Data processing system and method for aircraft driving parameter simulation playback

Abstract

The invention relates to the technical field of aircraft driving parameter simulation, in particular to a data processing system and method for aircraft driving parameter simulation playback. The data processing system comprising an acquisition module, a storage module, a processing module, a display module and an analysis module is constructed to acquire, store, process, display and analyze flight state data and driving operation data in a flight simulation process of a driver, so that a flight playback image, a flight state parameter and a flight quality parameter are obtained; and the operation skill of the driver is evaluated and analyzed, so that the operation skill of the driver is guided, and the safety of future flight driving is improved.

Description

Technical Field

[0001] The present application relates to the technical field of aircraft driving parameter simulation, and in particular to a data processing system and method for aircraft driving parameter simulation playback. Background Art

[0002] At present, in the process of simulated driving, driving training and accident investigation in the aviation field, it is often necessary to extract the data generated during the simulated driving process of the flight simulator or the real flight driving process, transfer the data to the analysis software for analysis, and finally realize the simulation playback of the flight process. The rationality of the simulation in the simulation playback process directly affects the validity of the analysis results and the safety of future flight driving. It is of great significance to guide the pilot's operating skills through the simulation playback of aircraft driving parameters. Summary of the invention

[0003] In order to guide the pilot's operating skills through the simulation playback of aircraft driving parameters, the present application provides a data processing system and method for the simulation playback of aircraft driving parameters, which adopts the following technical solutions: In a first aspect, the present application provides a data processing system for aircraft driving parameter simulation playback, comprising: The acquisition module is used to collect the flight status data and driving operation data generated during the flight simulation; A storage module, used to store the flight status data and driving operation data collected by the collection module, and organize them in time sequence and parameter category; A processing module, used for extracting and calculating the flight status data and driving operation data organized and stored by the storage module to obtain aircraft status parameters and flight quality parameters; A display module is used to perform three-dimensional visual dynamic playback according to the flight state parameters and flight quality parameters processed by the processing module to display the flight motion state and the driving operation process; The analysis module is used to evaluate and analyze the pilot's operating skills based on the playback images of the display module, the flight status parameters and the flight quality parameters processed by the processing module.

[0004] By adopting the above-mentioned technical solution, the present application constructs a data processing system including an acquisition module, a storage module, a processing module, a display module and an analysis module to collect, store, process, display and analyze the flight status data and driving operation data during the pilot's flight simulation process, thereby obtaining flight playback images, flight status parameters and flight quality parameters, evaluating and analyzing the pilot's operating skills, and then guiding the pilot's operating skills to improve the safety of future flight driving.

[0005] In a preferred embodiment, the present application can be further configured as follows: the flight status data includes aircraft speed parameters, aircraft altitude parameters, aircraft pitch angle parameters, aircraft roll angle parameters and aircraft heading angle parameters; the driving operation data includes elevator position parameters, rudder position parameters, throttle position parameters, flap position parameters and landing gear position parameters.

[0006] By adopting the above technical solution, the types of flight status data and driving operation data are specifically disclosed.

[0007] In a preferred embodiment, the present application may be further configured to include: An auxiliary module, used for receiving the driver's voice instructions and feedback, converting them into text instructions, and transmitting them to the processing module; The processing module is also used to analyze the matching degree between the text instruction and the driving operation data, and judge the voice response ability of the driver.

[0008] By adopting the above-mentioned technical solution, the present application receives the driver's voice commands and feedback through the auxiliary module and converts them into text commands. The processing module analyzes the matching degree between the text commands and the driving operation data, thereby realizing voice interaction and solving the problem of insufficient playback authenticity. At the same time, the pilot's flying skills in voice interaction are examined.

[0009] In a preferred embodiment, the present application may be further configured such that when the matching degree is lower than a threshold, the auxiliary module performs speech recognition error analysis and generates speech training suggestions to improve the driver's speech response ability.

[0010] By adopting the above technical solution, the present application sets thresholds, performs error analysis on speech recognition, and generates speech training suggestions, thereby providing analysis and training solutions when speech recognition is difficult, thereby improving the driver's speech response ability.

