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

Abstract

The invention discloses a virtual-real matching digital twin aircraft brake system combining monitoring, diagnosis and control, which comprises 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 a corresponding relation between a physical braking system and a virtual twin braking system and realizing data and action synchronization in a braking process; the virtual-real data interaction module is used for updating the physical brake data, the virtual brake data and a database model; the operation state monitoring module is used for effective data judgment, consistency analysis of brake data and a data model and state judgment; the fault diagnosis module is used for fault judgment and fault source analysis; and the brake decision adjustment module is used for control strategy adjustment and intelligent control. Physical brake data and virtual brake data are fused, and the feasibility and safety of the brake system are improved.

Description

Technical Field

[0001] The present invention relates to the field of digital twin aircraft braking, and in particular to a virtual-reality matching digital twin aircraft braking system that combines monitoring, diagnosis, and control. Background Art

[0002] Accidents before takeoff and after landing have surpassed those during the flight phase, placing even higher demands on aircraft safety. As an onboard component, the aircraft's braking system plays a crucial role in landing. With the increasing demand for aviation operations across various industries, the braking environment faced by the braking systems of unconventional aircraft (drones, fighter jets, and ultra-large carrier aircraft) has become even more challenging. Consequently, higher technical requirements are being placed on the reliability, safety, and braking performance of the braking system.

[0003] Digital twin technology can describe physical systems using virtual models, simulating data from physical entities in virtual space, greatly simplifying data sources. In the automotive brake system sector, relying on physical devices for brake control testing and debugging is inefficient and costly. A brake system integrated with digital twins can effectively address this issue. Compared to automotive braking, aircraft brake testing is more expensive and potentially more dangerous. Therefore, integrating digital twin technology to collect simulated data sets is essential for aircraft brake systems. However, there is currently no publicly available technical documentation on aircraft brake systems that incorporate digital twins. Furthermore, aircraft brake systems, based on data-driven safe braking methods, are limited by data sources and have only a single diagnostic function, unable to monitor brake system status or adjust safe braking strategies in real time. Summary of the Invention

[0004] The purpose of the present invention is to overcome the shortcomings of the existing technology and provide a virtual-reality matching digital twin aircraft braking system that combines monitoring, diagnosis and control.

[0005] The object of the present invention is achieved through the following technical solutions:

[0006] In a first aspect, the present invention provides a virtual-reality matching digital twin aircraft braking system that combines monitoring, diagnosis, and control, including a digital twin controller, a virtual-reality matching module, a sensor perception module, a virtual-reality data interaction module, an operating 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 synchronize the braking process data and actions;

[0008] The sensor perception 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 the physical braking data, virtual braking data, and database model: a database model of the braking system is constructed based on the physical braking data and the virtual braking data. The database model is iteratively updated every time the data of the physical braking process and the virtual braking process are processed.

[0010] The operating status monitoring module is used for valid data judgment, brake data and data model consistency analysis, and status judgment, specifically including: using the database model in the virtual-real data interaction module to distinguish and analyze the sensor signal data collected during the physical braking process, monitor the system status, and feed back the monitoring data and judgment data to the virtual-real data interaction module;

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

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

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

[0014] Furthermore, for the sensor perception module, the collected sensors include temperature sensors, torque sensors, wheel speed sensors, acceleration sensors and wear sensors, which are specifically used to collect signals of the temperature of the brake system, the wear degree of the brake disc, the braking torque of the braking mechanism, the aircraft wheel speed, and the aircraft acceleration.

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

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

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

[0020] Provides a real-time human-computer interaction interface for the braking system and provides braking assistance.

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

[0022] Perform a matching analysis on the dynamic parameters of the physical model of the physical brake system and the virtual model of the virtual twin brake system. If the model parameters are consistent, a virtual correlation is performed. If the model parameters are inconsistent, the parameters of the virtual model are adjusted until the parameters match.

