate the dynamic impact of external disturbances (such as construction vibration, earthquake, etc.) on the subgrade during train operation. Traditional methods do not adequately assess the subgrade response under different construction disturbance scenarios, resulting in biased assessment results, making it difficult to provide a reliable basis for construction optimization and risk control. Summary of the invention

[0004] The present application provides a method for evaluating the dynamic safety of railway subgrades in combination with vehicle-track coupling analysis, which is used to solve the technical problem that the existing technology is not accurate enough in evaluating the dynamic safety of railway subgrades.

[0005] In view of the above problems, the present application provides a railway subgrade dynamic safety assessment method combined with vehicle-track coupling analysis.

[0006] The present application provides a method for evaluating the dynamic safety of railway subgrade combined with vehicle-rail coupling analysis, the method comprising: According to the railway line code of the railway passing through the target construction area, a passing train association search is performed to obtain K unit train formation models and K train association parameter information of the K passing trains; the track state detection is performed on the target construction area to obtain the track geometry flatness spectrum of the local passing railway; the subgrade mechanical parameter information of the local subgrade is obtained by conducting a roadbed soil property survey on the local passing railway; with the railway line code as the modeling basis, the subgrade simulation coupling is performed according to the track geometry flatness spectrum and the subgrade mechanical parameter information to establish a subgrade-rail coupling model; according to the K train association parameter information, the K unit train formation models are integrated into the subgrade-rail coupling model to obtain a vehicle-track coupling dynamic model; the vehicle-track coupling dynamic model is driven by the target construction task to simulate the external disturbance of the subgrade, and the critical working condition space is output as the railway subgrade safety assessment result.

[0007] In a possible implementation, the vehicle-track coupling dynamic model is driven by a target construction task to simulate the external disturbance of the roadbed, and a critical operating condition space is output as a railway roadbed safety assessment result, including: performing historical disturbance retrieval according to the target construction task to obtain construction external disturbance data; using the construction external disturbance data to drive the vehicle-track coupling dynamic model to perform railway roadbed dynamic simulation to obtain multiple critical operating condition distributions of multiple external disturbance scenarios; performing linear interpolation processing on the multiple critical operating condition distributions of the multiple external disturbance scenarios to output the critical operating condition space; and using the critical operating condition space as a railway roadbed safety assessment result of the railway passing through the target construction area.

[0008] In a possible implementation, a search is performed on the associated passing trains according to the railway line code of the railway passing through the target construction area to obtain K unit train formation models and K train associated parameter information of the K passing trains, including: searching for passing trains according to the railway line code and outputting a train timetable; obtaining K passing trains by aggregating the train timetable; and obtaining K unit train formation models and K train associated parameter information from the vehicle manufacturer based on the vehicle models of the K passing trains.

[0009] In a possible implementation, the railway line code is used as a modeling reference, and roadbed simulation coupling is performed according to the track geometry and flatness spectrum and the roadbed mechanical parameter information to establish a roadbed-rail coupling model, including: retrieving a unit track model according to the railway line code; copying and connecting the unit track model according to the track geometry and flatness spectrum to obtain a local rail model; taking the local rail model as a basic model, performing roadbed simulation coupling on the local rail model according to the roadbed mechanical parameter information, and establishing the roadbed-rail coupling model.

[0010] In a possible implementation, the train-associated parameter information includes train operation dynamic information, train static parameter information and train operation formation information.

[0011] In a possible implementation, the K unit train formation models are integrated into the subgrade-rail coupling model according to the K train-associated parameter information to obtain a vehicle-track coupling dynamic model, including: extracting the first train static parameter information, the first train operation dynamic information and the first train operation formation information from the first train-associated parameter information of the first passing train; applying the first train static parameter information to define the physical properties of the first unit train formation model to obtain the first unit train physical model; using the first train operation formation information and the first train operation dynamic information as simulation constraints to control the dynamic simulation of the first unit train physical model in the subgrade-rail coupling model to obtain the first train dynamic model; according to the second train-associated parameter information, integrating the second unit train formation model into the first train dynamic model to obtain the second train dynamic model; and so on, through superposition simulation, according to the K-2 train-associated parameter information, the dynamic characteristics of the K unit train formation models are sequentially integrated into the subgrade-rail coupling model to complete the construction of the vehicle-track coupling dynamic model.

[0012] In a possible implementation, the first train operation formation information and the first train operation dynamic information are used as simulation constraints to control the dynamic simulation of the first unit train physical model in the roadbed-rail coupling model to obtain a first train dynamic model, including: decomposing the first train operation formation information to obtain a plurality of first train formation characteristics; making formation adjustments to the first unit train physical model with reference to the plurality of first train formation characteristics, and outputting a plurality of first formation train physical models; and integrating the plurality of first formation train physical models into the roadbed-rail coupling model to perform train operation dynamics simulation based on the first train operation dynamic information to obtain the first train dynamic model.

[0013] In a possible implementation, the construction external disturbance data is used to drive the vehicle-track coupling dynamic model to perform a dynamic simulation of the railway subgrade and obtain multiple critical operating condition distributions of multiple external disturbance scenarios, including: aggregating the construction external disturbance data to obtain multiple construction external disturbance characteristics of the multiple external disturbance scenarios; extracting the first train speed extreme value from the first train operation dynamic information; while using the first construction external disturbance characteristic, the first train speed extreme value and multiple first train formation characteristics to drive the vehicle-track coupling dynamic model to perform a dynamic simulation of the railway subgrade, performing a subgrade settlement detection to obtain a first-dimensional settlement operating condition distribution of the first passing train; and so on to obtain the K-dimensional settlement operating condition distributions of the K passing trains; spatially aligning the K-dimensional settlement operating condition distributions to output a first critical operating condition distribution; and so on to obtain multiple critical operating condition distributions of the multiple external disturbance scenarios.

