Virtual-real matching digital twin aircraft brake system combined with monitoring, diagnosis and control

Abstract

The application discloses a virtual-real matching digital twin airplane brake system combined with monitoring, diagnosis and control, comprising a digital twin controller, a virtual-real matching module, a sensor sensing module, a virtual-real data interaction module, an operation state monitoring module, a fault diagnosis module and a brake decision adjustment module, wherein: the virtual-real matching module is used for realizing the corresponding relationship between the physical brake system and the virtual twin brake system, and realizing the brake process data and action synchronization; the virtual-real data interaction module is used for updating the physical brake data, the virtual brake data and the database model; the operation state monitoring module is used for effective data judgment, brake data and data model consistency analysis and state determination; the fault diagnosis module is used for fault determination and fault source analysis; and the brake decision adjustment module is used for control strategy adjustment and intelligent control. The application combines the physical brake data and the virtual brake data to improve the feasibility and safety of the brake system.

Description

Technical Field

[0001] This invention relates to the field of digital twin aircraft braking, and more particularly to a virtual-real matching digital twin aircraft braking system that combines monitoring, diagnosis, and control. Background Technology

[0002] The number of accidents involving aircraft before takeoff and after landing exceeds that during the flight phase, placing higher demands on aircraft safety. As airborne equipment, the aircraft braking system plays a crucial role in landing. With the increasing demands of aviation operations across various industries, the braking environment faced by unconventional aircraft (UAVs / fighter jets / super-large transport aircraft) is becoming increasingly challenging. Therefore, higher technical requirements are being placed on the reliability, safety, and braking performance of braking systems.

[0003] Digital twin technology can describe physical systems using virtual models, simulating the data information of physical entities in virtual space, greatly simplifying data sourcing. In the field of automotive braking systems, relying on physical components for brake control testing and debugging is inefficient and costly; a braking system incorporating digital twins can effectively solve this problem. Compared to automotive braking, aircraft braking experiments are even more expensive and potentially more dangerous. Therefore, integrating digital twin technology to collect simulated datasets is essential in the field of aircraft braking systems. Currently, there is no publicly available technical information on aircraft braking systems incorporating digital twins. Furthermore, aircraft braking systems based on data-driven safety braking methods, limited by data sources, only have a single diagnostic function and cannot achieve monitoring of the braking system status or real-time adjustment of safety braking strategies. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a virtual-real matching digital twin aircraft braking system that combines monitoring, diagnosis, and control.

[0005] The objective of this invention is achieved through the following technical solution:

[0006] A first aspect of the present invention provides a virtual-real matching digital twin aircraft braking system integrating monitoring, diagnosis, and control, comprising a digital twin controller, a virtual-real matching module, a sensor perception module, a virtual-real data interaction module, an operational status monitoring module, a fault diagnosis module, and a braking decision adjustment module, wherein:

[0007] The virtual-real matching module is used to realize the correspondence between the physical braking system and the virtual twin braking system, and to realize the synchronization of braking process data and actions;

[0008] The sensor sensing module transmits the collected sensor signals to each functional module for corresponding data processing.

[0009] The virtual-real data interaction module is used to update physical braking data, virtual braking data, and the database model: a database model of the braking system is constructed based on physical braking data and virtual braking data, and the database model is iteratively updated with data from each physical braking process and virtual braking process.

[0010] The operation status monitoring module is used for valid data judgment, consistency analysis of braking data and data model, and status judgment. Specifically, it includes: using the database model in the virtual and real data interaction module to judge and analyze the sensor signal data collected during the physical braking process, monitoring the system status, and feeding back the monitoring data and judgment data to the virtual and real data interaction module.

[0011] The fault diagnosis module is used for fault determination and fault source analysis, specifically including: determining the cause of failure of the faulty component based on the status determined by the operation status monitoring module and combining the fault diagnosis algorithm, and feeding back the corresponding abnormal data and diagnostic data to the virtual and real data interaction module.

[0012] The braking decision adjustment module is used for control strategy adjustment and intelligent control, specifically including: real-time adjustment of braking control strategy decision and intelligent braking control based on data information from the operation status monitoring module and the fault diagnosis module;

[0013] The digital twin controller provides interfaces and data transfer between the modules.

[0014] Furthermore, the sensor sensing module collects signals from sensors including temperature sensors, torque sensors, wheel speed sensors, acceleration sensors, and wear sensors, specifically for collecting signals of the braking system temperature, brake disc wear, braking torque of the braking mechanism, aircraft wheel speed, and aircraft acceleration.

