Urban rail transit rail structure disease simulation test platform

Abstract

The invention discloses an urban rail transit rail structure disease simulation test platform. The platform comprises a modular rail structure, a disease simulation execution mechanism, a dynamic loading system and an intelligent control system. The modularized track structure comprises a steel spring floating slab module, a high-grade vibration reduction ballast bed module and a monolithic ballast bed module. The disease simulation execution mechanism is arranged on the modular track structure and is used for simulating different disease modes; the dynamic loading system comprises a wheel rail excitation simulation device used for loading wheel rail excitation parameters; the intelligent control system comprises an integrated sensor network, a central controller and a man-machine interaction terminal, and the intelligent control system is electrically connected with the disease simulation execution mechanism and the dynamic loading system and used for controlling the disease simulation execution mechanism and the dynamic loading system so as to achieve track structure disease simulation prediction.

Description

Technical Field

[0001] The present invention relates to the field of rail transit technology, and more particularly to a platform and method for simulating and testing rail structure defects in urban rail transit. Background Art

[0002] Modern rail transit systems face complex operating environments (such as high-frequency vibration and heavy-load impact), resulting in a trend of diversified and coupled track structural defects, seriously impacting operational safety. Existing research has yet to conduct comprehensive experimental studies on multiple track structural defects. Single-defect tests cannot replicate the multi-factor interactions found in real-world scenarios. For example, existing track testing equipment suffers from limited defect simulation capabilities, uncontrollable parameters, and a lack of intelligent intelligence.

[0003] Therefore, there is an urgent need to build a high-fidelity simulation platform to quantify the impact of disease evolution on track mechanical performance and provide multi-source heterogeneous data training sets for intelligent monitoring systems. Summary of the Invention

[0004] The present invention aims to address the above-mentioned deficiencies in the prior art and to provide a test simulation platform for urban rail transit track structure defects. Through the collaborative innovation of modular track structure, defect simulation actuators, intelligent control systems and dynamic loading systems, the present invention aims to solve difficult problems such as the complex test defect simulation process and uncontrollable parameters.

[0005] According to one aspect of the present invention, there is provided an urban rail transit track structure defect simulation test platform, comprising a modular track structure, a defect simulation actuator, a dynamic loading system, and an intelligent control system;

[0006] The modular track structure includes a steel spring floating plate module, an advanced vibration damping track bed module and an integral track bed module;

[0007] The disease simulation execution mechanism is arranged on the modular track structure and is used to simulate different disease modes;

[0008] The dynamic loading system includes a wheel-rail excitation simulation device for loading wheel-rail excitation parameters;

[0009] The intelligent control system includes an integrated sensor network, a central controller and a human-computer interaction terminal, wherein the intelligent control system is electrically connected to the disease simulation actuator and the dynamic loading system, and is used to control the disease simulation actuator and the dynamic loading system to realize track structure disease simulation prediction.

[0010] According to an embodiment of the present invention, the modular track structure further comprises an extended transition section, wherein the extended transition section comprises an adjustable rail support for boundary condition simulation.

[0011] According to an embodiment of the present invention, the wheel-rail excitation parameters include axle weight, vehicle speed, and vibration spectrum type.

[0012] According to an embodiment of the present invention, the disease simulation actuator arrangement includes a fastener loosening device, a rail breakage adjuster, a shear hinge failure controller, a vibration damping pad de-airing lifting platform, and a steel spring stiffness degradation device.

[0013] According to an embodiment of the present invention, the integrated sensor network includes a distributed vibration strain sensing composite optical fiber, an acoustic emission probe, a point vibration sensor and a crack monitoring unit, which are respectively used to collect and feed back detection parameter data in real time.

[0014] According to an embodiment of the present invention, the central controller is used for real-time data processing, running the digital twin engine, and realizing track status prediction by fusing the finite element model with the measured data.

[0015] According to an embodiment of the present invention, the human-computer interaction terminal is used to provide a visual programming interface, support autonomous configuration of disease scenarios, and generate three-dimensional mechanical cloud maps and spectrum waterfall diagrams.