[0014] In a possible implementation, obtaining the first train dynamics model also includes: performing a formation complexity evaluation on the multiple first train formation characteristics to obtain a dynamics simulation sequence; using the dynamics simulation sequence as a constraint and based on the first train operation dynamics information, sequentially integrating the multiple first train formation physical models into the roadbed-rail coupling model to perform train operation dynamics simulation to obtain the first train dynamics model.

[0015] In a possible implementation, a track state detection is performed on the target construction area to obtain a track geometric flatness spectrum of the local through-travel railway, including: presetting a construction disturbance associated scale; extending the construction disturbance associated scale with the target construction area as a starting point to frame a target analysis area; demarcating a track detection interval with the target analysis area as a boundary to obtain the local through-travel railway; and obtaining the track geometric flatness spectrum by performing a track state detection on the local through-travel railway.

[0016] One or more technical solutions provided in this application have at least the following technical effects or advantages: The present application performs a related search for passing trains based on the railway line code of the railway passing through the target construction area, and obtains K unit train formation models and K train related parameter information of the K passing trains; performs track state detection on the target construction area, and obtains the track geometry flatness spectrum of the local passing railway; obtains the subgrade mechanical parameter information of the local subgrade by conducting a roadbed soil property survey on the local passing railway; uses the railway line code as a modeling reference, performs subgrade simulation coupling based on the track geometry flatness spectrum and the subgrade mechanical parameter information, and establishes a subgrade-rail coupling model; integrates the K unit train formation models into the subgrade-rail coupling model based on the K train related parameter information, and obtains a vehicle-track coupling dynamic model; uses the target construction task to drive the vehicle-track coupling dynamic model, performs subgrade external disturbance simulation, and outputs the critical operating condition space as the railway subgrade safety assessment result. The present invention solves the technical problem that the prior art is not accurate enough in evaluating the dynamic safety of railway subgrades, and achieves the technical effect of improving the accuracy of dynamic safety evaluation of railway subgrades by establishing a vehicle-track coupling dynamics model and performing external disturbance simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1A schematic flow chart of a railway subgrade dynamic safety assessment method combined with vehicle-track coupling analysis provided in an embodiment of the present application; Figure 2 A schematic diagram of the process of simulating external disturbances of a railway subgrade in a railway subgrade dynamic safety assessment method combined with vehicle-track coupling analysis provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] The present application provides a method for evaluating the dynamic safety of railway subgrade combined with vehicle-track coupling analysis, which is used to solve the technical problem that the existing technology is not accurate enough in evaluating the dynamic safety of railway subgrade. By establishing a vehicle-track coupling dynamic model and performing external disturbance simulation, the technical effect of improving the accuracy of dynamic safety evaluation of railway subgrade is achieved.

[0020] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0021] It should be noted that any variations of the terms "include" and "have" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or inherent to these processes, methods, products or devices.

[0022] Examples, such as Figure 1 As shown, the present application provides a railway subgrade dynamic safety assessment method combined with vehicle-track coupling analysis, the method comprising: Step S100: performing a search for associated passing trains based on the railway line code of the railway passing through the target construction area, and obtaining K unit train formation models and K train associated parameter information of the K passing trains.

[0023] In an embodiment of the present application, when performing a search for associated passing trains based on the railway line code of the railway passing through the target construction area, first query the train timetable on the line through the railway line code, aggregate the timetable data, and screen out K passing trains. Subsequently, based on the vehicle model information of the K screened passing trains, call the vehicle manufacturer database to obtain the corresponding unit train formation model and train-related parameter information. Among them, the unit train formation model refers to a train model in the railway transportation system that is composed of a locomotive and one or more carriages according to certain rules and requirements and is studied and managed as a basic unit, and the train-related parameter information includes train operation dynamic information, train static parameter information, and train operation formation information, which is used to accurately describe the train's operating status, structural characteristics, and formation method.

[0024] Furthermore, in the method provided in the embodiment of the application, a passing train association search is performed based on the railway line code of the railway passing through the target construction area to obtain K unit train formation models and K train association parameter information of K passing trains, and also includes: Passing trains are retrieved according to the railway line code and a train timetable is output; K passing trains are obtained by aggregating the train timetables; and based on the models of the K passing trains, K unit train formation models and K train-related parameter information are obtained from the vehicle manufacturer.

[0025] In the embodiment of the present application, the railway line code of the railway passing through the target construction area is first used as the query basis to search for passing trains in the railway operation management system or related database. The railway line code is a code used to uniquely identify a specific railway line. The train operation information on the line can be quickly queried through the code, and the train timetable is output, which contains information such as the train number, operating range, departure time, arrival time, and stop stations.

[0026] After obtaining the train schedule, the next step is to process the data, that is, to screen out K passing trains. The core of this step is data aggregation, that is, to extract train information directly related to the target construction area from the schedule and exclude trains that do not pass through the area. The screening criteria are based on the train's running track, passing time period, stop conditions, etc., to ensure that the selected trains can truly reflect the train operation conditions in the construction area. Finally, K passing trains are screened out.

[0027] After determining the K passing trains, the next step is to obtain their detailed train models and operating parameters. Specifically, first extract the vehicle model information of each train, and then call the corresponding unit train marshaling model and train-related parameter information from the vehicle manufacturer database or the railway vehicle archive system. Among them, the unit train marshaling model refers to a train model in the railway transportation system that is composed of a locomotive and one or more carriages according to certain rules and requirements and is studied and managed as a basic unit. The train-related parameter information includes train operation dynamic information, train static parameter information and train operation marshaling information. Through this process, K unit train marshaling models and K train-related parameter information are obtained.

