Aircraft digital twin situation deduction and risk assessment method in complex meteorological environment

Abstract

The invention provides an aircraft digital twinning situation deduction and risk assessment method in a complex meteorological environment, and belongs to the technical field of data processing, the aircraft digital twinning situation deduction and risk assessment method in the complex meteorological environment comprises the following steps: collecting and processing weather data covering parameters such as wind direction and wind speed; obtaining aircraft performance parameters and building a database; and inputting and analyzing the flight plan. By establishing a three-dimensional deduction model including dynamics, weather influence and environment models, aircraft situations under different weathers are deduced, and flight safety, performance and task risks are evaluated. The method has the advantages that weather factors are comprehensively and accurately analyzed, and influences are quantified through data acquisition and processing and a meteorological model; the system is suitable for various aircrafts, can integrate navigation and control systems, and realizes remote monitoring management; risk assessment is scientific and reliable, multiple factors are integrated, powerful support is provided for flight decision making, and aircraft safety and task success rate in complex weather are effectively improved.

Description

Technical Field

[0001] The present invention belongs to the field of data processing technology, and specifically relates to a method for potential deduction and risk assessment of digital twins of aircraft in complex meteorological environments. Background Art

[0002] For a long time, in flight demonstrations of traditional aircraft, flight trajectories have been drawn using two- and three-dimensional grids. This expression method is not only not intuitive enough, but also limits the real-time constraints on the aircraft and is out of line with the requirements of modern flight mission systems.

[0003] With the continuous advancement of aerospace technology, aircraft flight safety is receiving increasing attention. Weather conditions are a key factor affecting aircraft flight safety. Severe weather conditions such as strong winds, heavy rain, and lightning can adversely affect aircraft performance and flight trajectory, and even lead to flight accidents. Therefore, accurately predicting weather impacts on aircraft and conducting situational analysis and risk assessments are crucial for ensuring aircraft flight safety.

[0004] Currently, several methods exist for situational analysis and risk assessment of aircraft. However, most of these methods fail to fully consider the impact of weather factors or simply use weather data as input parameters, lacking in-depth analysis and modeling of weather impacts. Furthermore, existing methods have limitations in situational analysis and risk assessment in three-dimensional space, making them difficult to meet the needs of practical applications. Summary of the Invention

[0005] The purpose of this invention is to provide a method for digital twin situation deduction and risk assessment of aircraft in complex meteorological environments, aiming to solve the problem that the existing aircraft situation deduction and risk assessment technology has deficiencies in considering weather factors, making it difficult to accurately predict the situation and risks of aircraft in complex weather conditions, and unable to meet the growing demand for flight safety.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A method for analyzing the potential of digital twins of aircraft in complex meteorological environments and conducting risk assessment includes the following steps:

[0008] S1. Collect real-time weather data using meteorological equipment integrated with novel quantum sensor technology. This quantum sensor technology can sense wind direction with picometer-level accuracy, wind speed with sub-micron-per-second accuracy, temperature with millikelvin accuracy, air pressure with micropascal accuracy, and humidity with part-per-million accuracy in complex meteorological environments. The collected data is pre-processed to remove noise and outliers, and analyzed and predicted using meteorological models based on quantum computing principles.

[0009] S2. Collect the weight and dimensions of the aircraft. By obtaining detailed design parameters of the specific aircraft model and combining them with actual flight history data, use deep learning algorithms to optimize and calibrate the aircraft's weight, dimensions and other performance parameters, and establish a database containing the optimized and calibrated parameters.

[0010] S3. Input the flight plan of the aircraft and convert it into a flight trajectory;

[0011] S4. Build a three-dimensional aircraft situation deduction model based on the collected weather data, aircraft parameters, and flight plan. This model includes an aircraft dynamics model for describing the aircraft's motion state and forces, a weather impact model based on quantum entanglement theory for describing the impact of weather conditions on the aircraft, and a flight environment model for describing the aircraft's flight environment.