[0016] According to another aspect of the present invention, a method for simulating track structure defects using an urban rail transit track structure defect simulation test platform includes:

[0017] System initialization and self-test, including hardware pre-start and software loading;

[0018] The test parameters are configured through human-computer interaction, including selecting the simulated test disease mode, setting the loading conditions and data acquisition conditions;

[0019] Intelligent analysis and instruction issuance, including conversion of configuration parameters into disease simulation actuator control signals and dynamic loading parameter generation;

[0020] The disease simulation actuator and the wheel-rail excitation simulation device are started;

[0021] Real-time data closed-loop feedback: Sensor network data is collected in real time, processed by the central controller and input into the digital twin model to promptly update the virtual track status until the actual response deviates from the theoretical value by less than 10%; and

[0022] Adaptive optimization and result output include the central controller starting the algorithm, iteratively generating the worst-case working condition combination, and outputting key indicators and corresponding analysis processes and results.

[0023] According to an embodiment of the present invention, the method further includes resetting the system, including restoring the disease simulation actuator to an initial state and re-verifying the track geometry by the sensor network.

[0024] According to an embodiment of the present invention, the adaptive optimization includes the following steps: when conducting a multi-disease coupling experiment, the platform initiates a Q-learning algorithm, uses the maximum track damage degree as a reward function, and iteratively generates the worst-case working condition combination; the algorithm dynamically adjusts the action strategy based on historical test data to shorten the exploration time of extreme working conditions.

[0025] The urban rail transit track structure defect test simulation platform of the present invention quantifies abstract defects such as shear hinge failure and spring stiffness attenuation into actuator control parameters by constructing a defect knowledge base. It uses digital twin technology to drive the virtual track model through real-time sensor data to achieve bidirectional mapping between physical and digital space. It also optimizes the multi-disease coupled loading sequence based on a reinforcement learning algorithm to automatically generate the worst-case working condition combination.

[0026] The platform and method can reproducibly detect typical track defects such as loose fasteners, broken rails, loose steel springs, shear hinge failure, and debonding of vibration damping pads. It supports structural performance evaluation under multi-parameter coupling conditions and provides a high-confidence test environment for the verification of track condition monitoring algorithms and the optimization of maintenance decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 Schematic diagram of the structure of the urban rail transit track structure disease simulation test platform according to an embodiment of the present invention;

[0028] Figure 2 2. It is a flow chart of a method for simulating and testing defects in urban rail transit track structures according to an embodiment of the present invention;

[0029] Figure 3 Schematic diagram of a modular track structure of an urban rail transit track structure disease simulation test platform according to an embodiment of the present invention;

[0030] Figure 4 Schematic diagram of the structure of the loading system (steel spring floating plate module) and intelligent control system of the urban rail transit track structure disease simulation test platform according to the embodiment of the present invention;

[0031] Figure 5 A schematic side view of an advanced vibration-damping roadbed of an urban rail transit track structure defect simulation test platform according to an embodiment of the present invention; and

[0032] Figure 6 It is a schematic side view of the overall track bed of the urban rail transit track structure disease simulation test platform according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The present invention can be better understood with reference to the accompanying drawings and the following embodiments. However, it is easy for those skilled in the art to understand that the contents described in the embodiments are only used to illustrate the present invention, and should not and will not limit the present invention.

[0034] Figure 1 This is a schematic diagram of the structure of an urban rail transit track structure defect simulation test platform according to an embodiment of the present invention. As shown in the figure, the urban rail transit track structure defect simulation test platform includes four core modules: a modular track structure, a defect simulation actuator, a dynamic loading system, and an intelligent control system. The following details the structure of each module in conjunction with the accompanying figures.

[0035] The modular track structure of the test platform may include a steel spring floating plate (1), an advanced vibration-damping track bed (2), an integral track bed (3), and an extended transition section (not shown). In other words, the modular track structure of the embodiment may include different types of track bed structures, the number and arrangement of which may be set as needed, and the track bed structures are connected by rails.