[0028] Furthermore, the method provided in the application embodiment also includes: The train-related parameter information includes train operation dynamic information, train static parameter information and train operation formation information.

[0029] In the embodiment of the present application, the train-related parameter information includes train operation dynamic information, train static parameter information and train operation marshaling information. Among them, the train operation dynamic information includes the operating speed range of the vehicle type, that is, the maximum speed and average speed of the train under different working conditions. The train static parameter information includes parameters such as the total weight of the train, axle weight distribution, and body structure characteristics. The train operation marshaling information includes the head type of the train, the number of carriages, and the marshaling method.

[0030] Step S200: performing track status detection on the target construction area to obtain a track geometric flatness spectrum of the local through railway.

[0031] In an embodiment of the present application, when performing track status detection on the target construction area, the construction disturbance association scale is first preset, that is, the range in which the construction may affect the track status is determined, so as to reasonably assess the extent to which the track is affected. Subsequently, with the target construction area as the center, the preset disturbance association scale is extended outward to frame the target analysis area, thereby ensuring that the track status detection covers all track ranges that may be affected. On this basis, the track detection interval is further delineated with the target analysis area as the boundary, and the local through-travel railway that needs to be monitored is accurately defined. Finally, the track status in the area is measured using track detection equipment, and the data is processed and analyzed to generate a track geometry flatness spectrum.

[0032] The track geometric roughness spectrum is a curve or data that describes the degree of unevenness and distribution of the track's geometric shape. It can reflect the size and frequency of change of geometric deviations such as height, level, track direction, and triangular pits at different locations of the track.

[0033] Furthermore, in the method provided in the embodiment of the application, the track state detection is performed on the target construction area to obtain the track geometric flatness spectrum of the local railway, and further includes: A construction disturbance association scale is preset; the construction disturbance association scale is extended with the target construction area as the starting point to frame the target analysis area; the track detection interval is delineated with the target analysis area as the boundary to obtain the local through-travel railway; the track geometric flatness spectrum is obtained by performing track state detection on the local through-travel railway.

[0034] In the embodiment of the present application, a technical expert first presets a length value according to the type of construction activity to obtain the construction disturbance association scale.

[0035] Next, starting from the target construction area, we expand outward according to the construction disturbance association scale to form a new area. Specifically, we draw a vertical line based on the boundary tangent of the target construction area, and use the length of the vertical line as the construction disturbance association scale. In this way, we extend the influence range of the target construction area outward to determine the target analysis area, which is the area occupied by the target construction area plus the construction disturbance association scale.

[0036] Then, the track inspection interval is delineated with the target analysis area as the boundary. The purpose is to determine the track sections within the target analysis area, that is, to find those tracks that may be affected by construction disturbances. Through this process, the specific monitoring area is clarified, and the local passing railway is obtained, that is, the specific section where the track status needs to be inspected.

[0037] Finally, the track condition of local railways is tested using a track inspection vehicle. The track inspection vehicle is equipped with a laser measurement system and an inertial sensor to measure the geometric condition of the track in real time, collect data on geometric deviations including track height, track direction, horizontal deviation, etc., and finally generate a track geometric flatness spectrum by processing and analyzing these data.

[0038] Step S300: obtaining the subgrade mechanical parameter information of the local subgrade by surveying the subgrade soil characteristics of the local railway.

[0039] In an embodiment of the present application, when investigating the characteristics of the subgrade soil of a local railway, drilling is performed to obtain soil samples. Drilling technology is widely used in soil investigation, and soil samples are obtained by drilling holes at different locations and depths in the construction area. During the drilling process, the operator selects the location and depth of the borehole according to pre-set requirements to ensure that soil samples of representative soil layers can be obtained to help understand the basic composition and hierarchical structure of the soil. Next, the obtained soil samples are sent to the laboratory for a triaxial shear test, which can test the shear strength and deformation characteristics of the soil. In the test, different pressures are applied to the soil samples to test the damage of the soil under shear, thereby obtaining important parameters such as the shear strength and elastic modulus of the soil.

[0040] Then, an unconfined compression test is carried out, which mainly tests the compressive strength of the soil. In the test, the maximum compression force that the soil can withstand is obtained by gradually applying pressure until the soil sample breaks or deforms, reflecting the bearing capacity of the soil. Through this process, the subgrade mechanical parameter information of the local subgrade is obtained, including the elastic modulus, Poisson's ratio, compressive strength, shear strength and other parameters of the soil.

[0041] Step S400: taking the railway line code as a modeling reference, performing roadbed simulation coupling according to the track geometric flatness spectrum and roadbed mechanical parameter information, and establishing a roadbed-rail coupling model.

[0042] In the embodiment of the present application, the corresponding unit track model is first retrieved and obtained based on the railway line code to ensure that the track modeling conforms to the structural characteristics of the target line. Subsequently, based on the track geometric flatness spectrum, the local rail model is constructed by copying and connecting the unit track model, thereby accurately reflecting the geometric shape and unevenness characteristics of the track. Finally, based on the local rail model, combined with the roadbed mechanical parameter information, the interaction between the track and the roadbed is simulated to complete the establishment of the roadbed-rail coupling model.

[0043] Furthermore, in the method provided in the embodiment of the application, the railway line code is used as a modeling reference, and roadbed simulation coupling is performed according to the track geometric flatness spectrum and roadbed mechanical parameter information to establish a roadbed-rail coupling model, which also includes: The unit track model is retrieved according to the railway line code; the unit track model is copied and connected according to the track geometric flatness spectrum to obtain a local rail model; the local rail model is used as a basic model, and the local rail model is coupled with the roadbed simulation according to the roadbed mechanical parameter information to establish the roadbed-rail coupling model.