[0011] In a preferred embodiment, the present application may be further configured such that the processing module sets reliability levels for different voice commands, and different reliability levels of voice commands require different recognition accuracy rates; When the important flight instruction does not reach the corresponding reliability level, the processing module converts it into manual confirmation input or multi-modal confirmation input.

[0012] By adopting the above-mentioned technical solution, the present application sets reliability levels for different voice commands. When the recognition accuracy of important flight commands does not reach the corresponding reliability level, it is converted to manual confirmation input or multimodal confirmation input, thereby increasing the reliability of the system.

[0013] In a preferred embodiment, the present application can be further configured such that the analysis module is also used to obtain the driver's assessment level, and adjust the difficulty of scene training including voice interaction according to the assessment level. When the driver's assessment level is low, the voice interaction is set to non-critical instructions and dialogues.

[0014] By adopting the above technical solution, the present application adjusts the training difficulty according to the driver's assessment level to achieve targeted training optimization and evaluation analysis.

[0015] In a second aspect, the present application provides a data processing method for aircraft driving parameter simulation playback, comprising the following steps: Collect flight status data and driving operation data generated during flight simulation; Store the collected flight status data and driving operation data and organize them in chronological order and parameter categories; Extract and calculate the flight status data and driving operation data stored in the organization to obtain aircraft status parameters and flight quality parameters; According to the processed flight status parameters and flight quality parameters, three-dimensional visual dynamic playback is performed to display the flight motion status and driving operation process; The pilot's operating skills are evaluated and analyzed based on the playback images, processed flight status parameters and flight quality parameters.

[0016] In a preferred embodiment, the present application can be further configured as follows: the flight status data includes aircraft speed parameters, aircraft altitude parameters, aircraft pitch angle parameters, aircraft roll angle parameters and aircraft heading angle parameters; the driving operation data includes elevator position parameters, rudder position parameters, throttle position parameters, flap position parameters and landing gear position parameters.

[0017] In a preferred embodiment, the present application may be further configured as follows: Receive the driver's voice commands and feedback and convert them into text commands; The matching degree between the text instruction and the driving operation data is analyzed to determine the voice response ability of the driver.

[0018] In a preferred embodiment of the present application, the method may be further configured as follows: after analyzing the matching degree between the text instruction and the driving operation data, the method further includes: When the matching degree is lower than a threshold, a speech recognition error analysis is performed and a speech training suggestion is generated to improve the driver's speech response ability.

[0019] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the data processing method for simulating playback of the above-mentioned aircraft driving parameters when executing the computer program.

[0020] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the data processing method for the above-mentioned aircraft driving parameter simulation playback.

[0021] In summary, the present application includes at least one of the following beneficial technical effects: 1. This application constructs a data processing system including an acquisition module, a storage module, a processing module, a display module and an analysis module to collect, store, process, display and analyze the flight status data and driving operation data of the pilot during the flight simulation, thereby obtaining flight playback images, flight status parameters and flight quality parameters, evaluating and analyzing the pilot's operating skills, and then guiding the pilot's operating skills to improve the safety of future flight driving; 2. This application receives the pilot's voice commands and feedback through an auxiliary module and converts them into text commands. The processing module analyzes the degree of matching between the text commands and the driving operation data, thereby realizing voice interaction and solving the problem of insufficient playback authenticity. At the same time, it examines the pilot's flying skills in voice interaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a module schematic diagram of a data processing system for aircraft driving parameter simulation playback according to an embodiment of the present application; Figure 2 It is an exemplary flow chart of a data processing method for aircraft driving parameter simulation playback in an embodiment of the present application; Figure 3 It is a diagram of the internal structure of the electronic device according to the embodiment of the present application. DETAILED DESCRIPTION

[0023] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more listed items.