[0036] Figure 3 The figure is a schematic diagram of the modular track structure of the urban rail transit track structure disease simulation test platform according to the embodiment of the present invention. The figure shows a modular track structure composed of two sections of steel spring floating plates, a section of integral roadbed and a section of high-vibration damping roadbed. Figure 4 、 5 6 show schematic cross-sectional structures of a steel spring floating plate, an advanced vibration-damping trackbed, and an integral trackbed, respectively. The specific structures of the steel spring floating plate, the advanced vibration-damping trackbed, and the integral trackbed are well known to those skilled in the art. For example, the steel spring floating plate module may include a long ballastless track (including fasteners), a concrete floating plate, a steel spring isolator, and a shear hinge; the integral trackbed module may include a long ballastless track (including fasteners) and a trackbed structure; and the advanced vibration-damping trackbed module may include a long ballastless track (including fasteners), longitudinal beams, vibration-damping pads, etc. The details are not repeated here. The extended transition section may include adjustable rail supports, which can be used for boundary condition simulation.

[0037] The disease simulation actuator is arranged on the modular track structure and is used to simulate different disease modes. The disease simulation actuator can be composed of various disease device parts, for example, it can include a fastener loosening device (4), a rail breakage adjuster (5), a steel spring stiffness degradation device (6), a shear hinge failure controller (7) and a vibration damping pad de-airing lifting platform (8). The working principle and structure of each device are further described below. Ordinary technicians in this field can easily implement these devices by combining the description of the present invention and conventional technical knowledge in this field.

[0038] The fastener loosening device can be installed on steel spring floating slabs, high-vibration damping ballast, and monolithic ballast to simulate fastener loosening conditions. It may include an electromagnetic torque regulator and an insulating protective sleeve. The electromagnetic torque regulator, integrated into the fastener bolt, modifies the bolt preload through an alternating magnetic field generated by an electromagnetic coil. The insulating protective sleeve utilizes a high-temperature ceramic coating to prevent electromagnetic interference from affecting other sensors. The fastener preload adjustment range is 0-100% for the loosening rate, corresponding to the fastener's measuring range. The current is controlled by reducing the current under no-loosening conditions by the loosening rate. The rail break regulator can be installed at each rail joint / connection in a modular track structure to simulate rail breakage conditions. It may include a hydraulic wedge separation mechanism and a contoured cleat system. The hydraulically driven dual wedge mechanism consists of symmetrically arranged titanium alloy wedges driven by a servo-hydraulic cylinder. The contoured cleat system uses adaptive cleats with pressure sensors to maintain rail surface smoothness after crack formation. The crack width can be adjusted from 0 to 20 mm. The hydraulic cylinder lifts the wedge block at a constant speed of v = 0.2mm / min, while the contoured clamp dynamically adjusts the pressure to compensate for rail deformation. The steel spring stiffness degradation device can be installed on the steel spring floating plate to simulate the steel spring stiffness degradation condition. It can include a multi-stage hydraulic damping system and a replaceable spring group. The multi-stage hydraulic damping system consists of a main hydraulic cylinder, an accumulator and a proportional valve. The equivalent stiffness is changed by adjusting the oil pressure. The replaceable spring group is a series / parallel combination of disc springs. The preload is controlled by a servo motor and supports discrete stiffness graded adjustment. The shear hinge failure controller can be installed on the steel spring floating plate to simulate the shear hinge failure condition. It can include a multi-modal stiffness adjustment system composed of a hydraulic damper and a shape memory alloy spring in parallel, supporting multi-stage stiffness adjustment. The equivalent stiffness is adjusted by adjusting the hydraulic damper oil pressure and the shape memory alloy spring phase transition temperature. The vibration damping pad de-airing lifting platform can be installed on a high-grade vibration damping track bed to simulate the vibration damping pad de-airing condition (see attached). Figure 6 ), which may include a pneumatic array lifting system, a flexible contact interface, and a vacuum suction module. The pneumatic array lifting system consists of independently controlled airbag units arranged in a grid pattern; the flexible contact interface is a silicone contoured pad that conforms to the bottom contour of the vibration damping pad to ensure uniform pressure distribution; and the vacuum suction module is a negative pressure suction cup that allows for rapid repositioning of the vibration damping pad after testing.