[0044] In the embodiment of the present application, first, according to the railway line code, the unit track model is retrieved and obtained from the railway engineering database or the track structure modeling software. The unit track model is a representative track structure model, which includes the main components of the track such as rails, sleepers, and ballast, and defines the interaction relationship between them. Specifically, a parametric modeling method can be used to generate a unit track model that conforms to the actual line characteristics according to the parameters such as the curve radius, track gauge, sleeper spacing, and rail specifications of the track.

[0045] After obtaining the unit track model, the track morphology is then expanded according to the track geometry roughness spectrum to construct a local rail model. The track geometry roughness spectrum is a set of data or curves that describes the unevenness of the track, including the size and frequency of geometric deviations such as height, level, track direction, and triangular pits. By using data interpolation methods or spectral analysis techniques, the data of the track geometry roughness spectrum is parsed into track morphology information that can be used for numerical modeling. Then, by copying and connecting the unit track model, the track geometry flatness information is superimposed on the unit track model to obtain a local rail model.

[0046] Then, the local rail model is coupled with the roadbed simulation according to the roadbed mechanical parameter information. Specifically, the finite element method (FEM) is used to divide the roadbed into multiple discrete units, and each unit is assigned a value according to the roadbed mechanical parameters to simulate the force characteristics of different roadbed materials. Subsequently, the stress, displacement and settlement response of the track-roadbed system under the action of train loads are analyzed through numerical solution methods, thereby realizing the simulation coupling of the track and the roadbed. Finally, a complete roadbed-rail coupling model is established by integrating the local rail model with the roadbed simulation coupling model. This model can simulate the dynamic interaction between the track and the roadbed under the action of train loads, and predict the deformation, settlement and vibration characteristics of the track under different operating conditions.

[0047] Step S500: Integrate the K unit train formation models into the roadbed-rail coupling model according to the K train-related parameter information to obtain a vehicle-rail coupling dynamics model.

[0048] In the embodiment of the present application, based on K train-related parameter information, K unit train formation models are gradually integrated into the roadbed-rail coupling model, and finally a vehicle-track coupling dynamic model is established. Specifically, the static parameter information, operation dynamic information and formation information of the first passing train are first extracted from the train-related parameter information. These parameters are used to define the physical characteristics of the first unit train formation model, and the first unit train physical model is constructed to ensure accurate simulation of the train structure and dynamic properties.

[0049] Next, the running dynamic information and marshaling information of the first train are used as simulation constraints to control the dynamic behavior of the physical model of the first unit train in the roadbed-rail coupling model, and the construction of the first train dynamic model is completed. This process calculates the interaction between the train wheels and the track through the wheel-rail contact dynamic model, including rolling, slipping, and changes in wheel-rail contact force, thereby simulating the dynamic impact of the train on the track and roadbed during travel.

[0050] Then, based on the train-related parameter information of the second train, the second unit train formation model is integrated into the first train dynamic model using the same method as the first train to form the second train dynamic model. Similarly, K-2 unit train formation models are gradually superimposed in the same way, and dynamic characteristics are matched to ensure that the running status of all trains, track stress conditions and roadbed response characteristics are coordinated, and finally the construction of the vehicle-track coupling dynamic model is completed.

[0051] Furthermore, in the method provided in the embodiment of the application, the K unit train formation models are integrated into the roadbed-rail coupling model according to the K train-related parameter information to obtain the vehicle-rail coupling dynamics model, and further includes: Extract the first train static parameter information, the first train operation dynamic information and the first train operation marshaling information from the first train associated parameter information of the first passing train; use the first train static parameter information to define the physical properties of the first unit train marshaling model to obtain the first unit train physical model; use the first train operation marshaling information and the first train operation dynamic information as simulation constraints to control the dynamic simulation of the first unit train physical model in the roadbed-rail coupling model to obtain the first train dynamic model; according to the second train associated parameter information, integrate the second unit train marshaling model into the first train dynamic model to obtain the second train dynamic model; and so on, through superposition simulation, according to the K-2 train associated parameter information, sequentially integrate the dynamic characteristics of the K unit train marshaling models into the roadbed-rail coupling model to complete the construction of the vehicle-rail coupling dynamic model.

[0052] In the embodiment of the present application, firstly, the first train static parameter information, the first train operation dynamic information and the first train operation marshaling information are extracted from the first train associated parameter information of the first passing train. Among them, the static parameter information includes the axle weight, body mass distribution, suspension system stiffness and damping characteristics of the train. The operation dynamic information includes the speed, acceleration, wheel-rail contact force, braking characteristics, etc. of the train. The operation marshaling information defines the locomotive type, number of carriages, wheelbase distribution and marshaling mode of the train.

[0053] Next, the static parameter information of the first train is applied to the physical property definition of the first unit train formation model to establish the physical model of the first unit train. Specifically, by adopting multi-body dynamics modeling (MBD), the train is split into multiple independent but interacting rigid body units (such as car body, bogie, wheelset, etc.), and each unit is assigned corresponding mass, inertia, stiffness and damping. This physical model can accurately simulate the physical properties and structural characteristics of the train to ensure the correct calculation of the forces acting on the train during operation. The physical model of the first unit train is obtained through this step.

[0054] Subsequently, the running marshaling information and running dynamic information of the first train are used as simulation constraints, and the physical model of the first unit train is introduced into the roadbed-rail coupling model for dynamic simulation calculation to obtain the first train dynamic model. In this step, the running marshaling information of the first train is first decomposed into a plurality of first train marshaling characteristics, which describe the different components and structural characteristics of the train. According to these marshaling characteristics, the first unit train physical model is adjusted to generate a plurality of first marshaling train physical models. Then, according to the running dynamic information of the first train, these adjusted physical models are integrated into the roadbed-rail coupling model, and the train running dynamics simulation is used for simulation to finally obtain the first train dynamic model.

