Train coupler force monitoring method, system, terminal and storage medium

Abstract

The present application provides a train coupler force monitoring method, system, terminal and storage medium, which relates to the field of rail transit systems, and in particular to a train coupler force monitoring method, comprising: obtaining a pre-established train digital twin virtual simulation model; using the train digital twin virtual simulation model to simulate and generate working condition data samples; establishing a coupler force virtual sensor model based on the working condition data samples; obtaining vehicle-side acceleration time history data; and performing online monitoring of coupler force during train operation based on the vehicle-side acceleration time history data, the coupler force virtual sensor model and the train digital twin virtual simulation model. The present application can achieve long-term and safe monitoring of the stress status of running train couplers.

Description

Technical Field

[0001] The present application relates to the field of rail transit systems, and in particular to a method, system, terminal and storage medium for monitoring the force on train couplers. Background Art

[0002] Long trains, the mainstay of bulk freight and heavy-load transport, are typically operated with twin or multiple locomotives. The stress on the couplers between locomotives and freight cars, and between freight cars, is a crucial factor in determining train safety. Factors such as the track's longitudinal slope, tight curves, and traction and braking control can significantly impact the structural safety of the couplers.

[0003] Existing coupler force monitoring is mainly carried out through physical sensors based on strain or force sensors. Monitoring methods based on physical sensors such as strain or force sensors are very prone to damage during long-term operation and are not suitable for long-term safety monitoring.

[0004] Therefore, how to achieve long-term and safe monitoring of the stress status of the couplers of running trains is a technical problem that needs to be solved urgently by those skilled in the art. Summary of the Invention

[0005] To solve the above technical problems, the present application provides a train coupler force monitoring method that can achieve long-term and safe monitoring of the force status of running train couplers. The present application also provides a train coupler force monitoring system, terminal and storage medium, which have the same technical effects.

[0006] The first purpose of this application is to provide a method for monitoring the force on train couplers.

[0007] The above-mentioned application objective 1 of this application is achieved through the following technical solutions:

[0008] A train coupler force monitoring method, comprising:

[0009] Obtain a pre-established train digital twin virtual simulation model;

[0010] Using the digital twin virtual simulation model of the train, simulate and generate working condition data samples;

[0011] Establishing a coupler force virtual sensor model based on the working condition data sample;

[0012] Obtain vehicle-side acceleration time history data;

[0013] Based on the vehicle-end acceleration time history data, the coupler force virtual sensor model and the train digital twin virtual simulation model, online monitoring of the coupler force is performed during train operation.

[0014] Preferably, the train coupler force monitoring method further includes establishing a digital twin virtual simulation model of the train, and establishing the digital twin virtual simulation model of the train includes:

[0015] Establish a train multi-body dynamics model based on train design and marshaling scheme;

[0016] Establish a simulation model of the train traction drive control subsystem;

[0017] Establish a simulation model of the train braking and anti-skid control subsystem;

[0018] Based on the train multi-body dynamics model, the train traction drive control subsystem simulation model and the train braking and anti-skid control subsystem simulation model, a multidisciplinary joint simulation digital twin virtual body simulation model of the train is constructed.

[0019] Preferably, in the train coupler force monitoring method, the step of using the train digital twin virtual simulation model to simulate and generate working condition data samples comprises:

[0020] By using the digital twin virtual simulation model of the train, combined simulation conditions of vertical curves with different slopes, different ramp lengths, plane curves with different radii, and different traction control parameters are selected to carry out electromechanical coupling simulation calculations of train operation and generate operating condition data samples.

[0021] Preferably, in the train coupler force monitoring method, establishing a coupler force virtual sensor model based on the working condition data sample includes:

[0022] Extracting vehicle-end vibration acceleration data samples and coupler force time history data samples of each working condition according to the working condition data samples;

[0023] Based on the vehicle-end vibration acceleration data samples and the coupler force time history data samples, a machine learning algorithm is used to construct a nonlinear mapping relationship between the vehicle-end vibration acceleration data and the coupler force, and a data-based coupler force virtual sensor model is obtained.

