Parameter optimization method for floating slab track

Abstract

The invention discloses a floating slab track parameter optimization method, which comprises the steps of determining to-be-optimized parameters of a floating slab track structure, defining constraint conditions and optimization targets, and establishing a parameter optimization model; determining a test design method and a parameter optimization algorithm; aBAQUS software is utilized to establish a floating slab track structure frequency domain finite element model and a vehicle-floating slab track time domain finite element model, and a time-frequency domain batch simulation program of the floating slab track structure is written in combination with Python; calling a time-frequency domain batch simulation program to carry out simulation analysis to obtain a simulation result file; based on the optimization target and the simulation result file, extracting an output parameter value required by the parameter optimization model through a preset processing program; and the output parameter values are input to a modeFRONTIER platform, parameter optimization is carried out, and a floating slab track parameter optimization result is output. By means of the method, the optimized parameter result of the floating slab track with both safety and vibration damping performance can be obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of rail transit simulation, and more specifically, to a method for optimizing the parameters of a floating slab track. Background Art

[0002] With the rapid growth of China's economy and the rapid advancement of the urbanization process, urban rail transit has also developed rapidly. Urban rail transit lines often pass through buildings and densely populated areas. The vibration generated by trains is likely to induce resonance in surrounding buildings, resulting in inaccuracy of precision instrument products, affecting the daily life of surrounding citizens, and in severe cases, causing damage to the buildings themselves and threatening the personal safety of residents. Among all track vibration reduction measures, floating slab tracks are widely used in urban rail transit at home and abroad due to their excellent vibration reduction effect.

[0003] The design of the structural parameters of a floating slab track involves the geometric dimensions of the ballast slab, the stiffness of the fasteners, the damping of the fasteners, the stiffness of the vibration isolators / vibration damping pads, the damping of the vibration isolators / vibration damping pads, etc. These parameters affect the vibration reduction performance of the floating slab track and the safety performance of the train-floating slab track coupling system to varying degrees. Therefore, scientifically and reasonably designing the parameters of the floating slab track structure is a prerequisite for ensuring the safe and effective operation of the structure.

[0004] At present, the existing optimization methods for floating slab tracks at home and abroad mostly adopt the process of "trial calculation - verification - modification", that is, first assume parameters, conduct trial calculations using experimental tests or finite element simulation analysis, and change the parameters one by one according to the trial calculation results. When there are many parameter variables and optimization objectives, this optimization method of "trial calculation - verification - modification" one by one will be too cumbersome. Some optimization methods consider using optimization algorithms to optimize the floating slab track structure. However, most of them use simplified means to evaluate whether the vibration reduction performance of the floating slab track reaches the maximum, and cannot comprehensively consider the influence of each parameter of the floating slab track structure on the structural safety performance and vibration reduction performance from the time-frequency domain perspective.

[0005] Therefore, how to optimize the vibration isolation performance of the floating slab track structure while ensuring the safety of vehicles and track structures, and provide a basis for the parameter design of the floating slab track is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0006] In view of the above problems, the present invention provides a method for optimizing the parameters of a floating slab track to at least solve some of the technical problems mentioned in the above background art.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] The present invention provides a method for optimizing the parameters of a floating slab track, including the following steps:

[0009] S1. Determine the parameters to be optimized for the floating slab track structure, clarify the constraint conditions and optimization objectives of the floating slab track structure; establish a parameter optimization model for the floating slab track structure by combining the parameters to be optimized, constraint conditions and optimization objectives; determine the experimental design method and parameter optimization algorithm;

[0010] S2. Use ABAQUS software to establish a frequency-domain finite element model of the floating slab track structure and a time-domain finite element model of the vehicle-floating slab track, and write a batch simulation program for the time-frequency domain of the floating slab track structure in combination with Python;

[0011] S3. Generate values of the parameters to be optimized based on the constraint conditions and experimental design method, input the values of the parameters to be optimized into the time-frequency domain batch simulation program and conduct simulation analysis to obtain a simulation result file containing time-frequency domain response characteristics;

[0012] S4. Based on the optimization objective and the simulation result file, extract the output parameter values required for the parameter optimization model through a preset processing program;

[0013] S5. Input the output parameter values into the parameter optimization model based on the modeFRONTIER platform, optimize the parameters to be optimized according to the optimization objective and the parameter optimization algorithm, and output the optimization results of the floating slab track parameters.