[0015] Furthermore, the digital twin controller is used for:

[0016] Establish connections between sensors and various functional modules, and receive and analyze signals collected by various sensors;

[0017] Establish a connection between the physical braking system and the virtual twin braking system, collect and learn physical braking data and virtual braking data, and build a database model;

[0018] It performs condition monitoring, fault diagnosis, braking decision-making, and calculation of intelligent control algorithms.

[0019] Furthermore, the digital twin controller is also used for:

[0020] Provides a real-time human-machine interface for the braking system and offers braking assistance.

[0021] Furthermore, the virtual-real matching module is constructed using digital twin technology to achieve a correspondence between the physical braking system and the virtual twin braking system, specifically including:

[0022] A matching degree analysis is performed on the dynamic parameters of the physical model of the physical braking system and the virtual model of the virtual twin braking system. If the model parameters are consistent, virtual association is performed; if the model parameters are inconsistent, the parameters of the virtual model are adjusted until the parameters are matched.

[0023] During the physical braking process, the virtual model synchronously simulates the braking action in the visualization interface, and performs a real-time consistency comparison and analysis between the characteristic parameters of the physical braking system and the dynamic parameters of the virtual model, realizing a one-to-one correspondence between virtual and real components and subsystems.

[0024] Furthermore, the virtual-real data interaction module specifically includes:

[0025] Virtual braking data is obtained through virtual simulation braking experiments, and physical braking data is obtained through actual braking experiments.

[0026] The physical braking data and the simulated braking data are interfacing, classified, and recombined to obtain virtual and real data.

[0027] Preprocessing is performed on both virtual and real data to smooth the data and identify outliers.

[0028] The preprocessed virtual and real data are fused to build a database model of the braking system.

[0029] Furthermore, the virtual simulation braking experiment includes offline virtual simulation braking experiment and online virtual simulation braking experiment, and the virtual braking data includes offline virtual braking data and online virtual braking data.

[0030] Furthermore, the operational status monitoring module specifically includes:

[0031] Preprocessing is performed on the physical braking data corresponding to the sensor signals acquired during the real-time physical braking process, including filtering and elimination.

[0032] A consistency analysis was performed on the preprocessed physical braking data and the virtual and real data in the database model. The physical braking data was classified into effective braking data, warning braking data, failed braking data, and braking data that is difficult to determine.

[0033] The operating status of the vehicle braking system is determined and classified into safe braking status, potentially dangerous braking status, and faulty braking status.

[0034] Furthermore, regarding the fault diagnosis module:

[0035] When the system state is determined to be a potentially dangerous braking state, it is not treated as a fault state. The system feeds back the data to the virtual-real interaction module, predicts the potential danger through the database model, gives abnormal instructions and issues warnings, and at the same time the digital twin controller adjusts the braking control strategy in a timely manner.

[0036] When the system state is determined to be a fault braking state, based on the sufficient fault data provided by the behavioral fault simulation in the database model, combined with the fault diagnosis algorithm, the fault is diagnosed and analyzed to clarify the source of the fault and the cause of component failure, and the digital twin controller makes a corresponding emergency braking control strategy.

[0037] Furthermore, the braking decision adjustment module's control strategies for safe braking states, potentially dangerous braking states, and faulty braking states specifically include:

[0038] When in a safe braking state, the system performs normal braking control, that is, it brakes according to the braking signal;

[0039] When in a potentially dangerous braking state, the system adjusts key dynamic parameters of braking efficiency and braking torque in a timely manner based on feedback signals, and corrects the system state to restore it to a safe braking state.

[0040] When the braking system is in a fault braking state, the system adjusts the emergency braking control strategy based on the fault diagnosis results and fault source analysis. Without considering braking efficiency, the system prioritizes safety and the control algorithm automatically completes the braking process.

[0041] The beneficial effects of this invention are:

[0042] The digital twin aircraft braking system of this invention integrates physical braking data and virtual braking data, greatly enriching the training data and possessing data iteration capabilities. As a result, the braking system has more accurate status monitoring, more intelligent fault diagnosis, and safer control strategy adjustment, solving the problem that traditional braking systems only have a single diagnostic function due to data sources, thereby improving the feasibility and safety of the braking system. Attached Figure Description

[0043] Figure 1 This is an overall block diagram of a virtual-real matching digital twin aircraft braking system that combines monitoring, diagnosis, and control, provided in an exemplary embodiment of the present invention.