[0024] Preferably, in the train coupler force monitoring method, the online monitoring of the coupler force during train operation based on the vehicle-end acceleration time history data, the coupler force virtual sensor model and the train digital twin virtual simulation model includes:

[0025] According to the vehicle-end acceleration time history data, the real-time coupler force time history data is calculated by the coupler force virtual sensor model;

[0026] The train digital twin virtual simulation model is used to perform extreme value statistical analysis on the real-time coupler force time history data, and monitor data anomalies in real time.

[0027] Preferably, in the train coupler force monitoring method, the train digital twin virtual simulation model includes filtering algorithm, transfer learning, artificial neural network, random forest, support vector machine, convolutional neural network and deep learning model.

[0028] The second purpose of this application is to provide a train coupler force monitoring system.

[0029] The second object of the present application is achieved through the following technical solutions:

[0030] A train coupler force monitoring system comprising:

[0031] The first acquisition module is used to obtain a pre-established train digital twin virtual simulation model;

[0032] A simulation module, configured to generate operating condition data samples by simulating the train digital twin virtual simulation model;

[0033] A construction module, used for establishing a coupler force virtual sensor model based on the working condition data sample;

[0034] The second acquisition module is used to obtain vehicle-side acceleration time history data;

[0035] The monitoring module is used to perform online monitoring of the coupler force during train operation based on the vehicle-end acceleration time-history data, the coupler force virtual sensor model and the train digital twin virtual simulation model.

[0036] Preferably, the train coupler force monitoring system further includes an establishment module for establishing the digital twin virtual simulation model of the train, and the establishment module includes:

[0037] First, a sub-model is established to establish a train multi-body dynamics model based on the train design and formation plan;

[0038] Second, a sub-model is established to establish a simulation model of the train traction drive control subsystem;

[0039] Third, a sub-model is established to establish a simulation model of the train braking and anti-skid control subsystem;

[0040] The fourth sub-module is used to construct a digital twin virtual simulation model of the train for multidisciplinary joint simulation based on the train multi-body dynamics model, the train traction drive control subsystem simulation model and the train braking and anti-skid control subsystem simulation model.

[0041] The third object of this application is to provide a train coupler force monitoring terminal.

[0042] The third object of the present application is achieved through the following technical solutions:

[0043] A train coupler force monitoring terminal includes: a storage medium and a processor;

[0044] The storage medium stores computer-executable instructions;

[0045] The processor executes the computer-executable instructions stored in the storage medium to implement any of the above-mentioned train coupler force monitoring methods.

[0046] The fourth object of this application is to provide a computer-readable storage medium.

[0047] The fourth object of the present application is achieved through the following technical solutions:

[0048] A computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement any of the above-mentioned train coupler force monitoring methods.

[0049] This technical solution utilizes digital twin technology, a fusion of virtual and real, to achieve online monitoring of coupler forces during train operation by acquiring a pre-established digital twin virtual simulation model of the train, establishing a virtual sensor model of coupler forces, and combining this with vehicle-side acceleration time-history data. Compared to existing technical solutions, this solution, by establishing a virtual sensor model of coupler forces, avoids the vulnerability of force measurement using physical sensors such as strain or force sensors, which are prone to damage. Furthermore, the vehicle-side acceleration time-history data can be obtained solely through accelerometers located on the vehicle side. Accelerometers are more durable than physical sensors such as strain or force sensors, significantly improving the reliability of the onboard train coupler force monitoring system.

[0050] Furthermore, the aforementioned technical solution utilizes virtual sensor measurements, avoiding the inconvenience of deploying strain sensors at the train-side connection and the tedious calibration of coupler force measurements. By indirectly measuring coupler force using train-side accelerometers, it improves the reuse of accelerometer data and the integration of equipment, indirectly reducing costs. This technical solution utilizes digital twin technology to monitor coupler forces, facilitating the monitoring and management of coupler force data across the entire train. This can be further combined with data analysis and fault warnings to achieve intelligent management of train operation safety.