[0014] Furthermore, select the parameters that need to be optimized from the geometric parameters, fastener parameters and isolator parameters of the floating slab track as the parameters to be optimized.

[0015] Furthermore, use the non-exceedance of the safety index of the floating slab track as the constraint condition;

[0016] The safety index includes the vehicle safety index and the track safety index;

[0017] The vehicle safety index includes: car body acceleration, derailment coefficient and wheel load reduction rate;

[0018] The track safety index includes: track structure displacement and track structure acceleration.

[0019] Furthermore, use the optimal vibration reduction performance of the floating slab track as the optimization objective, and select the vibration isolation rate of the floating slab track and the reaction force of the steel spring as the vibration reduction performance indexes of the floating slab track.

[0020] Furthermore, the steps for establishing the frequency-domain finite element model of the floating slab track structure include:

[0021] Establish rail components and roadbed slab components in ABAQUS software according to the geometric characteristics of the floating slab track;

[0022] Assemble the rail components and the roadbed slab components according to their actual positional relationships, and use spring-damping elements to simulate the fastening model;

[0023] Create a harmonic response analysis step and apply a steady-state swept-frequency excitation on the upper surface of the rail components;

[0024] Modify the keywords of the floating slab track structure frequency-domain finite element model to extract the vibration isolation rate of the floating slab track.

[0025] Furthermore, the steps for establishing the vehicle-floating slab track time-domain finite element model include:

[0026] Establish a car body model, a bogie model, and a wheel set model using rigid body elements according to the geometric characteristics of the train;

[0027] Use solid elements to establish the rail components and the roadbed slab components, and assemble the rail components and the roadbed slab components according to their actual positional relationships;

[0028] Use spring-damping elements to simulate the suspension system between the car body and the bogie, and simulate the suspension system between the bogie and the wheel set;

[0029] Use the history output module to output the wheel-rail interaction force, the car body acceleration, the track structure acceleration, the vertical displacement of the track structure, and the reaction force of the steel spring.

[0030] Furthermore, the steps for writing the time-frequency domain batch simulation program include:

[0031] Obtain the *.inp files corresponding to the floating slab track structure frequency-domain finite element model and the vehicle-floating slab track time-domain finite element model;

[0032] Use Python programming means to modify the parameters to be optimized of the floating slab track in the *.inp file and reserve an interface for modifying the parameters to be optimized.

[0033] Furthermore, step S3 specifically includes:

[0034] The inputting the values of the parameters to be optimized into the time-frequency domain batch simulation program and conducting simulation analysis specifically includes:

[0035] Use the interface for modifying the parameters to be optimized to input the values of the parameters to be optimized into the time-frequency domain batch simulation program, and conduct simulation analysis based on the simulation module in ABAQUS software.

[0036] Furthermore, step S4 specifically includes:

[0037] Use Python to read the result file with the format of *.dat corresponding to the frequency-domain finite element model of the floating slab track, and extract the lowest vibration isolation rate in the low-frequency range and the highest vibration isolation rate in the medium- and high-frequency ranges of the floating slab track;

[0038] Use Python to read the result file with the format of *.odb corresponding to the time-domain finite element model of the vehicle-floating slab track, and extract the results of wheel-rail forces, carbody acceleration, vertical displacement of the track structure, acceleration of the track structure, and reaction forces of the steel springs.

[0039] Furthermore, in the step S5, the following is further included:

[0040] Evaluate whether the current optimization result of the floating slab track parameters converges;

[0041] If it does not converge, repeat steps S3 - S5;

[0042] If it converges, output the current optimization result of the floating slab track parameters.

[0043] As can be seen from the above technical solutions, compared with the prior art, the present invention discloses a method for optimizing the parameters of a floating slab track, which has the following beneficial effects:

[0044] The present invention can not only obtain the influence of different parameters on the vibration reduction performance and safety performance of the floating slab track from the time-frequency domain perspective, but also efficiently realize the optimization of the structural parameters of the floating slab track, making the vibration isolation performance of the floating slab track structure reach the optimal while ensuring the safety of the vehicle and the track structure, providing a reference for the parameter design of the floating slab track, and being of great significance for vibration reduction, noise reduction and green sustainable development of urban rail transit.