[0039] The dynamic loading system is used to simulate various locomotive loads on the track structure. Such loading systems are well known in the art. More specifically, the dynamic loading system includes a wheel-rail excitation simulator for loading wheel-rail excitation parameters, such as axle load, vehicle speed, and vibration spectrum type. The wheel-rail excitation simulator can utilize an electro-hydraulic servo actuator with a maximum loading force of up to 200kN and a frequency range of 0.1-1000Hz. It can simulate the time-domain excitation spectrum of train axle loads (16-32t) and speeds (0-120km / h). Figure 3 and Figure 4 A schematic diagram of the wheel-rail excitation simulation device (12) is shown in FIG.

[0040] The intelligent control system is electrically connected to the disease simulation actuator and the dynamic loading system, and is used to control the disease simulation actuator and the dynamic loading system to achieve track structure disease simulation prediction. Figure 4 The figure shows a schematic diagram of the structure of an intelligent control system in an urban rail transit track structure defect simulation test platform according to an embodiment of the present invention. As shown in the figure, the intelligent control system may include an integrated sensor network (9), a central controller (10), and a human-computer interaction terminal (11).

[0041] The integrated sensor network can include distributed vibration and strain sensing composite optical fibers, acoustic emission probes, point vibration sensors, and crack monitoring units to collect track strain, vibration, and acoustic emission signals. The distributed strain sensing optical fibers can be pre-buried along the neutral axis of the track slab, while the acoustic emission probes and point vibration sensors can be embedded in the rail waist. The crack monitoring unit can be a high-frequency industrial camera combined with an image recognition algorithm to measure crack width in real time.

[0042] The central controller can be equipped with a dual-core processor, such as one based on a Field-Programmable Gate Array (FPGA) and Advanced RISC Machine (ARM) architecture, supporting multi-threaded real-time control and a response latency of less than 1ms. The FPGA module handles real-time data processing, while the ARM module runs the digital twin engine, enabling track state prediction by fusing finite element models with measured data. Using digital twin technology, the virtual track model is driven by real-time sensor data, enabling bidirectional mapping between physical and digital space. Digital twin technology is well known in the art and will not be discussed in detail here.

[0043] The human-computer interaction terminal can provide a visual programming interface, support autonomous configuration of disease scenarios, and generate three-dimensional mechanical cloud maps and spectrum waterfall diagrams.

[0044] Figure 2 This is a flow chart of a method for simulating damage to a track structure of urban rail transit according to an embodiment of the present invention. As shown in the figure, the method for simulating damage to a track structure of urban rail transit using the platform for simulating damage to a track structure of urban rail transit according to the embodiment of the present invention may include the following steps:

[0045] 1. System initialization and self-test, including hardware pre-start, calibration, and software loading. More specifically, when the power is turned on, the central controller automatically performs zero-point calibration on each disease simulation actuator to confirm that the electromagnetic torque regulator, hydraulic wedge block, pneumatic jacking unit, etc. are in the initial state. The sensor network starts self-diagnosis, verifies the signal stability of the distributed vibration strain composite optical fiber and acoustic emission probe, and triggers an alarm when the error exceeds the limit. Software loading includes loading the preset track model (including the finite element parameters of the steel spring floating plate, advanced vibration damping roadbed, and integral roadbed) into the digital twin module.