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

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

[0025] Get virtual braking data through virtual simulation braking experiments, and get physical braking data through actual braking experiments;

[0026] Connect, classify and reorganize physical braking data and simulated braking data to obtain virtual and real data;

[0027] Preprocessing of smoothing virtual and real data and identifying abnormal data;

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

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

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

[0031] Preprocessing of filtering and eliminating physical braking data corresponding to sensor signals collected during real-time physical braking;

[0032] Perform consistency analysis on the pre-processed physical brake data and the virtual and real data in the database model, and classify the physical brake data into valid brake data, warning brake data, invalid brake data, and difficult-to-determine brake data;

[0033] The operating status of the braking system is judged and divided into safe braking status, potentially dangerous braking status, and faulty braking status.

[0034] Furthermore, for the fault diagnosis module:

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

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

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

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

[0039] When in a potentially dangerous braking state, the system promptly adjusts key dynamic parameters such as braking efficiency and braking torque based on feedback signals, and promptly corrects the system state to restore it to a safe braking state;

[0040] When the brake system is in a faulty braking state, the system adjusts the emergency braking control strategy based on the fault diagnosis results and fault source analysis, without considering braking efficiency. With safety as the only goal, the control algorithm automatically completes the braking process.

[0041] The beneficial effects of the present invention are:

[0042] The digital twin aircraft braking system of the present invention integrates physical braking data and virtual braking data, greatly enriching the training data and having data iteration capabilities. Therefore, 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 the data source, thereby improving the feasibility and safety of the braking system. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

[0045] Figure 3 A data fusion flow chart of a virtual-real data interaction module provided in an exemplary embodiment of the present invention;

[0046] Figure 4A monitoring flow chart of an operation status monitoring module provided in an exemplary embodiment of the present invention;

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

[0048] Figure 6 This is a flow chart of adjusting a control strategy adjustment module provided in an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0049] The technical solution of the present invention is described clearly and completely below with reference to the accompanying drawings. It is apparent that the embodiments described are only a portion of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are intended to fall 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 also Figure 1 , Figure 1 A virtual-reality matching digital twin aircraft braking system combining monitoring, diagnosis, and control provided in an exemplary embodiment of the present invention is shown, including a digital twin controller, a virtual-reality matching module, a sensor perception module, a virtual-reality data interaction module, an operating 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 synchronize the braking process data and actions;

[0053] The sensor perception 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 the physical braking data (physical data), virtual braking data (simulation data), and database model: a database model of the braking system is constructed based on the physical braking data and the virtual braking data. The database model is iteratively updated every time the data of the physical braking process and the data of the virtual braking process are processed.

[0055] The operating status monitoring module is used for valid data judgment, brake data and data model consistency analysis, and status judgment, specifically including: using the database model in the virtual-real data interaction module to distinguish and analyze the sensor signal data collected during the physical braking process, monitor the system status, and feed back the monitoring data and judgment data to the virtual-real data interaction module;

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

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

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

[0059] Specifically, in this exemplary embodiment, the digital twin-based braking system can achieve a virtual-physical integration, feeding back prior braking data, fault models, and intelligent decision-making capabilities in the virtual space to the physical braking system and driver in real time, assisting the driver in achieving more efficient and safe 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 providing data iteration capabilities. As a result, the braking system has more accurate status monitoring, smarter fault diagnosis, and safer control strategy adjustment, solving the problem that traditional braking systems only have a single diagnostic function due to the data source, thereby improving the feasibility and safety of the braking system.

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

[0062] More preferably, in an exemplary embodiment, for the sensor perception module, the collected sensors include a temperature sensor, a torque sensor, a wheel speed sensor, an acceleration sensor and a wear sensor, which are specifically used to collect signals of the temperature of the brake 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 functional implementation and various interfaces of all the above modules are completed by the digital twin controller. The digital twin controller is used to:

[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] Perform 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 a program is designed to implement the functions of all modules. Various virtual and real interfaces are also completed by the digital twin controller, which has the following functions:

[0068] (1) Provide aircraft braking environment and 3D simulation model interface:

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

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

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

[0072] (3) Receive and analyze the signals collected by various sensors to obtain valid 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 are transmitted according to the needs of each module.