[0024] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0025] The present application provides a data processing system and method for aircraft driving parameter simulation playback. By constructing a data processing system including an acquisition module, a storage module, a processing module, a display module and an analysis module, the flight status data and driving operation data of the pilot in the flight simulation process are collected, stored, processed, displayed and analyzed, so as to obtain flight playback images, flight status parameters and flight quality parameters, evaluate and analyze the pilot's operating skills, and then guide the pilot's operating skills, thereby improving the safety of future flight driving.

[0026] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0027] Reference Figure 1 , Figure 1 It is a module schematic diagram of a data processing system for aircraft driving parameter simulation playback in an embodiment of the present application.

[0028] A data processing system for aircraft driving parameter simulation playback, comprising: The acquisition module 110 is used to acquire the flight status data and driving operation data generated during the flight simulation process.

[0029] Specifically, the flight status data includes aircraft speed parameters, aircraft altitude parameters, aircraft pitch angle parameters, aircraft roll angle parameters and aircraft heading angle parameters; the driving operation data includes elevator position parameters, rudder position parameters, throttle position parameters, flap position parameters and landing gear position parameters. The acquisition module 110 is composed of various sensors for collecting flight parameters, which may specifically include speed sensors, altitude sensors, attitude angle sensors, vertical gyroscopes, roll gyroscopes, magnetometers, GPS, airborne inertial navigation systems, and position sensors for operating levers, throttles, flaps and landing gears, etc. The sampling frequency is set at 50-60Hz. All sensors are connected to the data acquisition unit via a data bus.

[0030] The storage module 120 is used to store the flight status data and driving operation data collected by the collection module 110, and organize them in chronological order and parameter categories.

[0031] Specifically, by adopting a solid-state hard drive as the storage medium, using a database to store the flight time series, and establishing a parameter category name index, the flight data is managed through time sequence and classified storage, and indexed according to the time series and parameter category name during playback.

[0032] The processing module 130 is used to extract and calculate the flight status data and driving operation data organized and stored by the storage module 120 to obtain aircraft status parameters and flight quality parameters.

[0033] Specifically, the processing module 130 is composed of an aerodynamic processing unit 131, a flight control processing unit 132, and a flight quality processing unit 133. The aerodynamic processing unit 131 extracts flight status data and driving operation data including aircraft speed parameters, aircraft altitude parameters, elevator position parameters, rudder position parameters, throttle position parameters, flap position parameters, and landing gear position parameters from the storage module 120, and uses an aerodynamic model to solve the aircraft state parameters such as the aircraft airspeed, flight angle of attack, sideslip angle, lift, and drag. The flight control processing unit 132 calculates aircraft attitude parameters such as the aircraft pitch angle parameter, roll angle parameter, and yaw angle parameter based on the flight status data and driving operation data. The flight quality processing unit 133 uses a preset evaluation function to calculate and obtain evaluation indicators reflecting flight quality such as smoothness parameters and control coordination parameters based on aircraft state parameters and aircraft attitude parameters. Among them, the evaluation function is pre-formulated according to the civil aviation flight quality standard.

[0034] The display module 140 is used to perform three-dimensional visual dynamic playback according to the flight state parameters and flight quality parameters processed by the processing module 130 to display the flight motion state and the driving operation process.

[0035] Specifically, the display module 140 calculates the 3D position and attitude of the 3D model of the aircraft at each moment and displays the flight trajectory synchronously through the pre-built 3D model of the aircraft, the flight environment scene and the sky model according to the flight status parameters output by the processing module 130. At the same time, a virtual lens can be set in the aircraft cabin to provide the driver's perspective and display the flight parameters in conjunction with the physical instrument.

[0036] The analysis module 150 is used to evaluate and analyze the pilot's operating skills based on the playback images of the display module 140 and the flight status parameters and flight quality parameters processed by the processing module 130.

[0037] Specifically, features that reflect the driver's operating skills, such as the smoothness, accuracy, and coordination of the operation, are extracted from the playback images, flight status parameters, and flight quality parameters. A driver skill evaluation model is constructed using a machine learning algorithm to evaluate the driver's skills. The model sets different weights for different features to determine the skill dimensions that have the greatest impact on the evaluation results. Based on the model output results, clustering and sorting methods are used to determine the driver's operating skill level, generate a skill evaluation report, and give the quality of the operation, existing problems, and improvement suggestions. Furthermore, historical driver data can be collected to build a personalized skill evaluation model.