[0046] 2. Test parameter configuration. Select a fault mode through the human-computer interface or customize a combination of faults. For example: The steel spring floating plate module: fastener loosening, steel spring stiffness reduction, and shear hinge failure; the integrated trackbed module: rail cracks; the advanced vibration damping trackbed module: one or a combination of vibration damping pad de-airing. Loading condition configuration: Enter wheel-rail excitation parameters such as axle load, vehicle speed, and vibration spectrum type. Acquisition condition configuration: Set the sampling frequency and data collection requirements for each sensor network.

[0047] 3. Intelligent analysis and command issuance. Defect parameter quantification: The central controller converts abstract defects into actuator control signals. Dynamic loading parameter generation: The wheel-rail excitation device automatically generates equivalent vibration time history curves based on vehicle speed and axle load parameters.

[0048] 4.Multiple systems operate collaboratively.

[0049] The actuators are started in a preset sequence: in the first stage, the electromagnetic fastener regulator reduces the target fastener preload to the set value; in the second stage, the steel spring stiffness degradation device adjusts the stiffness to the set value; in the third stage, the shear hinge failure controller is adjusted to the set value at the same time; in the fourth stage, the hydraulic fracture regulator pushes the rail to the set value; in the fifth stage, the pneumatic lifting unit is synchronously lifted to the set value to form a void zone.

[0050] After the disease loading is completed, the wheel-rail excitation device applies the set equivalent vibration load.

[0051] 5. Real-time data closed-loop feedback. The sensor network collects track strain, vibration, and acoustic emission signals at a set sampling frequency. After filtering by the central controller's computational nodes, the data is fed into the digital twin model to update the virtual track state. If the actual response deviates from the theoretical value by more than 10%, the central controller automatically adjusts actuator parameters (e.g., reducing the loading amplitude or pausing the test).

[0052] 6. Adaptive Optimization and Result Output. Reinforcement Learning Condition Optimization: When conducting multi-disease coupled experiments, the platform activates a Q-learning algorithm, using "maximum track damage" as a reward function to iteratively generate the optimal operating condition combination. The algorithm dynamically adjusts its action strategy based on historical test data, shortening the time required to explore extreme conditions. Test Report Generation: The system automatically outputs key indicators, including the disease evolution rate, peak track dynamic response, and monitoring algorithm false alarm rate. The digital twin model provides a three-dimensional damage cloud map and time-frequency analysis graphs.

[0053] 7. System reset. Post-test reset: The central controller sends a reverse command to restore the actuator to its initial state; the sensor network rechecks the track geometry to ensure there is no residual deformation.

[0054] The present invention will be further described below by taking the simulation of composite diseases of a floating slab and the simulation of composite diseases of an integral roadbed and a steel spring floating slab as examples.

[0055] Example 1: Simulation of composite diseases of floating slabs

[0056] Test parameter configuration: Select "Steel Spring Floating Plate Module - Steel Spring Stiffness Attenuation 30% - Fastener Loosening 50% - Shear Hinge Failure 40%" through the human-computer interface. Enter the wheel-rail excitation parameters: axle load of 25 tons, vehicle speed of 80 km / h, random vibration spectrum type, frequency range of 1-1000 Hz. Set the sampling condition to 2000 Hz and save all data. Select "No" for adaptive optimization.

[0057] After the command is issued, each actuator starts in a preset order. After the defect loading is completed, the wheel-rail excitation device applies the set equivalent vibration load, and the sensor network begins to collect and feedback data in real time.

[0058] Example 2: Simulation of composite damage of integral track bed and steel spring floating slab

[0059] Test parameter configuration: Select "Integrated trackbed - 30% fastener loosening; Steel spring floating plate module - 20% spring stiffness reduction - 30% fastener loosening" through the human-computer interface. Enter the wheel-rail excitation parameters: axle load of 30 t, vehicle speed of 60 km / h, random vibration spectrum type, frequency range of 1-1000 Hz. Set the sampling condition to 2000 Hz and save all data. Enable adaptive optimization: Yes.

[0060] After the command is issued, each actuator starts in a preset order. After the defect loading is completed, the wheel-rail excitation device applies the set equivalent vibration load, and the sensor network begins to collect and feedback data in real time.