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

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

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

[0077] Provides a real-time human-computer interaction interface for the braking system and provides braking assistance.

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

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

[0080] Perform a matching analysis on the dynamic parameters of the physical model of the physical brake system and the virtual model of the virtual twin brake system. If the model parameters are consistent, a virtual correlation is performed. If the model parameters are inconsistent, the parameters of the virtual model are adjusted until the parameters match.

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

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

[0083] Get virtual braking data through virtual simulation braking experiments, and get physical braking data through actual braking experiments;

[0084] Connect, classify and reorganize physical braking data and simulated braking data to obtain virtual and real data;

[0085] Preprocessing of smoothing virtual and real data and identifying abnormal data;

[0086] The pre-processed 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) Collecting virtual braking data through offline simulation and online simulation (i.e., in a preferred exemplary embodiment, the virtual simulation braking experiment includes an offline virtual simulation braking experiment and an 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 different braking speeds, including normal braking, faulty braking, etc., and collect as much virtual braking data as possible.

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

[0091] Specifically, the safety of the braking system needs to be ensured during the physical braking process. Therefore, the collected data does not include fault braking data, and the braking data during skidding can be collected.

[0092] (3) ,connecting, classifying and reorganizing virtual and real braking data;

[0093] (4) Smoothing of virtual and real data and preprocessing of abnormal data identification;

[0094] Specifically, the braking data is smoothed and abnormally stacked and abrupt data is deleted.

[0095] (5) ,Fusing the pre-processed imaginary and real numbers to construct data for learning;

[0096] (6) Build a brake system database;

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

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

[0099] Preprocessing of filtering and eliminating physical braking data corresponding to sensor signals collected during real-time physical braking;

[0100] Perform consistency analysis on the pre-processed physical brake data and the virtual and real data in the database model, and classify the physical brake data into valid brake data, warning brake data, invalid brake data, and difficult-to-determine brake data;

[0101] The operating status of the braking system is judged and divided into safe braking status, potentially dangerous braking status, and faulty braking status.

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

[0103] (1) Preprocessing the sensor signals collected by the sensor module in real time;

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

[0105] (2) Perform consistency analysis and regression on the pre-processed braking data and the data model, and classify the braking data into valid braking data, warning braking data, invalid braking data, and difficult-to-determine braking data;

[0106] (3) Determine the braking status;

[0107] Specifically, the classified data is used to determine the operating status according to the database model, and the operating status of the system is divided into safe braking, potential dangerous braking, and faulty braking.

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

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

[0110] When the system state is determined to be a faulty braking state, the fault is diagnosed and analyzed based on the sufficient fault data provided by the behavioral fault simulation in the database model and combined with the fault diagnosis algorithm 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 a corresponding emergency braking control strategy.

[0111] More preferably, in an exemplary embodiment, Figure 6 As shown, the braking decision adjustment module specifically includes the following control strategies for safe braking state, potentially dangerous braking state, and faulty braking state:

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

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

[0114] (3) When the brake system is in a faulty braking state, the system adjusts the emergency braking control strategy based on the fault diagnosis results and fault source analysis, starts safe fault-tolerant control, and automatically completes the braking process with safety as the only goal, regardless of braking efficiency.

[0115] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will readily appreciate that other variations or modifications can be made based on the above descriptions. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications derived therefrom remain within the scope of protection of the present invention.

Claims

1. A virtual-real matching digital twin aircraft braking system that combines monitoring, diagnosis, and control, featuring: It includes a digital twin controller, a virtual-reality matching module, a sensor perception module, a virtual-reality 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 synchronize the braking process data and actions; The sensor perception module transmits the collected sensor signals to each functional module for corresponding data processing; The virtual-real data interaction module is used to update the physical braking data, virtual braking data, and database model: a database model of the braking system is constructed based on the physical braking data and the virtual braking data. The database model is iteratively updated every time the data of the physical braking process and the virtual braking process are processed. The operating status monitoring module is used for valid data judgment, brake data and data model consistency analysis, and status judgment, specifically including: using the database model in the virtual-real data interaction module to distinguish and analyze the sensor signal data collected during the physical braking process, monitor the system status, and feed back the monitoring data and judgment data to the virtual-real data interaction module; The fault diagnosis module is used for fault determination and fault source analysis, specifically including: determining the failure cause of the faulty component based on the status determined by the operation status monitoring module in combination with the fault diagnosis algorithm, and feeding back the corresponding abnormal data and diagnostic data to the virtual-real data interaction module; The brake decision adjustment module is used for control strategy adjustment and intelligent control, specifically including: real-time adjustment of brake control strategy decision and intelligent brake control according to data information of the operation status monitoring module and the fault diagnosis module; The digital twin controller provides interfaces and data transmission between modules.