[0045] The following will further describe the technical solutions of the present invention in detail through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only the embodiments of the present invention, and those of ordinary skill in the art can also obtain other accompanying drawings according to the provided accompanying drawings without creative efforts.

[0047] Figure 1 It is a schematic flow chart of the method for optimizing the parameters of the floating slab track provided by the embodiment of the present invention.

[0048] Figure 2 It is a schematic structural diagram of the frequency-domain finite element model of the floating slab track structure provided by the embodiment of the present invention.

[0049] Figure 3Schematic diagram of the vehicle-floating slab track time domain finite element model structure provided by the embodiment of the present invention.

[0050] Figure 4 Schematic diagram of the optimization logic relationship provided by the embodiment of the present invention.

[0051] Figure 5 Schematic diagram of the variation law of the input and output parameters with the increase of the iteration times provided by the embodiment of the present invention. Detailed implementation manners

[0052] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0053] The embodiment of the present invention discloses a parameter optimization method for a floating slab track. Refer to Figure 1 as shown, and the method includes the following steps:

[0054] S1. Determine the parameters to be optimized for the floating slab track structure, clarify the constraint conditions and optimization objectives of the floating slab track structure; establish a parameter optimization model for the floating slab track structure in combination with the parameters to be optimized, constraint conditions and optimization objectives; determine the experimental design method and parameter optimization algorithm;

[0055] S2. Use the ABAQUS software to establish a frequency domain finite element model of the floating slab track structure and a vehicle-floating slab track time domain finite element model, and write a time-frequency domain batch simulation program for the floating slab track structure in combination with Python;

[0056] S3. Generate the values of the parameters to be optimized based on the constraint conditions and experimental design method, input the values of the parameters to be optimized into the time-frequency domain batch simulation program and conduct simulation analysis to obtain a simulation result file containing time-frequency domain response characteristics;

[0057] S4. Based on the optimization objective and the simulation result file, extract the output parameter values required for the parameter optimization model through a preset processing program;

[0058] S5. Input the output parameter values into the parameter optimization model based on the modeFRONTIER platform, optimize the parameters to be optimized according to the optimization objective and parameter optimization algorithm, and output the parameter optimization result of the floating slab track.

[0059] Next, the content of each of the above steps will be described in detail.

[0060] In the above step S1, it specifically includes:

[0061] (1) Determine the parameters to be optimized for the floating slab track structure;

[0062] Select the parameters to be optimized from the geometric parameters, fastener parameters, and isolator parameters of the floating slab track as the parameters to be optimized;

[0063] Taking the vertical parameter optimization of the steel spring floating slab track structure as an example, the parameters to be optimized include the vertical stiffness k1 of the fastener, the vertical damping d1 of the fastener, the vertical stiffness k2 of the steel spring, and the vertical damping d2 of the steel spring;

[0064] (2) Define the constraint conditions and optimization objectives of the floating slab track structure;

[0065] 1) Take the safety index of the floating slab track not exceeding the limit as the constraint condition;

[0066] Among them, the safety index includes the vehicle safety index and the track safety index; the vehicle safety index includes: vehicle body acceleration, derailment coefficient, and wheel load reduction rate; the track safety index includes: track structure displacement and track structure acceleration.

[0067] Taking the vertical parameter optimization of the steel spring floating slab track structure as an example, the constraint condition is: the vertical acceleration a of the vehicle body c does not exceed 1 m / s 2 , the derailment coefficient T1 is less than 0.8, the wheel load reduction rate T2 is not greater than 0.6, the vertical displacement y of the rail g does not exceed 4.0 mm, the vertical acceleration a of the rail g does not exceed 2000 m / s 2 , the vertical displacement y of the track slab b does not exceed 3.0 mm, the vertical acceleration a of the track slab b does not exceed 200 m / s 2 ;

[0068] 2) Take the best vibration reduction performance of the floating slab track as the optimization objective, and select the vibration reduction rate of the floating slab track and the reaction force of the steel spring as the vibration reduction performance indexes of the floating slab track;

[0069] Taking the vertical parameter optimization of the steel spring floating slab track structure as an example, the optimization objective of the vertical displacement of the track slab is that while the reaction force F of the steel spring reaches the minimum, the weighted combined value of the lowest vibration reduction rate f 1min in the low-frequency range and the highest vibration reduction rate f 2max in the medium- and high-frequency ranges of the floating slab track reaches the maximum;

[0070] (3) Establish a parameter optimization model for the floating slab track structure by combining the parameters to be optimized, the constraint conditions, and the optimization objectives;

[0071] Taking the vertical parameter optimization of the steel spring floating slab track structure as an example, the range of optimization parameters is set according to the actual application project of the floating slab track. The weights of the lowest vibration isolation rate and the highest vibration isolation rate are set to 0.2 and 0.8 respectively. The established mathematical model is shown in the following formula, and all units use the International System of Units.