[0038] In a preferred embodiment, the present application is configured with an auxiliary module 160 for receiving the driver's voice commands and feedback, converting them into text commands, and transmitting them to the processing module 130; the processing module 130 is also used to analyze the degree of match between the text commands and the driving operation data, and to determine the driver's voice response ability.

[0039] Specifically, the auxiliary module 160 includes a speech recognition unit 161 and a speech understanding unit 162. The speech recognition unit 161 recognizes the voice command into text through a deep neural network model, and the speech understanding unit 162 maps the text command to a predefined command set and outputs a standardized command format. The processing module 130 includes a matching analysis unit 134, which establishes a correlation model between the standard command and the driving operation at the same time, and evaluates the quality of the voice response by statistically analyzing indicators such as the accuracy of the execution of the command, the delay time, and the smoothness of the operation. Among them, the matching analysis model adopts a supervised learning method and is trained using annotated voice-operation data. In some embodiments, multiple levels of quality thresholds can be set to determine the driver's voice response ability level. Finally, a quality report of the voice interaction is generated, pointing out the problems with the voice response and providing targeted improvement suggestions.

[0040] In a preferred embodiment, when the matching degree between the text instruction and the driving operation data is lower than a threshold, the auxiliary module 160 performs speech recognition error analysis and generates speech training suggestions to improve the driver's speech response ability.

[0041] Specifically, we collect voice command samples that produce matching errors, analyze the voice features of the samples, check the voice quality, background noise level, speech speed and intonation, analyze the output of the voice recognition model, determine the error type, such as unclear voice, dialect accent, misrecognition of similar words, etc., locate the wrong words in voice recognition by comparing with the correct text instructions, build a voice recognition supplementary model for pilots, and enhance the adaptability to their voice characteristics. At the same time, we generate a voice training recommendation report, which proposes training suggestions including improving microphone usage habits, improving voice clarity, expanding flight vocabulary, and correcting accents.

[0042] In a preferred embodiment, the processing module 130 sets reliability levels for different voice commands, and voice commands of different reliability levels have different recognition accuracy requirements. When an important flight instruction does not reach the corresponding reliability level, the processing module 130 converts it into manual confirmation input or multimodal confirmation input.

[0043] Specifically, according to the influence of voice commands, three reliability levels are set: critical commands, general commands, and non-critical commands. The recognition accuracy of critical commands is required to be greater than or equal to 99%, the recognition accuracy of general commands is required to be greater than or equal to 95%, and the recognition accuracy of non-critical commands is required to be greater than or equal to 90%. For example, commands that have a significant impact on flight control, such as commands to change flight altitude, are critical commands, and commands such as inquiring about weather conditions are non-critical commands. The processing module 130 determines the confidence of the voice recognition result. When the confidence of important flight commands, i.e., critical commands, does not reach the corresponding 99% accuracy, multimodal confirmation or manual confirmation is triggered. Multimodal confirmation includes voice repetition, key or touch screen confirmation, and the pilot needs to confirm the command in more than two ways. For general commands, the system requires repeated confirmation of a single mode, and corrects or prompts errors in non-critical commands without confirmation. It can be understood that the reliability level, accuracy requirement, and confirmation mode of the command can be configured and adjusted in real time. At the same time, the number of times multimodal confirmation is used is recorded, which can be used as an evaluation indicator of voice interaction quality.

[0044] In a preferred embodiment, the analysis module 150 is also used to obtain the driver's assessment level and adjust the difficulty of the scene training including voice interaction according to the assessment level. When the driver's assessment level is low, the voice interaction is set to non-critical instructions and dialogues.