2. The virtual-real matching digital twin aircraft braking system combining monitoring, diagnosis, and control according to claim 1 is characterized by: For the sensor perception module, the collected sensors include temperature sensors, torque sensors, wheel speed sensors, acceleration sensors and wear sensors, which are specifically used to collect signals of the temperature of the brake system, the wear degree of the brake disc, 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 according to claim 1 is characterized by: The digital twin controller is used to: 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; Perform 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 according to claim 3 is characterized by: The digital twin controller is also used to: Provides a real-time human-computer interaction interface for the braking system and provides braking assistance.

5. The virtual-real matching digital twin aircraft braking system combining monitoring, diagnosis, and control according to claim 1 is characterized by: The virtual-real matching module is constructed using digital twin technology to achieve the correspondence between the physical braking system and the virtual twin braking system, specifically including: Perform a matching analysis on the dynamic parameters of the physical model of the physical brake system and the virtual model of the virtual twin brake system. If the model parameters are consistent, a virtual correlation is performed. If the model parameters are inconsistent, the parameters of the virtual model are adjusted until the parameters match. During the physical braking process, the virtual model synchronously simulates the braking action in the visual interface, and conducts a real-time consistency comparison and analysis between the characteristic parameters of the physical braking system and the dynamic parameters of the virtual model to achieve 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 according to claim 1 is characterized by: The virtual-real data interaction module specifically includes: Get virtual braking data through virtual simulation braking experiments, and get physical braking data through actual braking experiments; Connect, classify and reorganize physical braking data and simulated braking data to obtain virtual and real data; Preprocessing of smoothing virtual and real data and identifying abnormal data; The pre-processed 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 according to claim 6 is characterized by: The virtual simulation braking experiment includes an offline virtual simulation braking experiment and an 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 according to claim 1 is characterized by: The operation status monitoring module specifically includes: Preprocessing of filtering and eliminating physical braking data corresponding to sensor signals collected during real-time physical braking; Perform consistency analysis on the pre-processed physical brake data and the virtual and real data in the database model, and classify the physical brake data into valid brake data, warning brake data, invalid brake data, and difficult-to-determine brake data; The operating status of the braking system is judged and divided 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 according to claim 8 is characterized by: For the fault diagnosis module: When the system status is judged to be a potentially dangerous braking state, it is not treated as a fault state. The system feeds data back to the virtual-reality interaction module, predicts potential dangers through the database model, gives abnormal instructions and issues warnings, and the digital twin controller adjusts the braking control strategy in a timely manner. When the system state is determined to be a faulty braking state, the fault is diagnosed and analyzed based on the sufficient fault data provided by the behavioral fault simulation in the database model, combined with the fault diagnosis algorithm, to clarify the source of the fault and the cause of component failure, and the digital twin controller will make 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 is characterized by: The braking decision adjustment module specifically includes the following control strategies for safe braking state, potentially dangerous braking state, and faulty braking state: When in the safe braking state, the system performs normal braking control, that is, braking according to the braking signal; When in a potentially dangerous braking state, the system promptly adjusts key dynamic parameters such as braking efficiency and braking torque based on feedback signals, and promptly corrects the system state to restore it to a safe braking state; When the brake system is in a faulty braking state, the system adjusts the emergency braking control strategy based on the fault diagnosis results and fault source analysis, without considering braking efficiency. With safety as the only goal, the control algorithm automatically completes the braking process.

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