[0012] S5. Use the established three-dimensional aircraft situation deduction model to deduce the flight situation of the aircraft under different weather conditions;

[0013] S6. Based on the deduction results, a dynamic weight allocation mechanism is used to adjust the weights of the evaluation indicators in real time according to different meteorological conditions and aircraft status based on the principle of quantum state superposition, and the flight safety risk, flight performance risk, and flight mission risk of the aircraft under different weather conditions are evaluated;

[0014] S7. Output the situation simulation results and risk assessment report of the aircraft under different weather conditions. When the risk assessment report results exceed the set threshold, an early warning signal is issued through an audible and visual alarm or SMS notification that integrates quantum encryption communication technology.

[0015] As a preferred solution of the present invention, in the S1 step, when real-time weather data is collected using meteorological equipment, the data can be transmitted to the data processing module in real time through a quantum communication link to ensure the security and accuracy of data transmission. The weather data includes wind direction angle parameters, wind speed parameters, temperature parameters, air pressure parameters, and humidity parameters.

[0016] As a preferred solution of the present invention, in the step S2, when optimizing and calibrating the aircraft performance parameters, blockchain technology is used to fully record and trace the source and processing process of the data to ensure the authenticity and reliability of the data.

[0017] As a preferred solution of the present invention, in the S4 step, the weather impact model uses quantum entanglement to accurately describe the complex relationship between meteorological factors and aircraft status, thereby improving the accuracy of the model in predicting the aircraft status in a complex meteorological environment. The three-dimensional aircraft situation deduction model includes an aircraft dynamics model, a weather impact model and a flight environment model. The aircraft dynamics model is used to describe the motion state and force conditions of the aircraft; the weather impact model is used to describe the impact of weather conditions on the aircraft; and the flight environment model is used to describe the flight environment in which the aircraft is located.

[0018] As a preferred solution of the present invention, in step S6, the dynamic weight allocation mechanism uses a quantum annealing algorithm to quickly search for the optimal weight combination when adjusting the evaluation indicator weights, thereby improving the efficiency and accuracy of risk assessment. The risk assessment includes flight safety risk assessment, flight performance risk assessment, and flight mission risk assessment. The flight safety risk assessment is calculated as follows:

[0019] R 安全 =P 故障 ×C 影响 ,

[0020] Where R 安全 For flight safety risks, P 故障 is the probability of aircraft component failure, C 影响 is the impact coefficient of the fault on flight safety.

[0021] As a preferred solution of the present invention, the risk assessment includes a flight safety risk assessment for an aircraft under different weather conditions, a flight performance risk assessment for an aircraft under different weather conditions, and a flight mission risk assessment for an aircraft under different weather conditions. During the assessment process, quantum machine learning algorithms are used to deeply mine and analyze historical data and real-time data, providing a more comprehensive and accurate basis for risk assessment.

[0022] As a preferred solution of the present invention, in the step S7, when the risk assessment report result exceeds the set threshold, the warning signal issued is transmitted through quantum encryption communication technology to prevent the warning information from being stolen or tampered with.

[0023] As a preferred solution of the present invention, the aircraft is one of an airplane, a helicopter or a drone, and when conducting digital twin potential deduction and risk assessment, quantum simulation technology is used to simulate the operating state of the aircraft in a complex meteorological environment, providing a more realistic and reliable reference for risk assessment.

[0024] As a preferred solution of the present invention, the aircraft digital twin potential deduction and risk assessment method is integrated with the aircraft's navigation and control systems, and quantum computing technology is used to provide real-time decision support for the aircraft's safe flight. This method also achieves remote monitoring and management through the Internet integrated with quantum satellite communication technology.

[0025] As a preferred solution of the present invention, quantum error correction code technology is used to protect data during the entire digital twin potential deduction and risk assessment process to ensure the integrity and accuracy of the data and improve the reliability of the entire assessment method.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1. This invention enables comprehensive and accurate weather factor analysis and detailed data collection and processing. It collects a variety of weather data, including wind direction, wind speed, temperature, air pressure, and humidity. It also pre-processes the data to remove noise and outliers, improving data accuracy and reliability. It uses meteorological models with specific calculation methods to conduct in-depth analysis and quantification of weather factors. These formulas can accurately calculate the impact of weather factors on aircraft stress and flight performance, providing a solid foundation for subsequent situational analysis and risk assessment.