[0051] In summary, the above technical solution can realize long-term and safe monitoring of the stress status of the couplers of running trains. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0053] Figure 1 A flow chart of a train coupler force monitoring method provided in an embodiment of the present application;

[0054] Figure 2 Schematic diagram of the process of establishing a digital twin virtual simulation model of a train in an embodiment of the present application;

[0055] Figure 3 This is a structural diagram of a train digital twin virtual simulation model in an embodiment of the present application;

[0056] Figure 4 This is a schematic diagram of the architecture of the train digital twin software system in the embodiment of this application;

[0057] Figure 5 This is a virtual sensor model training diagram in the embodiment of this application;

[0058] Figure 6 This is a virtual sensor model verification diagram in the embodiment of this application;

[0059] Figure 7 This is a structural diagram of a train coupler force monitoring system provided in an embodiment of the present application;

[0060] Figure 8 This is a structural schematic diagram of a train coupler force monitoring terminal provided in an embodiment of the present application. DETAILED DESCRIPTION

[0061] In order to help those skilled in the art better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of this application.

[0062] In the embodiments provided in this application, it should be understood that the disclosed methods and systems can be implemented in other ways. The system embodiments described below are merely illustrative. For example, the division of modules is merely a logical function division. In actual implementation, there may be other division methods, such as: multiple modules or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0063] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. Throughout the description of this application, "plurality" or "several" means two or more, unless otherwise specifically defined.

[0064] The embodiments of the present application are written in a progressive manner.

[0065] like Figure 1 As shown, an embodiment of the present application provides a method for monitoring the force of a train coupler, comprising:

[0066] S101. Obtain a pre-established train digital twin virtual simulation model;

[0067] In S101, the train's digital twin virtual simulation model is implemented using digital twin technology. Digital twin technology leverages data from physical models, sensor updates, and operational history to integrate multidisciplinary, multi-physics, multi-scale, and multi-probability simulation processes. This technology then maps the model in virtual space, reflecting the entire lifecycle of the corresponding physical equipment. The digital twin simulation model can acquire data from the physical entity in real time through sensors and evolves with the entity in real time, ensuring consistency with the physical object throughout its lifecycle. In this embodiment, the digital twin virtual simulation model of the train can be used to analyze, predict, diagnose or monitor the stress state of the train coupler, so as to optimize the train coupler and make operation and maintenance decisions; specifically, the digital twin virtual simulation model of the train can be established based on multi-domain mechanisms (vehicle dynamics, traction drive, electromagnetic, braking, pneumatics, train structure, etc.) and multi-source heterogeneous data fusion; preferably, the digital twin virtual simulation model of the train includes filtering algorithms, transfer learning, artificial neural networks (ANN), random forests, support vector machines (SVM), convolutional neural networks (CNN) and deep learning (DL) models.

[0068] S102. Using the train digital twin virtual simulation model, simulate and generate working condition data samples;

[0069] In S102, specific simulation conditions can be determined based on actual production needs, and then the train digital twin virtual simulation model can be used to perform simulation calculations to obtain operating condition data samples. Preferably, the train digital twin virtual simulation model can be used to select simulation conditions combining vertical curves with different slopes, ramp lengths, planar curves with different radii, and traction control parameters to perform electromechanical coupling simulation calculations of train operation and generate operating condition data samples. By setting the above-mentioned combined simulation conditions, the validity of the operating condition data samples can be improved, thereby improving the accuracy of the subsequent virtual sensor model establishment.

[0070] S103. Establishing a coupler force virtual sensor model based on the working condition data sample;

[0071] In S103, specifically, a machine learning algorithm may be applied to establish a coupler force virtual sensor model, and the model may be trained, tested, and verified based on the working condition data samples.

[0072] S104. Obtain vehicle-side acceleration time history data;

[0073] In S104, the vehicle-side acceleration time history data can be obtained by an accelerometer deployed on the vehicle. Compared to physical sensors such as strain or force sensors, accelerometers are more durable. It should be noted that the execution order of S104, S101, S102, and S103 can be interchanged without affecting the implementation of this embodiment.

[0074] S105. Based on the vehicle-end acceleration time history data, the coupler force virtual sensor model and the train digital twin virtual simulation model, online monitoring of the coupler force during train operation is performed.