[0045] Specifically, pilots with lower assessment levels are not proficient in voice response and cannot accurately identify and execute key instructions. In training scenarios, voice interaction focuses on non-critical instructions and dialogues, cultivates voice communication skills, and gradually improves levels. Non-critical instructions refer to instructions that will not have a direct or significant impact on the flight after execution, such as information query, environmental control, system setting adjustment, etc. Such instruction errors can be corrected or prompted, and do not require strict multimodal confirmation. Dialogue interaction refers to natural voice dialogue that is not a control instruction, such as route query, weather inquiry, crew communication, etc. This is a non-critical voice interaction that can enhance the scene immersion, but does not involve flight control. Through this, targeted training optimization and evaluation analysis can be achieved.

[0046] The implementation principle of the embodiment of the present application is that the present application constructs a data processing system including an acquisition module 110, a storage module 120, a processing module 130, a display module 140 and an analysis module 150 to collect, store, process, display and analyze the flight status data and driving operation data during the pilot's flight simulation process, thereby obtaining flight playback images, flight status parameters and flight quality parameters, evaluating and analyzing the pilot's operating skills, and then guiding the pilot's operating skills to improve the safety of future flight driving.

[0047] In addition, the pilot's voice commands and feedback are received through the auxiliary module 160 and converted into text commands, and the matching degree between the text commands and the driving operation data is analyzed through the processing module 130, thereby realizing voice interaction, solving the problem of insufficient playback authenticity, and examining the pilot's flying skills in voice interaction at the same time.

[0048] In the second aspect, the present application provides a data processing method for aircraft driving parameter simulation playback. The data processing method for aircraft driving parameter simulation playback of the present application is described below in conjunction with the above-mentioned data processing method system for aircraft driving parameter simulation playback. Figure 2 , Figure 2 It is an exemplary flow chart of a data processing method for aircraft driving parameter simulation playback in an embodiment of the present application.

[0049] A data processing method for aircraft driving parameter simulation playback comprises the following steps: S210: collecting flight status data and driving operation data generated during the flight simulation process.

[0050] S220, storing the collected flight status data and driving operation data, and organizing them in chronological order and parameter categories.

[0051] S230, extracting and calculating the flight status data and driving operation data stored in the organization to obtain aircraft status parameters and flight quality parameters.

[0052] S240: Perform three-dimensional visual dynamic playback based on the processed flight state parameters and flight quality parameters to display the flight motion state and driving operation process.

[0053] S250: Evaluate and analyze the pilot's operating skills based on the playback images, the processed flight status parameters, and the flight quality parameters.

[0054] Optionally, in some embodiments, the flight status data includes aircraft speed parameters, aircraft altitude parameters, aircraft pitch angle parameters, aircraft roll angle parameters and aircraft heading angle parameters; the driving operation data includes elevator position parameters, rudder position parameters, throttle position parameters, flap position parameters and landing gear position parameters.

[0055] Optionally, in some embodiments, the method further comprises: S260, receiving the driver's voice command and feedback, and converting them into text commands; S270: Analyze the matching degree between the text instruction and the driving operation data, and determine the voice response ability of the driver.

[0056] Optionally, in some embodiments, after step S270, the method further includes: S280: When the matching degree is lower than a threshold, a speech recognition error analysis is performed and a speech training suggestion is generated to improve the driver's speech response ability.

[0057] Optionally, in some embodiments, after step S270, the method further includes: S290. Setting reliability levels for different voice commands, wherein different reliability levels of voice commands require different recognition accuracy rates.

[0058] S300: When the important flight instruction does not reach the corresponding reliability level, convert it into manual confirmation input or multi-modal confirmation input.

[0059] Optionally, in some embodiments, after step S270, the method further includes: S310. Obtain the driver's assessment level, and adjust the difficulty of scene training including voice interaction according to the assessment level. When the driver's assessment level is low, set the voice interaction to non-critical instructions and dialogues.

[0060] In one embodiment, the present application provides an electronic device, which may be a server, and its internal structure diagram may be as follows: Figure 3 As shown. The electronic device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the electronic device is used to store data. The network interface of the electronic device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a data processing method for simulating playback of aircraft driving parameters is implemented.