[0028] 2. This invention is applicable to a variety of aircraft types, including airplanes, helicopters, and drones. Whether large civil airliners or small drones, this technology can be used to conduct pre-flight risk assessments and in-flight situational analysis, thereby improving flight safety. This makes the technology promising for broad application, meeting the flight safety requirements of different types of aircraft in complex weather conditions. It can be integrated with aircraft systems, such as navigation and control systems, to enable remote monitoring and management via the internet or satellite communications. When risk assessment results exceed safety thresholds, timely measures such as adjusting flight plans, changing altitude or speed can be taken to ensure flight safety.

[0029] 3. The present invention adopts a reasonable calculation formula and comprehensively considers multiple factors to make the evaluation results more scientific and reliable. The flight performance risk assessment considers the impact of weather conditions on aircraft performance, such as the impact of wind speed on aircraft speed and the impact of temperature on engine performance. The flight mission risk assessment comprehensively considers the flight plan and actual flight conditions to evaluate whether the aircraft can complete the flight according to the predetermined mission requirements. These risk assessments can comprehensively evaluate the risk situation of the aircraft under different weather conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0031] Figure 1 It is a flowchart of the present invention. DETAILED DESCRIPTION

[0032] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0033] Example 1

[0034] See also Figure 1 , the present invention provides the following technical solutions:

[0035] S1. Collect real-time weather data using meteorological equipment integrated with novel quantum sensor technology. This quantum sensor technology can sense wind direction with picometer-level accuracy, wind speed with sub-micron-per-second accuracy, temperature with millikelvin accuracy, air pressure with micropascal accuracy, and humidity with part-per-million accuracy in complex meteorological environments. The collected data is pre-processed to remove noise and outliers, and analyzed and predicted using meteorological models based on quantum computing principles.

[0036] S2. Collect the weight and dimensions of the aircraft. By obtaining detailed design parameters of the specific aircraft model and combining them with actual flight history data, use deep learning algorithms to optimize and calibrate the aircraft's weight, dimensions and other performance parameters, and establish a database containing the optimized and calibrated parameters.

[0037] S3. Input the flight plan of the aircraft and convert it into a flight trajectory;

[0038] S4. Build a three-dimensional aircraft situation deduction model based on the collected weather data, aircraft parameters, and flight plan. This model includes an aircraft dynamics model for describing the aircraft's motion state and forces, a weather impact model based on quantum entanglement theory for describing the impact of weather conditions on the aircraft, and a flight environment model for describing the aircraft's flight environment.

[0039] S5. Use the established three-dimensional aircraft situation deduction model to deduce the flight situation of the aircraft under different weather conditions;

[0040] S6. Based on the deduction results, a dynamic weight allocation mechanism is used to adjust the weights of the evaluation indicators in real time according to different meteorological conditions and aircraft status based on the principle of quantum state superposition, and the flight safety risk, flight performance risk, and flight mission risk of the aircraft under different weather conditions are evaluated;

[0041] S7. Output the situation simulation results and risk assessment report of the aircraft under different weather conditions. When the risk assessment report results exceed the set threshold, an early warning signal is issued through an audible and visual alarm or SMS notification that integrates quantum encryption communication technology.

[0042] Weather data collection and processing

[0043] Collection method: Use meteorological equipment to obtain real-time weather data;

[0044] Data processing: Pre-process the collected data, including removing noise and outliers, and then use meteorological models for analysis and prediction; weather data includes parameters such as wind direction, wind speed, temperature, air pressure, and humidity;

[0045] Aircraft performance parameter acquisition

[0046] Parameter collection: Collect the aircraft's weight, dimensions, aerodynamic characteristics, and engine performance parameters and build a database; these parameters are crucial for subsequent model building and analysis;

[0047] Flight plan input and analysis

[0048] Input content: Enter the flight plan of the aircraft, such as take-off location, destination, flight altitude, speed, etc.