[0055] Next, based on the train-related parameter information of the second train, the second unit train formation model is integrated into the first train dynamics model to obtain the second train dynamics model. This process is similar to the modeling of the first train. First, the physical model of the second train is generated based on the static parameters, running dynamics information and formation information of the second train. Subsequently, the interaction force between the second train and the track is simulated through the wheel-rail contact force model, and it is added to the first train dynamics model. In this way, the second train dynamics model is finally obtained, and the dynamic coupling between the first train and the second train is completed.

[0056] Similarly, following the same steps, the dynamic characteristics of K-2 unit train formation models are gradually integrated into the established dynamic model for superposition simulation. Each superposition is based on the corresponding train-related parameter information, and each time a new train is added, the force conditions and dynamic constraints in the existing model are adjusted to ensure that the dynamic behaviors of all trains are coordinated in the multi-train system. Finally, through this process, the dynamic characteristics of all K trains are gradually integrated to obtain a complete vehicle-track coupling dynamic model.

[0057] Furthermore, in the method provided in the embodiment of the application, the first train running marshaling information and the first train running dynamic information are used as simulation constraints to control the dynamic simulation of the first unit train physical model in the roadbed-rail coupling model to obtain the first train dynamic model, and further includes: Decomposing the first train operation marshaling information to obtain a plurality of first train marshaling characteristics; adjusting the marshaling of the first unit train physical model with reference to the plurality of first train marshaling characteristics, and outputting a plurality of first marshaling train physical models; integrating the plurality of first marshaling train physical models into the roadbed-rail coupling model to perform train operation dynamics simulation according to the first train operation dynamics information, and obtaining the first train dynamics model.

[0058] In the embodiment of the present application, the running marshaling information of the first train is firstly decomposed to extract a plurality of marshaling features of the first train, such as marshaling order, number of carriages, locomotive type, carriage type, vehicle wheelbase, etc. By extracting these features, the marshaling structure of the train and its possible impact on the track and roadbed can be accurately reflected.

[0059] Next, refer to multiple first train formation characteristics to adjust the formation of the first unit train physical model. Based on the train formation order, number of carriages, locomotive type and other information, adjust the physical properties such as mass distribution, suspension system stiffness, damping characteristics, etc. in the first unit train physical model to ensure that the model can truly reflect the train operation status under different formation configurations. In this process, the multi-body dynamics modeling (MBD) method is used to divide the train into multiple rigid body units (such as car body, bogie, wheelset, etc.), and assign appropriate physical properties to each unit to simulate its movement on the track. Through this step, multiple first-formation train physical models are finally obtained, each model represents a different train formation configuration, and can provide a basis for subsequent dynamic simulation.

[0060] Finally, based on the running dynamic information of the first train, such as the train's maximum running speed, acceleration, traction, braking force, etc., multiple physical models of the first train formation are integrated into the roadbed-rail coupling model to simulate the train running dynamics. In this process, by combining the physical model of the train with the track model and the roadbed model, the finite element method (FEM) and rigid-flexible coupling dynamics method are used to simulate the dynamic response of the train under different operating conditions. During the simulation calculation process, factors such as the train's wheel-rail contact force, the force distribution of the track, and the deformation and settlement of the roadbed are considered, and finally the first train dynamics model is obtained.

[0061] Furthermore, the method provided in the application embodiment also includes: Performing a formation complexity evaluation on the multiple first train formation characteristics to obtain a dynamic simulation sequence; taking the dynamic simulation sequence as a constraint and based on the first train operation dynamics information, sequentially integrating the multiple first train formation physical models into the roadbed-rail coupling model to perform train operation dynamics simulation to obtain the first train dynamics model.

[0062] In the embodiment of the present application, the complexity of the formation is evaluated for a plurality of first train formation features, and the evaluation measures the complexity of the formation by analyzing the type of goods transported by the train. Different types of goods (such as heavy goods, light goods, liquid goods, bulk goods, etc.) have different effects on the dynamic behavior of the train and the track system. For example, heavy freight trains usually have larger axle weights and traction requirements, which will require the train to have higher stiffness and stronger car connections, while light freight trains may exhibit greater vibration and track impact due to their lighter loads. Bulk goods may increase the vibration and uneven load distribution of the train during operation due to the instability of the goods themselves, thereby making the impact on the track and roadbed more complex. Therefore, the evaluation of formation complexity not only depends on the train structural parameters such as the number of cars, car spacing and connection mode, but also needs to evaluate their effects on the train formation structure and dynamic response according to the type of goods. This process is simulated by multi-body dynamics modeling (MBD), and by gradually introducing train formation characteristics of different cargo types, the dynamic behavior of the train under different formation configurations and cargo conditions is simulated, and a dynamic simulation sequence is generated. This simulation sequence provides constraints for the construction of subsequent models.