[0044] Figure 2 This is a flowchart of virtual-real matching provided in an exemplary embodiment of the present invention;

[0045] Figure 3 This is a flowchart of the data fusion process of the virtual-real data interaction module provided in an exemplary embodiment of the present invention;

[0046] Figure 4This is a flowchart of the operation status monitoring module provided in an exemplary embodiment of the present invention;

[0047] Figure 5 This is a flowchart of the fault diagnosis module analysis provided in an exemplary embodiment of the present invention;

[0048] Figure 6 This is a flowchart illustrating the adjustment process of the control strategy adjustment module provided in an exemplary embodiment of the present invention. Detailed Implementation

[0049] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] The technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0051] See Figure 1 , Figure 1 This invention illustrates a virtual-real matching digital twin aircraft braking system combining monitoring, diagnosis, and control, as provided in an exemplary embodiment. The system includes a digital twin controller, a virtual-real matching module, a sensor perception module, a virtual-real data interaction module, an operational status monitoring module, a fault diagnosis module, and a braking decision adjustment module, wherein:

[0052] The virtual-real matching module is used to realize the correspondence between the physical braking system and the virtual twin braking system, and to realize the synchronization of braking process data and actions;

[0053] The sensor sensing module transmits the collected sensor signals to each functional module for corresponding data processing.

[0054] The virtual-real data interaction module is used to update physical braking data (physical data), virtual braking data (simulation data), and the database model: a database model of the braking system is constructed based on physical braking data and virtual braking data, and the database model is iteratively updated for each physical braking process and each virtual braking process.

[0055] The operation status monitoring module is used for valid data judgment, consistency analysis of braking data and data model, and status judgment. Specifically, it includes: using the database model in the virtual and real data interaction module to judge and analyze the sensor signal data collected during the physical braking process, monitoring the system status, and feeding back the monitoring data and judgment data to the virtual and real data interaction module.

[0056] The fault diagnosis module is used for fault determination and fault source analysis, specifically including: determining the cause of failure of the faulty component based on the status determined by the operation status monitoring module and combining the fault diagnosis algorithm, and feeding back the corresponding abnormal data and diagnostic data to the virtual and real data interaction module.

[0057] The braking decision adjustment module is used for control strategy adjustment and intelligent control, specifically including: real-time adjustment of braking control strategy decision and intelligent braking control based on data information from the operation status monitoring module and the fault diagnosis module;

[0058] The digital twin controller provides interfaces and data transfer between the modules.

[0059] Specifically, in this exemplary embodiment, the digital twin-based braking system can achieve a combination of virtual and real systems, feeding back prior braking data, fault models, and intelligent decision-making capabilities from the virtual space to the physical braking system and the driver in real time, assisting the driver in achieving more efficient and safer braking. Specifically:

[0060] The digital twin aircraft braking system in this exemplary embodiment integrates physical braking data and virtual braking data, greatly enriching the training data and possessing data iteration capabilities. As a result, the braking system has more accurate status monitoring, more intelligent fault diagnosis, and safer control strategy adjustment, solving the problem that traditional braking systems only have a single diagnostic function due to data sources, thereby improving the feasibility and safety of the braking system.

[0061] The following content will describe the specific implementation methods of each module:

[0062] More preferably, in an exemplary embodiment, the sensors collected by the sensor sensing module include a temperature sensor, a torque sensor, a wheel speed sensor, an acceleration sensor, and a wear sensor, specifically used to collect signals of the temperature of the braking system, the wear degree of the brake disc, the braking torque of the braking mechanism, the aircraft wheel speed, and the aircraft acceleration.

[0063] More preferably, in an exemplary embodiment, the functionality of all the above modules and the various interfaces are implemented by the digital twin controller. The digital twin controller is used for:

[0064] Establish connections between sensors and various functional modules, and receive and analyze signals collected by various sensors;

[0065] Establish a connection between the physical braking system and the virtual twin braking system, collect and learn physical braking data and virtual braking data, and build a database model;

[0066] It performs condition monitoring, fault diagnosis, braking decision-making, and calculation of intelligent control algorithms.

[0067] Specifically, in this exemplary embodiment, Speedgoat is used as the digital twin controller, and the program is designed to implement the functions of all modules. Various virtual and physical interfaces are also completed by this digital twin controller, which has the following functions:

[0068] (1) Provides interfaces for aircraft braking environment and 3D simulation models:

[0069] Specifically, a 3D model of the aircraft is built in Matlab / Simulink, including the braking system and braking environments such as different road surfaces, wind speeds, air densities, and temperatures. A communication interface is established with the Speedgoat digital twin controller via TCP / IP to realize the interaction of simulation data.