[0075] In S105, specifically, the vehicle-side acceleration time history data can be analyzed and processed through the coupler force virtual sensor model and the train digital twin virtual simulation model, and the vehicle-side acceleration time history data can be associated with the coupler force to achieve online monitoring of the coupler force during train operation. Preferably, the S105 includes the following steps: based on the vehicle-side acceleration time history data, the real-time coupler force time history data is measured and obtained through the coupler force virtual sensor model; using the train digital twin virtual simulation model, the real-time coupler force time history data is subjected to extreme value statistical analysis to monitor data anomalies in real time. The above implementation steps, through extreme value statistical analysis, can achieve real-time data anomaly warning, which can improve the operation and maintenance efficiency of operation and maintenance management personnel.

[0076] At present, existing coupler force monitoring is mainly carried out through physical sensors based on strain or force sensors. Monitoring methods based on physical sensors such as strain or force sensors are very prone to damage during long-term operation and are not suitable for long-term safety monitoring.

[0077] In this embodiment, a digital twin technology that integrates virtual and real forces is employed. By acquiring a pre-established digital twin virtual simulation model of the train, establishing a virtual sensor model for coupler forces, and combining this with vehicle-side acceleration time-history data, online monitoring of coupler forces during train operation is achieved. Compared to existing solutions, this embodiment, by establishing a virtual sensor model for coupler forces, avoids the vulnerability of force measurement using physical sensors such as strain or force sensors, which are prone to damage. Furthermore, the vehicle-side acceleration time-history data can be acquired solely through vehicle-side acceleration sensors, which are more durable than physical sensors such as strain or force sensors, thereby significantly improving the reliability of the onboard train coupler force monitoring system.

[0078] Furthermore, the aforementioned embodiment utilizes virtual sensor measurements, avoiding the inconvenience of deploying strain sensors at the train-side connection and the tedious calibration of coupler force measurements. Indirect coupler force measurement using train-side accelerometers improves the reuse of accelerometer data and the integration of equipment, indirectly reducing costs. The aforementioned embodiment utilizes digital twin technology to monitor coupler forces, facilitating the monitoring and management of coupler force data globally within the train. This can be further combined with data analysis and fault warnings to achieve intelligent management of train operation safety.

[0079] In summary, the above embodiments can achieve long-term and safe monitoring of the stress status of the couplers of running trains.

[0080] like Figure 2 As shown, on the basis of the above embodiment, it also includes establishing the digital twin virtual simulation model of the train. One implementation method of establishing the digital twin virtual simulation model of the train may include the following steps:

[0081] S201. Establish a multi-body dynamics model of the train based on the train design and marshaling scheme;

[0082] S202. Establish a train traction drive control subsystem simulation model;

[0083] S203. Establish a train braking and anti-skid control subsystem simulation model;

[0084] In S201 to S203, the train design and marshaling scheme can be formulated based on actual production requirements and may include information about the train's physical structure. Specifically, based on the train design and marshaling scheme, a multi-body dynamics model of the train can be established using multi-body dynamics software. Simulation models of the train's traction drive control subsystem and the train's braking and anti-skid control subsystem can also be established using simulation software (e.g., Matlab / Simulink). It should be noted that the order in which these models are established is interchangeable and does not affect the implementation of this embodiment.

[0085] S204. Based on the train multi-body dynamics model, the train traction drive control subsystem simulation model and the train braking and anti-skid control subsystem simulation model, a multidisciplinary joint simulation digital twin virtual simulation model of the train is constructed.

[0086] In S204, specifically, a train dynamics module, a traction drive control module, and a braking and anti-skid control module can be established based on the train multi-body dynamics model, the train traction drive control subsystem simulation model, and the train braking and anti-skid control subsystem simulation model. The train digital twin virtual body simulation model is constructed through these three models. For a structural diagram, please refer to Figure 3; For the train digital twin software system architecture, please refer to Figure 4 Preferably, the digital twin virtual simulation model of the train mainly includes physical entities, digital twin virtual entities, twin data, service applications and connection interactions among various components.