[0063] Next, with the dynamic simulation sequence as a constraint, multiple physical models of the first marshaling trains are sequentially integrated into the roadbed-rail coupling model to perform train operation dynamics simulation based on the dynamic information of the first train operation (such as the maximum operating speed). The dynamic information of the first train operation reflects the working conditions of the train and its performance under different working conditions. These data are collected through the train operation monitoring system (TCMS) to ensure that the actual operating status of the train can be accurately reflected in the simulation. For example, heavy freight trains may need to simulate greater traction, higher operating speeds, and stronger braking forces, while light freight trains may run at lower speeds, and the impact on the track is mainly manifested as greater vibration and smaller track impact force. To this end, the finite element method (FEM) is first used to simulate the track and roadbed, simulate the elastic response of the track and roadbed, and use the rigid-flexible coupling dynamics method to connect the physical model of the train and the track-roadbed system to accurately simulate the vertical vibration, lateral vibration, wheel-rail contact force and track force distribution of the train. As the number of train configurations increases (e.g., from five to ten or thirteen cars), the simulation model gradually considers the complexity of the connection between cars, such as hard joints, soft joints, and changes in the suspension system between cars, which will affect the dynamic behavior of the train and the response of the track system. In this way, the forces exerted by the train on the track and roadbed are simulated for each different configuration, ensuring that the simulation results can provide consistency and accuracy under different configurations.

[0064] Finally, after gradually integrating multiple physical models of the first marshaling train and performing train operation dynamics simulation, the first train dynamics model is obtained.

[0065] Step S600: using the target construction task to drive the vehicle-track coupling dynamics model, simulating the external disturbance of the roadbed, and outputting the critical working condition space as the railway roadbed safety assessment result.

[0066] In the embodiment of the present application, the target construction task is first used to drive the vehicle-track coupling dynamics model, and the external disturbance simulation of the railway subgrade is performed by setting the specific disturbance conditions in the construction task (such as vibration and load of construction equipment). These disturbance conditions are derived from historical disturbance data, and are dynamically simulated by driving the model to simulate the possible impact on the track and subgrade during the construction process. In this process, by analyzing different external disturbance scenarios, multiple critical operating condition distributions are obtained. These distributions reflect the dynamic responses of the railway subgrade such as maximum deformation and stress under different construction disturbances. Finally, these critical operating condition distributions are processed by linear interpolation to output the critical operating condition space, which can fully represent the safety status of the railway subgrade under the disturbance conditions in the target construction area. Finally, the critical operating condition space is used as the safety assessment result of the railway subgrade.

[0067] Further, such as Figure 2 As shown, in the method provided in the embodiment of the application, the vehicle-track coupling dynamic model is driven by the target construction task to simulate the external disturbance of the roadbed, and the critical working condition space is output as the railway roadbed safety assessment result, which also includes: Perform historical disturbance retrieval according to the target construction task to obtain construction external disturbance data; use the construction external disturbance data to drive the vehicle-track coupling dynamics model to perform railway roadbed dynamic simulation to obtain multiple critical operating condition distributions of multiple external disturbance scenarios; perform linear interpolation processing on the multiple critical operating condition distributions of the multiple external disturbance scenarios to output the critical operating condition space; use the critical operating condition space as a railway roadbed safety assessment result of the railway passing through the target construction area.

[0068] In an embodiment of the present application, firstly, a historical disturbance search is performed based on the target construction task. The purpose of this step is to obtain the external disturbance data generated in the past construction, including key information such as the time of occurrence, duration, frequency range, and acceleration amplitude. These data are obtained by querying the construction equipment monitoring system or the ground vibration monitoring instrument, or by analyzing construction records and historical data. Specifically, by using data mining methods to sort and screen the disturbance data in historical construction, various disturbance sources related to construction (such as vibration of heavy machinery, blasting operations, ground load changes, etc.) are identified. Through this step, the external disturbance data of the construction is obtained.

[0069] Subsequently, the vehicle-track coupling dynamics model is driven by the construction external disturbance data to perform dynamic simulation of the railway subgrade. Specifically, the construction external disturbance data is first aggregated to extract the construction external disturbance characteristics under multiple external disturbance scenarios, including the type, intensity, frequency and duration of the disturbance. Then, the speed extremes, i.e., the highest and lowest speeds of the train under different operating conditions, are extracted from the dynamic information of the first train operation. On this basis, the vehicle-track coupling dynamics model is driven to perform dynamic simulation of the railway subgrade in combination with the speed extremes and multiple marshaling characteristics of the first train. During the simulation process, the subgrade settlement detection is performed to obtain the first-element settlement condition distribution of the first passing train, i.e., the maximum settlement value caused by the train on the track and subgrade in the simulation results. Afterwards, through the same process, K passing trains are simulated in turn to obtain the K-element settlement condition distribution, and spatial alignment is performed to output the first critical condition distribution. This process is repeated for each disturbance scenario, and finally multiple critical condition distributions for multiple external disturbance scenarios are obtained.

[0070] Next, multiple critical operating condition distributions for multiple external disturbance scenarios are linearly interpolated to smooth and connect the critical operating condition data obtained under different external disturbance scenarios. The purpose of this process is to interpolate and smooth the critical operating condition data under different disturbance conditions to obtain a continuous critical operating condition space. By using the linear interpolation method, the subgrade behavior under other possible conditions is inferred based on the known critical operating condition points. For example, for construction vibrations of different frequencies and durations, linear interpolation is used to estimate the critical deformation or failure mode that may occur in the subgrade under these conditions. The result of this step is a critical operating condition space that fully reflects the safety status of the railway subgrade under construction disturbance conditions.

[0071] Finally, the critical operating space is used as the railway subgrade safety assessment result of the railway passing through the target construction area. This process is to output the final safety assessment based on the above simulation results. The critical operating space comprehensively shows whether the deformation, stress, settlement, etc. of the railway subgrade have reached the critical safety threshold under different construction disturbance conditions, that is, whether there is a risk of failure.