[0061] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the electronic device to which the scheme of the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0062] In one embodiment, an electronic device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0063] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the above-mentioned computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0064] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A data processing system for aircraft driving parameter simulation playback, characterized in that: include: The acquisition module is used to collect the flight status data and driving operation data generated during the flight simulation; A storage module, used to store the flight status data and driving operation data collected by the collection module, and organize them in time sequence and parameter category; A processing module, used for extracting and calculating the flight status data and driving operation data organized and stored by the storage module to obtain aircraft status parameters and flight quality parameters; A display module is used to perform three-dimensional visual dynamic playback according to the flight state parameters and flight quality parameters processed by the processing module to display the flight motion state and the driving operation process; The analysis module is used to evaluate and analyze the pilot's operating skills based on the playback images of the display module, the flight status parameters and the flight quality parameters processed by the processing module.

2. The data processing system for aircraft driving parameter simulation playback according to claim 1, characterized in that: The flight status data includes aircraft speed parameters, aircraft altitude parameters, aircraft pitch angle parameters, aircraft roll angle parameters and aircraft heading angle parameters; the driving operation data includes elevator position parameters, rudder position parameters, throttle position parameters, flap position parameters and landing gear position parameters.

3. The data processing system for aircraft driving parameter simulation playback according to claim 1, characterized in that: Also includes: An auxiliary module, used for receiving the driver's voice instructions and feedback, converting them into text instructions, and transmitting them to the processing module; The processing module is also used to analyze the matching degree between the text instruction and the driving operation data, and judge the voice response ability of the driver.

4. The data processing system for aircraft driving parameter simulation playback according to claim 3 is characterized in that: When the matching degree is lower than a threshold, the auxiliary module performs speech recognition error analysis and generates speech training suggestions to improve the driver's speech response ability.

5. The data processing system for aircraft driving parameter simulation playback according to claim 3 is characterized in that: The processing module sets reliability levels for different voice commands, and voice commands with different reliability levels require different recognition accuracy rates; When the important flight instruction does not reach the corresponding reliability level, the processing module converts it into manual confirmation input or multi-modal confirmation input.

6. The data processing system for aircraft driving parameter simulation playback according to claim 3, characterized in that: The analysis module is also used to obtain the driver's assessment level and adjust the difficulty of scene training including voice interaction according to the assessment level. When the driver's assessment level is low, the voice interaction is set to non-critical instructions and dialogues.

7. A data processing method for aircraft driving parameter simulation playback, characterized in that: The steps include: Collect flight status data and driving operation data generated during flight simulation; Store the collected flight status data and driving operation data and organize them in chronological order and parameter categories; Extract and calculate the flight status data and driving operation data stored in the organization to obtain aircraft status parameters and flight quality parameters; According to the processed flight status parameters and flight quality parameters, three-dimensional visual dynamic playback is performed to display the flight motion status and driving operation process; The pilot's operating skills are evaluated and analyzed based on the playback images, processed flight status parameters and flight quality parameters.

8. The data processing method for aircraft driving parameter simulation playback according to claim 7 is characterized in that: The flight status data includes aircraft speed parameters, aircraft altitude parameters, aircraft pitch angle parameters, aircraft roll angle parameters and aircraft heading angle parameters; the driving operation data includes elevator position parameters, rudder position parameters, throttle position parameters, flap position parameters and landing gear position parameters.

9. The data processing method for aircraft driving parameter simulation playback according to claim 7, characterized in that: The method further comprises: Receive the driver's voice commands and feedback and convert them into text commands; The matching degree between the text instruction and the driving operation data is analyzed to determine the voice response ability of the driver.

10. The data processing method for aircraft driving parameter simulation playback according to claim 9, characterized in that: After analyzing the matching degree between the text instruction and the driving operation data, the method further includes: When the matching degree is lower than a threshold, a speech recognition error analysis is performed and a speech training suggestion is generated to improve the driver's speech response ability.

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