[0049] Processing results: Convert the flight plan into a flight trajectory, providing a basis for subsequent situational deduction;

[0050] Establish a three-dimensional aircraft situation simulation model

[0051] Model composition: including aircraft dynamics model, weather impact model and flight environment model; aircraft dynamics model describes the motion state and force conditions of the aircraft; weather impact model describes the impact of weather conditions on the aircraft; flight environment model presents the environment in which the aircraft is located;

[0052] Situational simulation

[0053] Simulation Basis: Based on the established three-dimensional aircraft situation simulation model, combined with weather data, aircraft parameters and flight plans, the flight situation of the aircraft under different weather conditions is simulated;

[0054] risk assessment

[0055] Assessment Types: These include flight safety risk assessment, flight performance risk assessment, and flight mission risk assessment; each assessing the aircraft's safety, performance, and mission completion under different weather conditions.

[0056] Output

[0057] Output content: Output the situation simulation results and risk assessment reports of the aircraft under different weather conditions. These results can be presented in the form of charts, text, etc. to provide support for flight decisions.

[0058] Specifically, in step S1, when meteorological equipment is used to collect real-time weather data, the data can be transmitted to the data processing module in real time through the quantum communication link to ensure the security and accuracy of data transmission. The weather data includes wind direction angle parameters, wind speed parameters, temperature parameters, air pressure parameters, and humidity parameters.

[0059] Specifically, in step S2, when optimizing and calibrating aircraft performance parameters, blockchain technology is used to record and trace the source and processing of data throughout the entire process to ensure the authenticity and reliability of the data.

[0060] Specifically, the meteorological model includes calculations of the effect of wind direction on the lateral force of the aircraft and the effect of temperature on air density, as follows:

[0061] F 横向 =C 横向 ×ρ×V 2 ×A×sin(θ),

[0062] Where: F 横向 is the lateral force, C 横向 is the lateral force coefficient, ρ is the air density, V is the aircraft speed, A is the aircraft frontal area, and θ is the wind direction angle;

[0063]

[0064] Where: ρ is the air density, P is the air pressure, R is the gas constant, and T is the air temperature.

[0065] Specifically, in step S4, the weather impact model uses quantum entanglement to accurately describe the complex relationship between meteorological factors and aircraft status, thereby improving the accuracy of the model's prediction of the aircraft's status in complex meteorological environments. The three-dimensional aircraft situation deduction model includes an aircraft dynamics model, a weather impact model, and a flight environment model. The aircraft dynamics model is used to describe the aircraft's motion state and force conditions; the weather impact model is used to describe the impact of weather conditions on the aircraft; and the flight environment model is used to describe the flight environment in which the aircraft is located.

[0066] Specifically, in step S6, the dynamic weight allocation mechanism uses a quantum annealing algorithm to quickly search for the optimal weight combination when adjusting the evaluation indicator weights, thereby improving the efficiency and accuracy of risk assessment. The risk assessment includes flight safety risk assessment, flight performance risk assessment, and flight mission risk assessment. The flight safety risk assessment is calculated as follows:

[0067] R 安全 =P 故障 ×C 影响 ,

[0068] Where R 安全 For flight safety risks, P 故障 is the probability of aircraft component failure, C 影响 is the impact coefficient of the fault on flight safety.

[0069] Specifically, the risk assessment includes a flight safety risk assessment for aircraft under different weather conditions, a flight performance risk assessment for aircraft under different weather conditions, and a flight mission risk assessment for aircraft under different weather conditions. During the assessment process, quantum machine learning algorithms are used to deeply mine and analyze historical data and real-time data to provide a more comprehensive and accurate basis for risk assessment.

[0070] Specifically, in step S7, when the risk assessment report result exceeds the set threshold, the warning signal issued is transmitted through quantum encryption communication technology to prevent the warning information from being stolen or tampered with.