[0072]

[0073] Among them, f1 represents the vibration isolation rate of the floating slab track in the low-frequency range; f 1min represents the lowest vibration isolation rate of the floating slab track in the low-frequency range; f2 represents the vibration isolation rate of the floating slab track in the medium- and high-frequency ranges; f 2max represents the highest vibration isolation rate of the floating slab track in the medium- and high-frequency ranges.

[0074] (4) Define the experimental design method and parameter optimization algorithm for the floating slab track structure;

[0075] Select the random sequence method as the experimental design method to generate the initial population, and select NSGA-II as the optimization algorithm.

[0076] In the above step S2, it specifically includes:

[0077] (1) Use ABAQUS software to establish a frequency-domain finite element model of the floating slab track structure:

[0078] According to the geometric characteristics of the floating slab track, establish the rail component and the roadbed slab component in ABAQUS software; assemble the rail component and the roadbed slab component according to the actual position relationship, and use spring-damper elements to simulate the fastener model; create a harmonic response analysis step and apply a steady-state swept-frequency excitation on the upper surface of the rail component; modify the keyword "Keywords" of the frequency-domain finite element model of the floating slab track structure to extract the vibration isolation rate of the floating slab track.

[0079] Taking the 4.8m standard steel spring floating slab track as an example, use solid elements to simulate the rail and the roadbed slab, use spring-damper elements to simulate the action of the steel spring and the fastener, and use bending and shear springs to simulate the shear hinge; create a harmonic response analysis step, apply a steady-state swept-frequency excitation on the upper surface of the rail, fix the bottom of the steel spring, and modify the "Keywords" of the simulation model to extract the vibration isolation rate of the floating slab track. The established frequency-domain simulation model is as Figure 2 shown.

[0080] (2) Use ABAQUS software to establish a time-domain finite element model of the vehicle-floating slab track:

[0081] According to the geometric characteristics of the train, a rigid body element is used to establish the carbody model, bogie model and wheel set model; solid elements are used to establish the rail components and the ballast slab components, and the rail components and the ballast slab components are assembled according to the actual positional relationship; spring-damper elements are used to simulate the suspension system between the carbody and the bogie, and the suspension system between the bogie and the wheel set; the history output module is used to output the wheel-rail force, carbody acceleration, track structure acceleration, vertical displacement of the track structure and the reaction force of the steel spring.

[0082] Taking the 4.8m standard steel spring floating slab track as an example, a vehicle model is established on the basis of the existing steel spring floating slab model. The vehicle geometric model is based on the subway Type B car. The carbody, bogie and wheel set are all simulated by rigid bodies. The primary and secondary suspensions are both simulated by spring-damper elements. The longitudinal translation degree of freedom of the carbody is not considered. The total degree of freedom of the vehicle model is 35; spring-damper elements are used to simulate the suspension systems between the carbody and the bogie, and between the bogie and the wheel set. The history output module is used to output the results such as the wheel-rail force, carbody acceleration, track structure acceleration and track structure displacement. The established time-domain simulation model is as Figure 3 shown.

[0083] (3) Combine Python to write a time-frequency domain batch simulation program for the floating slab track structure. The writing steps include:

[0084] Obtain the format of the frequency-domain finite element model of the floating slab track structure and the vehicle-floating slab track time-domain finite element model as *.inp files; use Python programming means to modify the parameters to be optimized of the floating slab track in the *.inp file and reserve an interface for modifying the parameters to be optimized.

[0085] In the above step S3, it specifically includes:

[0086] Generate the values of the parameters to be optimized based on the constraint conditions and the experimental design method (random sequence method), and use the above interface for modifying the parameters to be optimized to input the values of the parameters to be optimized into the time-frequency domain batch simulation program. Carry out simulation analysis based on the simulation module in the ABAQUS software to obtain a simulation result file containing time-frequency domain response characteristics, including a result file with the format of *.dat and a result file with the format of *.odb.