[0072] Furthermore, in the method provided in the embodiment of the application, the construction external disturbance data is used to drive the vehicle-track coupling dynamics model to perform a dynamic simulation of the railway subgrade, and multiple critical operating condition distributions of multiple external disturbance scenarios are obtained, which also includes: Aggregate the construction external disturbance data to obtain multiple construction external disturbance features of the multiple external disturbance scenarios; extract the first train speed extreme value from the first train operation dynamic information; while using the first construction external disturbance feature, the first train speed extreme value and multiple first train formation features to drive the vehicle-track coupling dynamic model to perform railway roadbed dynamic simulation, perform roadbed settlement detection to obtain the first-dimensional settlement condition distribution of the first passing train; and so on to obtain the K-dimensional settlement condition distribution of the K passing trains; spatially align the K-dimensional settlement condition distribution and output a first critical condition distribution; and so on to obtain multiple critical condition distributions of the multiple external disturbance scenarios.

[0073] In an embodiment of the present application, firstly, the external disturbance data of the construction is aggregated, and the disturbance source data related to the construction is collected, which includes key information such as the time when the disturbance occurs, the duration, the frequency range and the acceleration amplitude. The vibration or load change generated during the construction process is recorded through the data acquisition system. Using the data sorting and screening method, all the disturbance data are summarized and divided into multiple external disturbance scenes, each of which represents the disturbance characteristics under different construction conditions. Finally, a data set containing the external disturbance characteristics of multiple construction disturbance scenes is obtained through this process.

[0074] Then, the first train speed extreme value is extracted from the first train operation dynamic information, including the maximum operating speed and the minimum operating speed of the train. This information helps to understand the dynamic performance of the train under different operating conditions and provides speed condition input for subsequent dynamic simulation.

[0075] On this basis, combined with the first construction external disturbance characteristics, the first train speed extreme value and multiple train formation characteristics, the vehicle-track coupling dynamics model is driven to perform dynamic simulation of the railway subgrade. Specifically, by bringing all input data (including construction disturbance characteristics, train speed and formation characteristics) into the model, the interaction between the train and the track and subgrade is simulated using multi-body dynamics modeling (MBD). During the simulation process, special attention is paid to the subgrade settlement detection. By calculating the settlement and deformation of the subgrade under the construction disturbance and train load, the first-dimensional settlement condition distribution of the first passing train is obtained. The output result of this step is the settlement influence of the first train on the subgrade, which reflects the dynamic response of the train under specific construction disturbance conditions.

[0076] Next, by analogy, we get the K-yuan settlement condition distribution of K passing trains. Each train is calculated through the same dynamic simulation process as before to obtain the settlement impact of each train on the track and roadbed. In each simulation, different train formation characteristics, operating conditions and construction disturbance data are input to calculate the settlement and deformation of each train under different disturbance conditions. Through this step, we finally get the K-yuan settlement condition distribution of K passing trains, which is used to describe the impact of multiple trains under the same construction disturbance conditions.

[0077] Then, the K-element settlement condition distributions are spatially aligned. By aligning the coordinate systems, the settlement data of all trains are mapped to a unified coordinate system, ensuring that the impact of each train on the track and roadbed can be compared and combined. The purpose of this process is to integrate the settlement data of all trains in the same coordinate system to generate a complete first critical condition distribution.

[0078] Finally, through the above process, multiple critical operating condition distributions of multiple external disturbance scenarios are obtained. For each different construction disturbance scenario, the simulation and data processing are repeated to generate critical operating condition distributions under different conditions. These distributions provide the safety status of the railway subgrade under different construction disturbance conditions.

[0079] In the embodiments of the present application, in summary, the embodiments of the present application have at least the following technical effects: The present application performs a related search for passing trains based on the railway line code of the railway passing through the target construction area, and obtains K unit train formation models and K train related parameter information of the K passing trains; performs track state detection on the target construction area, and obtains the track geometry flatness spectrum of the local passing railway; obtains the subgrade mechanical parameter information of the local subgrade by conducting a roadbed soil property survey on the local passing railway; uses the railway line code as a modeling reference, performs subgrade simulation coupling based on the track geometry flatness spectrum and the subgrade mechanical parameter information, and establishes a subgrade-rail coupling model; integrates the K unit train formation models into the subgrade-rail coupling model based on the K train related parameter information, and obtains a vehicle-track coupling dynamic model; uses the target construction task to drive the vehicle-track coupling dynamic model, performs subgrade external disturbance simulation, and outputs the critical operating condition space as the railway subgrade safety assessment result. The present invention solves the technical problem that the prior art is not accurate enough in evaluating the dynamic safety of railway subgrades, and achieves the technical effect of improving the accuracy of dynamic safety evaluation of railway subgrades by establishing a vehicle-track coupling dynamics model and performing external disturbance simulation.

[0080] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0081] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0082] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A railway subgrade dynamic safety assessment method combined with vehicle-track coupling analysis is characterized by: The method comprises: According to the railway line code of the railway passing through the target construction area, the passing train association search is performed to obtain K unit train formation models and K train association parameter information of the K passing trains; Performing track status detection on the target construction area to obtain a track geometric flatness spectrum of the local railway; By conducting a survey of the characteristics of the subgrade soil of the local railway, the subgrade mechanical parameter information of the local subgrade is obtained; Taking the railway line code as a modeling benchmark, performing roadbed simulation coupling according to the track geometric flatness spectrum and roadbed mechanical parameter information, and establishing a roadbed-rail coupling model; According to the K train-related parameter information, the K unit train formation models are integrated into the roadbed-rail coupling model to obtain a vehicle-rail coupling dynamic model; The vehicle-track coupling dynamics model is driven by the target construction task to simulate the external disturbance of the roadbed, and the critical working condition space is output as the railway roadbed safety assessment result.