[0071] Specifically, the aircraft is one of an airplane, a helicopter or a drone, and when conducting digital twin potential deduction and risk assessment, quantum simulation technology is used to simulate the operating status of the aircraft in a complex meteorological environment, providing a more realistic and reliable reference for risk assessment.

[0072] Specifically, the digital twin potential simulation and risk assessment method of the aircraft is integrated with the aircraft's navigation and control systems, and quantum computing technology is used to provide real-time decision support for the aircraft's safe flight. This method also achieves remote monitoring and management through the Internet integrated with quantum satellite communication technology.

[0073] Specifically, during the entire digital twin potential deduction and risk assessment process, quantum error correction code technology is used to protect data, ensure the integrity and accuracy of the data, and improve the reliability of the entire assessment method. The early warning signal can be in the form of sound and light alarms and SMS notifications.

[0074] In a specific embodiment of the present invention, meteorological equipment such as meteorological satellites and meteorological radars are used to collect real-time weather data, including wind direction angle parameters, wind speed parameters, temperature parameters, air pressure parameters, and humidity parameters. These data are the basis for subsequent analysis and prediction. The collected data are processed to remove noise and outliers to improve the accuracy and reliability of the data. For example, high-frequency noise in meteorological data is removed by filtering algorithms, and obviously unreasonable outliers are identified and eliminated to ensure the quality of data input into subsequent models. Meteorological model analysis and prediction: A meteorological model containing a specific calculation method is used for analysis and prediction, wherein the formula Calculate the effect of temperature on air density. Accurate calculation of air density is crucial for analyzing the force of the aircraft. At the same time, through the formula F 横向 =C 横向 ×ρ×V 2 ×A×sin(θ) calculates the effect of wind direction on the lateral force of the aircraft, which helps to accurately understand the force state of the aircraft in the wind and provides key data support for subsequent situation deduction and risk assessment;

[0075] Acquisition of aircraft performance parameters. Parameter collection scope: Collecting aircraft weight, dimensions, aerodynamic characteristics, and engine performance parameters and establishing a database. For example, aircraft weight affects its flight inertia and fuel consumption; dimensional parameters such as wing area are related to the calculation of lift and drag; aerodynamic characteristics, including the wing shape coefficient, determine the forces acting on the aircraft in the air; engine performance parameters such as thrust and fuel efficiency directly affect the aircraft's flight performance. Establishing a database facilitates the management and query of aircraft performance parameters, providing accurate aircraft characteristic data for the subsequent establishment of a three-dimensional aircraft situation deduction model.

[0076] Flight plan input and analysis: Input content: Input the aircraft's flight plan, including takeoff location, destination, flight altitude, speed, and other information. This information determines the aircraft's flight path and expected flight status. Converting the flight plan into a flight trajectory provides a reference path for deriving the aircraft's flight status in three-dimensional space, facilitating subsequent analysis of deviations between the aircraft's actual flight trajectory and the expected trajectory in combination with weather factors.

[0077] A three-dimensional aircraft situation simulation model is established, including an aircraft dynamics model, a weather impact model, and a flight environment model. The aircraft dynamics model describes the aircraft's motion state and force conditions, including factors such as the aircraft's own weight, engine thrust, and aerodynamic forces. Through precise mechanical analysis, it can simulate the aircraft's flight attitude and trajectory changes under different conditions. The weather impact model is used to describe the impact of weather conditions on the aircraft. Based on collected and processed weather data such as wind direction, wind speed, temperature, air pressure, and humidity, it accurately calculates the impact of weather factors on the aircraft's forces and flight performance, quantifies weather factors, and integrates them into the aircraft's flight analysis. The flight environment model is used to describe the aircraft's flight environment, including factors such as the airspace's terrain and electromagnetic environment. For example, it considers the impact of mountainous terrain on airflow and the impact of electromagnetic interference on the aircraft's communication and navigation systems. By integrating these three models, a comprehensive and accurate simulation of the aircraft's three-dimensional flight situation under the influence of weather can be performed within a comprehensive framework.