[0070] (2) Provide physical braking system and sensor interface:

[0071] Specifically, communication between the Speedgoat digital twin controller and the physical braking system is established through a network cable interface, and various sensors are connected through the CAN communication protocol to realize the acquisition and transmission of sensor signals and achieve the interaction of physical data.

[0072] (3) Receive and analyze signals collected by various sensors to obtain effective data, establish connections between sensors and various functional modules, and provide the required data for each module:

[0073] Specifically, the Kalman method is used to filter the received physical / simulation signals, the K-means method is used to classify and analyze the data signals, and the classified data is transmitted according to the needs of each module.

[0074] (4) Establish the connection between the physical braking system and the virtual braking system model, construct a digital twin virtual-real model, collect physical / virtual braking data, perform consistency analysis and iterative learning, and construct a database model.

[0075] (5) Perform condition monitoring, fault diagnosis, braking decision-making, and control algorithm calculation.

[0076] More preferably, in an exemplary embodiment, the digital twin controller is further configured to:

[0077] Provides a real-time human-machine interface for the braking system and offers braking assistance.

[0078] Specifically, in this exemplary embodiment, based on the digital twin model, the virtual model of the braking process can provide the operator with auxiliary information such as slip ratio and left and right wheel offset angles in real time on the human-computer interaction interface, while predicting the braking process and assisting the operator in braking.

[0079] More preferably, in an exemplary embodiment, such as Figure 2 As shown, the virtual-real matching module is constructed using digital twin technology to achieve a correspondence between the physical braking system and the virtual twin braking system, specifically including:

[0080] A matching degree analysis is performed on the dynamic parameters of the physical model of the physical braking system and the virtual model of the virtual twin braking system. If the model parameters are consistent, virtual association is performed; if the model parameters are inconsistent, the parameters of the virtual model are adjusted until the parameters are matched.

[0081] During the physical braking process, the virtual model synchronously simulates the braking action in the visualization interface, and performs a real-time consistency comparison and analysis between the characteristic parameters of the physical braking system and the dynamic parameters of the virtual model, realizing a one-to-one correspondence between virtual and real components and subsystems.

[0082] More preferably, in an exemplary embodiment, such as Figure 3 As shown, the virtual-real data interaction module specifically includes:

[0083] Virtual braking data is obtained through virtual simulation braking experiments, and physical braking data is obtained through actual braking experiments.

[0084] The physical braking data and the simulated braking data are interfacing, classified, and recombined to obtain virtual and real data.

[0085] Preprocessing is performed on both virtual and real data to smooth the data and identify outliers.

[0086] The preprocessed virtual and real data are fused to build a database model of the braking system.

[0087] Specifically, in an exemplary embodiment, the data fusion process of the virtual-real data interaction module includes the following steps:

[0088] (1) Virtual braking data is collected through offline simulation and online simulation (i.e., in a preferred exemplary embodiment, the virtual simulation braking experiment includes offline virtual simulation braking experiment and online virtual simulation braking experiment, and the virtual braking data includes offline virtual braking data and online virtual braking data);

[0089] Specifically, this process can simulate data under different braking environments and braking speeds, including normal braking and malfunction braking, to collect as much virtual braking data as possible.

[0090] (2) Collect physical braking data through online physical braking;

[0091] Specifically, during physical braking, it is necessary to ensure the safety of the braking system. Therefore, data on brake failures cannot be collected, but data on braking during skidding can be collected.

[0092] (3) Connect, classify and reorganize the virtual and real braking data;

[0093] (4) Smooth the virtual and real data and preprocess the abnormal data identification;

[0094] Specifically, the braking data is smoothed, and abnormal stacking or abrupt data is removed.

[0095] (5) The preprocessed real and virtual numbers are fused to construct data for learning;

[0096] (6) Construct a braking system database;

[0097] It can be seen that by using effective virtual and real data for deep learning, various braking databases can be constructed using braking data of different types and different braking conditions, including normal braking, abnormal braking, and braking under different environmental conditions.

[0098] More preferably, in an exemplary embodiment, such as Figure 4 As shown, the operation status monitoring module specifically includes:

[0099] Preprocessing is performed on the physical braking data corresponding to the sensor signals acquired during the real-time physical braking process, including filtering and elimination.

[0100] A consistency analysis was performed on the preprocessed physical braking data and the virtual and real data in the database model. The physical braking data was classified into effective braking data, warning braking data, failed braking data, and braking data that is difficult to determine.