[0087] On the basis of the above embodiment, one implementation method of establishing a coupler force virtual sensor model according to the working condition data sample may include the following steps:

[0088] S301. According to the working condition data samples, extract the vehicle-end vibration acceleration data samples and coupler force time history data samples of each working condition;

[0089] S302. Based on the vehicle-end vibration acceleration data samples and the coupler force time history data samples, a nonlinear mapping relationship between the vehicle-end vibration acceleration data and the coupler force is constructed using a machine learning algorithm to obtain a data-based coupler force virtual sensor model.

[0090] In S301 to S302, the establishment of a virtual sensor model for the coupler force between the two middle freight cars is used as an example: 240 sets of working condition vehicle-side vibration accelerations a1 and a2, as well as coupler force f time series samples are extracted, and the Long Short-Term Memory (LSTM) algorithm is used to construct a nonlinear mapping relationship between the vehicle-side vibration acceleration data a1, a2 and the coupler force f, as shown in the following example: Figure 5 As shown in Figure 2, a data-based coupler force virtual sensor model is established. At this time, the training of the virtual sensor model based on machine learning is completed, and then another 16 sets of data samples are used to verify the model, as shown in Figure 2. Figure 6 shown.

[0091] like Figure 7 As shown, in another embodiment of the present application, a train coupler force monitoring system is further provided, comprising:

[0092] The first acquisition module 10 is used to obtain a pre-established train digital twin virtual simulation model;

[0093] A simulation module 11 is used to simulate and generate working condition data samples using the train digital twin virtual simulation model;

[0094] A construction module 12 is used to establish a coupler force virtual sensor model based on the working condition data sample;

[0095] The second acquisition module 13 is used to obtain vehicle-side acceleration time history data;

[0096] The monitoring module 14 is used to perform online monitoring of the coupler force during train operation based on the vehicle-end acceleration time history data, the coupler force virtual sensor model and the train digital twin virtual simulation model.

[0097] On the basis of the above embodiment, the train coupler force monitoring system further includes an establishment module for establishing the digital twin virtual simulation model of the train, and the establishment module includes:

[0098] First, a sub-model is established to establish a train multi-body dynamics model based on the train design and formation plan;

[0099] Second, a sub-model is established to establish a simulation model of the train traction drive control subsystem;

[0100] Third, a sub-model is established to establish a simulation model of the train braking and anti-skid control subsystem;

[0101] The fourth sub-module is used to construct a digital twin virtual simulation model of the train for multidisciplinary joint simulation based on the train multi-body dynamics model, the train traction drive control subsystem simulation model and the train braking and anti-skid control subsystem simulation model.

[0102] As a preferred embodiment, the train coupler force monitoring system further includes a display module, and the display module is used to display the monitoring data of the online monitoring of the coupler force.

[0103] Among them, the display module can use a display screen to realize data visualization by displaying monitoring data in real time, which is conducive to improving the operation and maintenance efficiency of management personnel; the monitoring data can include the coupler force and coupler deflection angle of all workshops.

[0104] like Figure 8 As shown, in another embodiment of the present application, a train coupler force monitoring terminal is provided, comprising: a storage medium 15 and a processor 16;

[0105] The storage medium 15 stores computer-executable instructions;

[0106] The processor 16 executes the computer-executable instructions stored in the storage medium 15 to implement any of the above-mentioned train coupler force monitoring methods.

[0107] The processor 16 may include one or more processing cores. The processor 16 executes or runs instructions, programs, code sets, or instruction sets stored in the storage medium 15, accesses data stored in the storage medium 15, and performs the various functions and processes data of the present application. The processor 16 may be at least one of an application-specific integrated circuit, a digital signal processor, a digital signal processing device, a programmable logic device, a field programmable gate array, a central processing unit, a controller, a microcontroller, and a microprocessor. It is understood that for different devices, the electronic components used to implement the functions of the processor 16 may also be other.

[0108] The storage medium 15 may be used to store instructions, programs, codes, code sets, or instruction sets. The storage medium 15 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing any of the aforementioned train coupler force monitoring methods. The data storage area may store data involved in any of the aforementioned train coupler force monitoring methods.

[0109] In another embodiment of the present application, a computer-readable storage medium is further provided, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement any of the above-mentioned train coupler force monitoring methods.