[0078] Situational simulation uses the established three-dimensional aircraft situational simulation model, combined with collected weather data, aircraft parameters, and flight plans, to simulate the aircraft's flight situation under different weather conditions. For example, considering the changes in the aircraft's flight trajectory under different wind directions and wind speeds, as well as the impact of temperature and air pressure changes on aircraft performance, the aircraft's actual flight attitude, speed, altitude, and other parameters in various weather scenarios are obtained. The simulation results can be used to assess whether the aircraft can complete the flight mission as expected under different weather conditions and predict possible flight risks.

[0079] Risk assessment includes flight safety risk assessment, flight performance risk assessment and flight mission risk assessment. Flight safety risk assessment is performed by formula R 安全 =P 故障 ×C 影响 The calculation takes into account the probability of failure of aircraft components and the impact coefficient of failure on flight safety. For example, if the probability of failure of aircraft engine components is high and the failure has a serious impact on flight safety, the flight safety risk will increase accordingly. The flight performance risk assessment considers the impact of weather conditions on aircraft performance, such as the impact of wind speed on aircraft speed and the impact of temperature on engine performance, and evaluates whether the aircraft can meet flight performance requirements under different weather conditions. The flight mission risk assessment comprehensively considers the flight plan and actual flight conditions, and evaluates whether the aircraft can complete the flight according to the predetermined mission requirements, such as whether it can arrive at the destination on time and whether it can fly within the specified altitude and speed range. By evaluating different types of risks, the risk assessment can provide decision support for pilots and ground command personnel, helping them decide whether to adjust the flight plan, take additional safety measures, or perform maintenance and inspections on the aircraft.

[0080] Output results, output the aircraft's situational deduction results and risk assessment reports under different weather conditions. These results can be presented in the form of charts, text, etc. For example, by drawing the aircraft's flight trajectory diagram under different wind directions and wind speeds, the changes in the aircraft's flight situation can be intuitively displayed; at the same time, the assessment results of the aircraft's flight safety risks, flight performance risks and flight mission risks are detailed in the form of a text report; the output results provide decision support for pilots and ground command personnel, helping them make reasonable flight decisions and ensure the safe flight of the aircraft.

[0081] This example details the application of a digital twin aircraft situation simulation and risk assessment method to aircraft flight in complex weather environments. It demonstrates the functional role of various technical features and how they work together, providing an effective technical means for improving aircraft safety and reliability in complex weather conditions. Through accurate weather data collection and processing, comprehensive acquisition of aircraft performance parameters, rational flight plan input and analysis, precise three-dimensional aircraft situation simulation modeling, detailed situation simulation, comprehensive risk assessment, and effective output of results, this technology provides reliable decision support for safe aircraft flight.

[0082] Example 2

[0083] This embodiment 2 provides a specific implementation method for the digital twin potential deduction and risk assessment method of an aircraft in a complex meteorological environment. Taking an aircraft as an example, weather data and aircraft performance parameters are obtained at the same time. The details are as follows:

[0084] Weather data collection and processing:

[0085] Collect real-time weather data: wind direction angle is 30°, wind speed is 20m / s, temperature is 25℃, air pressure is 1013hPa, and humidity is 60%

[0086] Calculate air density: According to the formula R is 287J / (kg·K), T=25+273=298K, P=101300Pa, then

[0087] Calculate the lateral force: the aircraft's frontal area A = 10m 2 , lateral force coefficient C 横向 =0.5,

[0088] According to formula F 横向 =C 横向 ×ρ×V 2 ×A×sin(θ), then

[0089] F 横向 =0.5x1.18×20 2×10×sin(30°)=1180N;

[0090] Aircraft performance parameter acquisition: collect aircraft weight, dimensions, aerodynamic characteristics, and engine performance parameters and establish a database;

[0091] Flight plan input and parsing: input the aircraft's flight plan and convert it into a flight trajectory;

[0092] Establish a 3D aircraft situation deduction model: Based on the collected weather data, aircraft parameters, and flight plan, a 3D aircraft situation deduction model is established, including an aircraft dynamics model, a weather impact model, and a flight environment model.