[0087] In the above step S4, based on the optimization objective and the simulation result file, extract the output parameter values required for the parameter optimization model through a preset processing program; specifically include:

[0088] Use Python to read the result file with the format of *.dat corresponding to the frequency-domain finite element model of the floating slab track structure, and extract the lowest vibration isolation rate f in the low-frequency range of the floating slab track 1min and the highest vibration isolation rate f in the medium and high-frequency ranges2max ;

[0089] Use Python to read the result file with the format of *.odb corresponding to the vehicle-floating slab track time-domain finite element model, and extract the results of wheel-rail forces, carbody acceleration, vertical displacement of the track structure, acceleration of the track structure, and reaction force of the steel spring; specifically, extract the time history curves of the vertical wheel-rail force P and the lateral wheel-rail force Q, and calculate the peak values of the derailment coefficient T1 and the wheel load reduction rate T2 based on this, and at the same time extract the carbody acceleration a c , the vertical displacement y of the track structure g and the vertical displacement y of the track slab b , the acceleration a of the track structure g and the vertical acceleration a of the track slab b as well as the peak value of the reaction force F of the steel spring;

[0090] In the above step S5, input the output parameter values of the floating slab track into the parameter optimization model to output the parameter optimization results of the floating slab track;

[0091] This step can be carried out on the modeFRONTIER platform. Specifically, input the parameter optimization model established in the above step S1 into the modeFRONTIER platform to build a co-simulation model;

[0092] The specific steps for building the co-simulation model include: based on the modeFRONTIER platform, set the input parameter nodes, output parameter nodes, constraint condition nodes, and optimization target nodes according to the established mathematical model; build the experimental design and optimization algorithm modules based on the selected random sequence method and NSGA-II genetic algorithm; define the ABAQUS simulation module node to call the established time-frequency domain batch simulation model and data processing program, and define the input parameter reading node and parameter modification node to modify the input parameter variables of the batch simulation program. The logical relationship diagram of each node finally formed can be seen in Figure 4 .

[0093] After building the co-simulation model, input the output parameter values of the floating slab track obtained in the above step S4 into this co-simulation model.

[0094] This step S5 also includes: evaluating whether the current parameter optimization results of the floating slab track converge; if not, repeat steps S3 - S5; if converged, output the current parameter optimization results of the floating slab track. Specifically, judge the feasibility of the optimization parameters and whether the optimization converges according to the calculation results, the preset target values, and the genetic algorithm. If it converges, output the corresponding optimization parameters. If it does not converge, repeat the iterative process. The variation law of the input and output parameters with the increase of the number of iterations can be seen in Figure 5 , Figure 5(a) - (d) show the variation rules of input parameter values (including fastener stiffness, steel spring stiffness, fastener damping, and steel spring damping) with the number of iterations. Figure 5 (e) - (f) show the variation rules of output parameter values (including the combined value of vibration isolation rate and the peak value of steel spring reaction force) with the number of iterations; finally, the Pareto optimal solution of the optimized parameters of the floating slab track is obtained as follows: the fastener stiffness is 20 kN / mm, the steel spring stiffness is 6 kN / mm, the fastener damping is 0.015 kN·s / mm -1 , and the steel spring damping is 0.04 kN·s / mm -1 .

[0095] In this specification, each embodiment is described in a progressive manner. The key point of each embodiment is to illustrate the differences from other embodiments. For the same or similar parts among the embodiments, reference can be made to each other.

[0096] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for optimizing parameters of a floating plate track, characterized in that: The steps include: S1. Determine the parameters to be optimized of the floating plate track structure, clarify the constraints and optimization objectives of the floating plate track structure; establish a parameter optimization model of the floating plate track structure in combination with the parameters to be optimized, the constraints and the optimization objectives; determine the experimental design method and parameter optimization algorithm; S2. Use ABAQUS software to establish a frequency domain finite element model of the floating slab track structure and a time domain finite element model of the vehicle-floating slab track, and use Python to write a batch simulation program for the floating slab track structure in the time and frequency domain; S3, generating parameter values ​​to be optimized based on the constraint conditions and the experimental design method, inputting the parameter values ​​to be optimized into the time-frequency domain batch simulation program and performing simulation analysis to obtain a simulation result file containing time-frequency domain response characteristics; S4, based on the optimization target and the simulation result file, extracting the output parameter values ​​required by the parameter optimization model through a preset processing program; S5. Based on the modeFRONTIER platform, the output parameter value is input into the parameter optimization model, the parameter to be optimized is optimized according to the optimization target and the parameter optimization algorithm, and the floating plate track parameter optimization result is output.