2. The railway subgrade dynamic safety assessment method combined with vehicle-track coupling analysis according to claim 1 is characterized in that: The vehicle-rail coupling dynamics model is driven by a target construction task to simulate external disturbances of the roadbed, and a critical working condition space is output as a railway roadbed safety assessment result. The method includes: Perform historical disturbance retrieval based on the target construction task to obtain external disturbance data of the construction; The vehicle-track coupling dynamics model is driven by the construction external disturbance data to perform a dynamic simulation of the railway subgrade, and a plurality of critical operating condition distributions of a plurality of external disturbance scenarios are obtained; Performing linear interpolation processing on the distribution of multiple critical operating conditions of the multiple external disturbance scenarios, and outputting the critical operating condition space; The critical operating condition space is used as a railway subgrade safety assessment result of the railway passing through the target construction area.

3. The method for dynamic safety assessment of railway subgrade combined with vehicle-track coupling analysis according to claim 2, characterized in that: According to the railway line code of the railway passing through the target construction area, a passing train association search is performed to obtain K unit train formation models and K train association parameter information of the K passing trains, and the method includes: Searching for passing trains according to the railway line code and outputting a train timetable; By aggregating the train schedules, K passing trains are obtained; Based on the vehicle types of the K passing trains, K unit train formation models and K train-related parameter information are obtained from the vehicle manufacturer.

4. The railway subgrade dynamic safety assessment method combined with vehicle-track coupling analysis according to claim 1, characterized in that: Taking the railway line code as a modeling reference, performing roadbed simulation coupling according to the track geometric flatness spectrum and roadbed mechanical parameter information, and establishing a roadbed-rail coupling model, the method includes: Retrieving a unit track model according to the railway line code; According to the track geometric flatness spectrum, the unit track model is copied and connected to obtain a local rail model; The local rail model is used as a basic model, and roadbed simulation coupling is performed on the local rail model according to the roadbed mechanical parameter information to establish the roadbed-rail coupling model.

5. The railway subgrade dynamic safety assessment method combined with vehicle-track coupling analysis according to claim 3 is characterized in that: The train-related parameter information includes train operation dynamic information, train static parameter information and train operation formation information.

6. The railway subgrade dynamic safety assessment method combined with vehicle-track coupling analysis according to claim 5, characterized in that: According to the K train-related parameter information, the K unit train formation models are integrated into the roadbed-rail coupling model to obtain a vehicle-rail coupling dynamic model. The method includes: Extracting first train static parameter information, first train operation dynamic information and first train operation marshaling information from first train associated parameter information of a first passing train; Applying the first train static parameter information to define the physical properties of the first unit train marshaling model to obtain the first unit train physical model; Using the first train running marshaling information and the first train running dynamic information as simulation constraints, controlling the dynamic simulation of the first unit train physical model in the roadbed-rail coupling model, and obtaining a first train dynamic model; Integrating the second unit train formation model into the first train dynamics model according to the second train associated parameter information to obtain a second train dynamics model; By analogy, through superposition simulation, according to the K-2 train-related parameter information, the dynamic characteristics of the K unit train formation models are integrated into the roadbed-rail coupling model in turn to complete the construction of the vehicle-rail coupling dynamic model.

7. The method for dynamic safety assessment of railway subgrade combined with vehicle-track coupling analysis according to claim 6, characterized in that: The first train running formation information and the first train running dynamic information are used as simulation constraints to control the dynamic simulation of the first unit train physical model in the roadbed-rail coupling model to obtain a first train dynamic model, the method comprising: Decomposing the first train running marshaling information to obtain a plurality of first train marshaling features; Referring to the plurality of first train formation characteristics, adjusting the formation of the first unit train physical model, and outputting a plurality of first train formation physical models; According to the first train operation dynamics information, the plurality of first marshaling train physical models are integrated into the roadbed-rail coupling model to perform train operation dynamics simulation to obtain the first train dynamics model.

8. The railway subgrade dynamic safety assessment method combined with vehicle-track coupling analysis according to claim 7, characterized in that: The vehicle-track coupling dynamics model is driven by the construction external disturbance data to perform a dynamic simulation of the railway subgrade, and multiple critical operating condition distributions of multiple external disturbance scenarios are obtained. The method includes: Aggregating the construction external disturbance data to obtain multiple construction external disturbance features of the multiple external disturbance scenarios; Extracting a first train speed extreme value from the first train running dynamic information; In the process of driving the vehicle-track coupling dynamics model to perform a dynamic simulation of a railway subgrade by using the first construction external disturbance feature, the first train speed extreme value and a plurality of first train formation features, a subgrade settlement detection is performed to obtain a first-element settlement condition distribution of a first passing train; By analogy, the K-yuan settlement condition distribution of the K passing trains is obtained; Spatially aligning the K-dimensional settlement condition distribution and outputting the first critical condition distribution; By analogy, multiple critical operating condition distributions of the multiple external disturbance scenarios are obtained.

9. The railway subgrade dynamic safety assessment method combined with vehicle-track coupling analysis according to claim 7, characterized in that: The method further comprises: Performing a formation complexity evaluation on the plurality of first train formation characteristics to obtain a dynamic simulation sequence; Taking the dynamic simulation sequence as a constraint and according to the first train operation dynamic information, the multiple first marshaling train physical models are sequentially integrated into the roadbed-rail coupling model to perform train operation dynamics simulation to obtain the first train dynamics model.

10. The railway subgrade dynamic safety assessment method combined with vehicle-track coupling analysis according to claim 1, characterized in that: Performing track status detection on the target construction area to obtain a track geometric flatness spectrum of a local railway, the method comprising: Preset construction disturbance correlation scale; Taking the target construction area as a starting point, extending the construction disturbance association scale to frame the target analysis area; Taking the target analysis area as the boundary, the track detection interval is delineated to obtain the local passing railway; The track geometric flatness spectrum is obtained by performing track status detection on the local railway.

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