[0093] Conduct situation simulation: Use the established three-dimensional aircraft situation simulation model to simulate the aircraft's flight situation under different weather conditions;

[0094] Conduct risk assessment: flight safety risk assessment, aircraft component failure probability P 故障 =0.01, the impact coefficient of the fault on flight safety C 影响 =5, according to the formula R 安全 =P 故障 ×C 影响 , then R 安全 =0.01×5=0.05;

[0095] Flight performance risk assessment and flight mission risk assessment: assessment is conducted based on simulation results and relevant parameters.

[0096] Output results: Output aircraft situation simulation results and risk assessment reports under different weather conditions;

[0097] A risk assessment model is established, comprehensively considering factors such as flight altitude, flight speed, weather conditions, and aircraft performance. Based on the situation simulation results, the risk probability faced by the aircraft at different flight stages is calculated, and the risks are classified into different levels so that pilots and ground control personnel can take corresponding measures in a timely manner. When the risk assessment result exceeds the set threshold, an early warning signal is issued to remind pilots and ground control personnel and provide decision support suggestions, such as adjusting flight altitude, changing flight speed, changing route, etc., to reduce flight risks.

[0098] Example 3

[0099] This implementation 3 provides a specific implementation method for the digital twin potential deduction and risk assessment of aircraft in a complex meteorological environment. Taking a helicopter as an example, weather data and aircraft performance parameters are obtained simultaneously. The details are as follows:

[0100] Weather data collection and processing:

[0101] Collect real-time weather data: wind direction angle is 120°, wind speed is 15m / s, temperature is 15℃, air pressure is 1000hPa, and humidity is 50%

[0102] Calculate air density: According to the formula R is 287J / (kg·K), T=15+273=288K, P=100000Pa, then

[0103] Calculate the lateral force: the aircraft's frontal area A = 8m 2 , lateral force coefficient C 横向 =0.4,

[0104] According to formula F 横向 =C 横向 ×ρ×V 2 ×A×sin(θ), then

[0105] F 横向 =0.4x1.22×15 2 ×8×sin(120°)=883.7N;

[0106] Aircraft performance parameter acquisition: Collect helicopter weight, dimensions, aerodynamic characteristics, and engine performance parameters and establish a database;

[0107] Flight plan input and parsing: Input the helicopter's flight plan and convert it into a flight trajectory;

[0108] Establish a 3D aircraft situation deduction model: Based on the collected weather data, aircraft parameters, and flight plan, a 3D aircraft situation deduction model is established, including an aircraft dynamics model, a weather impact model, and a flight environment model.

[0109] Conduct situation simulation: Use the established three-dimensional aircraft situation simulation model to simulate the helicopter's flight situation under different weather conditions;

[0110] Conduct risk assessment: flight safety risk assessment, aircraft component failure probability P 故障 =0.02, the impact coefficient of the fault on flight safety C 影响 =4, according to the formula R 安全 =P 故障 ×C 影响 , then R 安全 =0.02×4=0.08;

[0111] Flight performance risk assessment and flight mission risk assessment: assessment is conducted based on simulation results and relevant parameters.

[0112] Output results: Output helicopter situation simulation results and risk assessment reports under different weather conditions;

[0113] A risk assessment model is established, comprehensively considering factors such as flight altitude, flight speed, weather conditions, and aircraft performance. Based on the situation simulation results, the risk probability faced by the aircraft at different flight stages is calculated, and the risks are classified into different levels so that pilots and ground control personnel can take corresponding measures in a timely manner. When the risk assessment result exceeds the set threshold, an early warning signal is issued to remind pilots and ground control personnel and provide decision support suggestions, such as adjusting flight altitude, changing flight speed, changing route, etc., to reduce flight risks.