2. A method for optimizing parameters of a floating plate track according to claim 1, characterized in that: Parameters that need to be optimized are selected from the floating slab track geometric parameters, fastener parameters and isolator parameters as the parameters to be optimized.

3. A method for optimizing parameters of a floating plate track according to claim 1, characterized in that: The safety index of the floating slab track is not exceeded as a constraint condition; The safety index includes vehicle safety index and track safety index; The vehicle safety indicators include: vehicle acceleration, derailment coefficient and wheel load reduction rate; The track safety indicators include: track structure displacement and track structure acceleration.

4. A method for optimizing parameters of a floating plate track according to claim 1, characterized in that: The optimal vibration reduction performance of the floating slab track is taken as the optimization target, and the vibration isolation rate of the floating slab track and the reaction force of the steel spring support are selected as the vibration reduction performance indicators of the floating slab track.

5. The method for optimizing parameters of a floating plate track according to claim 1, characterized in that: The steps of establishing the frequency domain finite element model of the floating slab track structure include: According to the geometric characteristics of the floating slab track, the rail components and the ballast plate components are established in ABAQUS software; Assemble the rail components and the ballast plate components according to the actual positional relationship, and use spring-damper units to simulate the fastener model; Create a harmonic response analysis step to apply a steady-state swept frequency excitation on the upper surface of the rail component. The keywords of the frequency domain finite element model of the floating slab track structure are modified to extract the vibration isolation rate of the floating slab track.

6. A method for optimizing parameters of a floating plate track according to claim 1, characterized in that: The steps of establishing the vehicle-floating plate track time domain finite element model include: According to the geometric characteristics of the train, the car body model, bogie model and wheelset model are established using rigid body units; Use entity elements to establish rail components and roadbed plate components, and assemble the rail components and roadbed plate components according to the actual position relationship; Spring-damper units are used to simulate the suspension system between the car body and the bogie, and the suspension system between the bogie and the wheelset; The process output module is used to output the wheel-rail force, vehicle body acceleration, track structure acceleration, track structure vertical displacement and steel spring support reaction force.

7. A method for optimizing parameters of a floating plate track according to claim 1, characterized in that: The steps of writing the time-frequency domain batch simulation program include: The corresponding formats of the floating slab track structure frequency domain finite element model and the vehicle-floating slab track time domain finite element model are obtained as *.inp files; The parameters to be optimized of the floating plate track in the *.inp file are modified by Python programming, and an interface for modifying the parameters to be optimized is reserved.

8. A method for optimizing parameters of a floating plate track according to claim 7, characterized in that: The inputting of the parameter value to be optimized into the time-frequency domain batch simulation program and carrying out simulation analysis specifically includes: The interface for modifying the parameters to be optimized is used to input the parameter values ​​to be optimized into the time-frequency domain batch simulation program, and simulation analysis is carried out based on the simulation module in the ABAQUS software.

9. A method for optimizing parameters of a floating plate track according to claim 1, characterized in that: The step S4 specifically includes: Use Python to read the result file in *.dat format corresponding to the frequency domain finite element model of the floating slab track structure, and extract the lowest vibration isolation rate in the low-frequency range and the highest vibration isolation rate in the medium- and high-frequency range of the floating slab track; Python is used to read the result file in *.odb format corresponding to the vehicle-floating slab track time-domain finite element model, and the results of wheel-rail force, vehicle body acceleration, track structure vertical displacement, track structure acceleration and steel spring support reaction force are extracted.

10. The method for optimizing parameters of a floating plate track according to claim 1, characterized in that: In the step S5, it also includes: Evaluate whether the current floating slab track parameter optimization results have converged; If it does not converge, repeat steps S3-S5; If converged, the current floating plate track parameter optimization results are output.

Images