[0101] The operating status of the vehicle braking system is determined and classified into safe braking status, potentially dangerous braking status, and faulty braking status.

[0102] Specifically, in an exemplary embodiment, the specific steps of the operation status monitoring module can be as follows:

[0103] (1) Perform real-time preprocessing on the sensor signals acquired by the sensor module in real time;

[0104] Specifically, the system pressure, temperature, wheel speed, acceleration status data, and other signals collected in real time by braking are filtered and eliminated to obtain effective real-time braking data.

[0105] (2) Perform consistency analysis and regression on the preprocessed brake data and data model, and classify the brake data into effective brake data, warning brake data, failed brake data and difficult-to-determine brake data.

[0106] (3) Determine the braking status;

[0107] Specifically, the categorized data is used to determine the operational status based on the database model, classifying the system's operational status into safe braking, potentially dangerous braking, and fault braking.

[0108] More preferably, in an exemplary embodiment, such as Figure 5 As shown, for the fault diagnosis module:

[0109] When the system state is determined to be a potentially dangerous braking state, it is not treated as a fault state. The system feeds back the data to the virtual-real interaction module, predicts the potential danger through the database model, gives abnormal instructions and issues warnings, and at the same time the digital twin controller adjusts the braking control strategy in a timely manner.

[0110] When the system state is determined to be a fault braking state, based on the sufficient fault data provided by the behavioral fault simulation in the database model, and combined with the fault diagnosis algorithm, the fault is diagnosed and analyzed to clarify the source of the fault and the cause of component failure (such as sensor failure, control loop failure, brake disc failure, motor failure, etc.), and the digital twin controller makes corresponding emergency braking control strategies.

[0111] More preferably, in an exemplary embodiment, such as Figure 6 As shown, the braking decision adjustment module's control strategies for safe braking states, potentially dangerous braking states, and faulty braking states specifically include:

[0112] (1) When in a safe braking state, the system performs normal braking control, that is, braking according to the braking signal; it can also brake efficiently with the optimal slip ratio control strategy according to the braking signal.

[0113] (2) When in a potentially dangerous braking state, the system adjusts the key dynamic parameters of braking efficiency and braking torque in a timely manner based on the feedback signal, and corrects the system state in a timely manner to restore it to a safe braking state.

[0114] (3) When the braking system is in a fault braking state, the system adjusts the emergency braking control strategy based on the fault diagnosis results and fault source analysis, starts safety fault-tolerant control, does not consider braking efficiency, takes safety as the only goal, and the control algorithm automatically completes the braking process.

[0115] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art can make other variations or modifications based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A virtual-real matching digital twin aircraft braking system that combines monitoring, diagnosis, and control, characterized in that: It includes a digital twin controller, a virtual-real matching module, a sensor perception module, a virtual-real data interaction module, an operation status monitoring module, a fault diagnosis module, and a braking decision adjustment module, among which: The virtual-real matching module is used to realize the correspondence between the physical braking system and the virtual twin braking system, and to realize the synchronization of braking process data and actions; The sensor sensing module transmits the collected sensor signals to each functional module for corresponding data processing. The virtual-real data interaction module is used to update physical braking data, virtual braking data, and the database model: a database model of the braking system is constructed based on physical braking data and virtual braking data, and the database model is iteratively updated with data from each physical braking process and virtual braking process. The operation status monitoring module is used for valid data judgment, consistency analysis of braking data and data model, and status judgment. Specifically, it includes: using the database model in the virtual and real data interaction module to judge and analyze the sensor signal data collected during the physical braking process, monitoring the system status, and feeding back the monitoring data and judgment data to the virtual and real data interaction module. The fault diagnosis module is used for fault determination and fault source analysis, specifically including: determining the cause of failure of the faulty component based on the status determined by the operation status monitoring module and combining the fault diagnosis algorithm, and feeding back the corresponding abnormal data and diagnostic data to the virtual and real data interaction module. The braking decision adjustment module is used for control strategy adjustment and intelligent control, specifically including: real-time adjustment of braking control strategy decision and intelligent braking control based on data information from the operation status monitoring module and the fault diagnosis module; The digital twin controller provides interfaces and data transfer between the modules.

2. The virtual-real matching digital twin aircraft braking system combining monitoring, diagnosis, and control as described in claim 1, characterized in that: The sensor sensing module collects signals from various sensors, including temperature sensors, torque sensors, wheel speed sensors, acceleration sensors, and wear sensors. Specifically, it collects signals related to the temperature of the braking system, the wear degree of the brake discs, the braking torque of the braking mechanism, the aircraft wheel speed, and the aircraft acceleration.