[0061] The above exemplary embodiments of the present invention are described, but the present invention is not limited to the embodiments described above. The basic concept of the present invention lies in the above basic scheme. For those skilled in the art, it does not require creative effort to design various modified models, formulas, and parameters based on the teachings of the present invention. Changes, modifications, substitutions, and variations of the embodiments without departing from the principles and spirit of the present invention remain within the scope of protection of the present invention.

Claims

1. An urban rail transit track structure disease simulation test platform, characterized in that: include: Modular track structure, disease simulation actuator, dynamic loading system and intelligent control system; The modular track structure includes a steel spring floating plate module, an advanced vibration damping track bed module and an integral track bed module; The disease simulation execution mechanism is arranged on the modular track structure and is used to simulate different disease modes; The dynamic loading system includes a wheel-rail excitation simulation device for loading wheel-rail excitation parameters; The intelligent control system includes an integrated sensor network, a central controller and a human-computer interaction terminal, wherein the intelligent control system is electrically connected to the disease simulation actuator and the dynamic loading system, and is used to control the disease simulation actuator and the dynamic loading system to realize track structure disease simulation prediction.

2. The urban rail transit track structure disease simulation test platform according to claim 1 is characterized in that: The modular track structure further includes an extended transition section, wherein the extended transition section includes an adjustable rail support for boundary condition simulation.

3. The urban rail transit track structure disease simulation test platform according to claim 1 is characterized in that: The wheel-rail excitation parameters include axle weight, vehicle speed, and vibration spectrum type.

4. The urban rail transit track structure disease simulation test platform according to claim 1 is characterized in that: The disease simulation actuator arrangement includes a fastener loosening device, a rail fracture adjuster, a shear hinge failure controller, a vibration damping pad de-airing lifting platform, and a steel spring stiffness degradation device.

5. The urban rail transit track structure disease simulation test platform according to claim 1 is characterized in that: The integrated sensor network includes a distributed vibration strain sensing composite optical fiber, an acoustic emission probe, a point vibration sensor and a crack monitoring unit, which are respectively used to collect and feed back detection parameter data in real time.

6. The urban rail transit track structure disease simulation test platform according to claim 1 is characterized in that: The central controller is used for real-time data processing and running the digital twin engine, and realizes track status prediction by fusing the finite element model with measured data.

7. The urban rail transit track structure disease simulation test platform according to claim 1 is characterized in that: The human-computer interaction terminal is used to provide a visual programming interface, support autonomous configuration of disease scenarios, and generate three-dimensional mechanical cloud maps and spectrum waterfall diagrams.

8. A method for simulating track structure defects using the urban rail transit track structure defect simulation test platform according to any one of claims 1 to 7, characterized in that: include: System initialization and self-test, including hardware pre-boot, calibration, and software loading; The test parameters are configured through human-computer interaction, including selecting the simulated test disease mode, setting the loading conditions and data acquisition conditions; Intelligent analysis and instruction issuance, including conversion of configuration parameters into disease simulation actuator control signals and dynamic loading parameter generation; The disease simulation actuator and the wheel-rail excitation simulation device are started; Real-time data closed-loop feedback: Sensor network data is collected in real time, processed by the central controller and input into the digital twin model to promptly update the virtual track status until the actual response deviates from the theoretical value by less than 10%; as well as Adaptive optimization and result output include the central controller starting the algorithm, iteratively generating the worst-case working condition combination, and outputting key indicators and corresponding analysis processes and results.

9. The method according to claim 8, characterized in that It also includes system reset, including restoration of the disease simulation actuator to its initial state and secondary verification of the track geometry by the sensor network.

10. The method according to claim 8, characterized in that Adaptive optimization includes the platform launching the Q-learning algorithm when conducting multi-disease coupling experiments, using the maximum track damage degree as the reward function, and iteratively generating the worst working condition combination; the algorithm dynamically adjusts the action strategy based on historical test data to shorten the exploration time of extreme working conditions.

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