[0110] The computer-readable storage medium may be any medium capable of storing program codes, such as a USB flash drive, a mobile hard disk, a read-only memory, a random access memory, or an optical disk.

[0111] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for monitoring the force on a train coupler, characterized in that: include: Obtain a pre-established train digital twin virtual simulation model; Using the digital twin virtual simulation model of the train, simulate and generate working condition data samples; Establishing a coupler force virtual sensor model based on the working condition data sample; Obtain vehicle-side acceleration time history data; Based on the vehicle-end acceleration time history data, the coupler force virtual sensor model and the train digital twin virtual simulation model, online monitoring of the coupler force during train operation is performed; Wherein, establishing a coupler force virtual sensor model according to the working condition data sample includes: Extracting vehicle-end vibration acceleration data samples and coupler force time history data samples of each working condition according to the working condition data samples; Based on the vehicle-end vibration acceleration data samples and the coupler force time history data samples, a machine learning algorithm is used to construct a nonlinear mapping relationship between the vehicle-end vibration acceleration data and the coupler force, and a data-based coupler force virtual sensor model is obtained.

2. The method according to claim 1, wherein The method further includes establishing a digital twin virtual simulation model of the train, wherein establishing the digital twin virtual simulation model of the train includes: Establish a train multi-body dynamics model based on train design and marshaling scheme; Establish a simulation model of the train traction drive control subsystem; Establish a simulation model of the train braking and anti-skid control subsystem; Based on the train multi-body dynamics model, the train traction drive control subsystem simulation model and the train braking and anti-skid control subsystem simulation model, a multidisciplinary joint simulation digital twin virtual body simulation model of the train is constructed.

3. The method according to claim 1, wherein The method of using the train digital twin virtual simulation model to simulate and generate working condition data samples includes: By using the digital twin virtual simulation model of the train, combined simulation conditions of vertical curves with different slopes, different ramp lengths, plane curves with different radii, and different traction control parameters are selected to carry out electromechanical coupling simulation calculations of train operation and generate operating condition data samples.

4. The method according to claim 1, wherein The online monitoring of the coupler force during train operation based on the vehicle-end acceleration time history data, the coupler force virtual sensor model, and the train digital twin virtual simulation model includes: According to the vehicle-end acceleration time history data, the real-time coupler force time history data is calculated by the coupler force virtual sensor model; The train digital twin virtual simulation model is used to perform extreme value statistical analysis on the real-time coupler force time history data, and monitor data anomalies in real time.

5. The method according to claim 1, wherein The train digital twin virtual simulation model includes filtering algorithms, transfer learning, artificial neural networks, random forests, support vector machines, convolutional neural networks and deep learning models.

6. A train coupler force monitoring system, applied to the train coupler force monitoring method according to claim 1, characterized in that: include: The first acquisition module is used to obtain a pre-established train digital twin virtual simulation model; A simulation module, configured to generate operating condition data samples by simulating the train digital twin virtual simulation model; A construction module, used for establishing a coupler force virtual sensor model based on the working condition data sample; The second acquisition module is used to obtain vehicle-side acceleration time history data; The monitoring module is used to perform online monitoring of the coupler force during train operation based on the vehicle-end acceleration time-history data, the coupler force virtual sensor model and the train digital twin virtual simulation model.

7. The system according to claim 6, wherein: It also includes an establishment module for establishing the digital twin virtual simulation model of the train, and the establishment module includes: First, a sub-model is established to establish a train multi-body dynamics model based on the train design and formation plan; Second, a sub-model is established to establish a simulation model of the train traction drive control subsystem; Third, a sub-model is established to establish a simulation model of the train braking and anti-skid control subsystem; The fourth sub-module is used to construct a digital twin virtual simulation model of the train for multidisciplinary joint simulation based on the train multi-body dynamics model, the train traction drive control subsystem simulation model and the train braking and anti-skid control subsystem simulation model.

8. A train coupler force monitoring terminal, characterized in that: include: storage media and processors; The storage medium stores computer-executable instructions; The processor executes the computer-executable instructions stored in the storage medium to implement the method according to any one of claims 1 to 5.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 5 when executed by a processor.

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