3. The virtual-real matching digital twin aircraft braking system combining monitoring, diagnosis, and control as described in claim 1, characterized in that: The digital twin controller is used for: Establish connections between sensors and various functional modules, and receive and analyze signals collected by various sensors; Establish a connection between the physical braking system and the virtual twin braking system, collect and learn physical braking data and virtual braking data, and build a database model; It performs condition monitoring, fault diagnosis, braking decision-making, and calculation of intelligent control algorithms.

4. The virtual-real matching digital twin aircraft braking system combining monitoring, diagnosis, and control as described in claim 3, characterized in that: The digital twin controller is also used for: Provides a real-time human-machine interface for the braking system and offers braking assistance.

5. The virtual-real matching digital twin aircraft braking system combining monitoring, diagnosis, and control as described in claim 1, characterized in that: The virtual-real matching module is constructed using digital twin technology to achieve a correspondence between the physical braking system and the virtual twin braking system, specifically including: A matching degree analysis is performed on the dynamic parameters of the physical model of the physical braking system and the virtual model of the virtual twin braking system. If the model parameters are consistent, virtual association is performed; if the model parameters are inconsistent, the parameters of the virtual model are adjusted until the parameters are matched. During the physical braking process, the virtual model synchronously simulates the braking action in the visualization interface, and performs a real-time consistency comparison and analysis between the characteristic parameters of the physical braking system and the dynamic parameters of the virtual model, realizing a one-to-one correspondence between virtual and real components and subsystems.

6. The virtual-real matching digital twin aircraft braking system combining monitoring, diagnosis, and control as described in claim 1, characterized in that: The virtual-real data interaction module specifically includes: Virtual braking data is obtained through virtual simulation braking experiments, and physical braking data is obtained through actual braking experiments. The physical braking data and the simulated braking data are interfacing, classified, and recombined to obtain virtual and real data. Preprocessing is performed on both virtual and real data to smooth the data and identify outliers. The preprocessed virtual and real data are fused to build a database model of the braking system.

7. The virtual-real matching digital twin aircraft braking system combining monitoring, diagnosis, and control as described in claim 6, characterized in that: The virtual simulation braking experiment includes offline virtual simulation braking experiment and online virtual simulation braking experiment, and the virtual braking data includes offline virtual braking data and online virtual braking data.

8. The virtual-real matching digital twin aircraft braking system combining monitoring, diagnosis, and control as described in claim 1, characterized in that: The operational status monitoring module specifically includes: Preprocessing is performed on the physical braking data corresponding to the sensor signals acquired during the real-time physical braking process, including filtering and elimination. A consistency analysis was performed on the preprocessed physical braking data and the virtual and real data in the database model. The physical braking data was classified into effective braking data, warning braking data, failed braking data, and braking data that is difficult to determine. The operating status of the vehicle braking system is determined and classified into safe braking status, potentially dangerous braking status, and faulty braking status.

9. The virtual-real matching digital twin aircraft braking system combining monitoring, diagnosis, and control as described in claim 8, characterized in that: For the fault diagnosis module: When the system state is determined to be a potentially dangerous braking state, it is not treated as a fault state. The system feeds back the data to the virtual-real interaction module, predicts the potential danger through the database model, gives abnormal instructions and issues warnings, and at the same time the digital twin controller adjusts the braking control strategy in a timely manner. When the system state is determined to be a fault braking state, based on the sufficient fault data provided by the behavioral fault simulation in the database model, combined with the fault diagnosis algorithm, the fault is diagnosed and analyzed to clarify the source of the fault and the cause of component failure, and the digital twin controller makes a corresponding emergency braking control strategy.

10. The virtual-real matching digital twin aircraft braking system combining monitoring, diagnosis, and control according to claim 9, characterized in that: The braking decision adjustment module's control strategies for safe braking states, potentially dangerous braking states, and faulty braking states specifically include: When in a safe braking state, the system performs normal braking control, that is, it brakes according to the braking signal; When in a potentially dangerous braking state, the system adjusts key dynamic parameters of braking efficiency and braking torque in a timely manner based on feedback signals, and corrects the system state to restore it to a safe braking state. When the braking system is in a fault braking state, the system adjusts the emergency braking control strategy based on the fault diagnosis results and fault source analysis. Without considering braking efficiency, the system prioritizes safety and the control algorithm automatically completes the braking process.

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