[0114] Example 4

[0115] This embodiment 4 provides a specific implementation method for the digital twin potential deduction and risk assessment method of an aircraft in a complex meteorological environment. Taking a drone as an example, weather data and aircraft performance parameters are obtained at the same time. The details are as follows:

[0116] Weather data collection and processing:

[0117] Collect real-time weather data: wind direction angle is 60°, wind speed is 10m / s, temperature is 20℃, air pressure is 950hPa, and humidity is 40%

[0118] Calculate air density: According to the formula R is 287J / (kg·K), T=20+273=293K, P=95000Pa, then

[0119] Calculate the lateral force: the aircraft's frontal area A = 3m 2 , lateral force coefficient C 横向 =0.3,

[0120] According to formula F 横向 =C 横向 ×ρ×V 2 ×A×sin(θ), then

[0121] F 横向 =0.3x1.14×10 2 ×3×sin(60°)=91.4N;

[0122] Aircraft performance parameter acquisition: collect the weight, size, aerodynamic characteristics and engine performance parameters of the UAV and establish a database;

[0123] Flight plan input and parsing: Input the UAV's flight plan and convert it into a flight trajectory;

[0124] Establish a 3D aircraft situation deduction model: Based on the collected weather data, aircraft parameters, and flight plan, a 3D aircraft situation deduction model is established, including an aircraft dynamics model, a weather impact model, and a flight environment model.

[0125] Conduct situation simulation: Use the established three-dimensional aircraft situation simulation model to simulate the flight situation of the UAV under different weather conditions;

[0126] Conduct risk assessment: flight safety risk assessment, aircraft component failure probability P 故障 =0.03, the impact coefficient of the fault on flight safety C 影响 =3, according to the formula R 安全 =P 故障 ×C 影响 , then R 安全 =0.03×3=0.09;

[0127] Flight performance risk assessment and flight mission risk assessment: assessment is conducted based on simulation results and relevant parameters.

[0128] Output results: Output the situation simulation results and risk assessment reports of UAVs under different weather conditions;

[0129] A risk assessment model is established, comprehensively considering factors such as flight altitude, flight speed, weather conditions, and aircraft performance. Based on the situation simulation results, the risk probability faced by the aircraft at different flight stages is calculated, and the risks are classified into different levels so that pilots and ground control personnel can take corresponding measures in a timely manner. When the risk assessment result exceeds the set threshold, an early warning signal is issued to remind pilots and ground control personnel and provide decision support suggestions, such as adjusting flight altitude, changing flight speed, changing route, etc., to reduce flight risks.

[0130] The technology in the present invention breaks through the limitation of traditional aircraft situation deduction and risk assessment that does not take weather factors into consideration; it not only collects a variety of weather data such as wind direction, wind speed, temperature, air pressure and humidity, but also uses special meteorological models (such as formulas for calculating the influence of wind direction on lateral force and the influence of temperature on air density) to conduct in-depth analysis and quantification of weather factors, providing a solid foundation for accurate situation deduction and risk assessment; different from the traditional two-dimensional and three-dimensional grid flight trajectory drawing method, a three-dimensional aircraft situation deduction model is established that includes an aircraft dynamics model, a weather impact model and a flight environment model; it can comprehensively and accurately simulate the aircraft's motion state, force conditions and flight trajectory changes under the influence of weather in three-dimensional space, which is more in line with the needs of modern flight mission systems; it is suitable for various aircraft types such as airplanes, helicopters or drones, and has broad application prospects; whether it is a large civil airliner or a small drone, this technology can be used for pre-flight risk assessment and situation deduction during flight to improve flight safety; it can be integrated with the aircraft's navigation system and control system, and remote control can be achieved through the Internet, satellite communications, etc. Monitoring and management; It can provide pilots and ground control personnel with real-time situation simulation results and risk assessment reports (including flight safety risk, flight performance risk and flight mission risk assessment) of aircraft under different weather conditions, presented in the form of charts, text, etc., to provide strong support for flight decision-making; for example, when the risk assessment results exceed the safety threshold, timely measures such as adjusting the flight plan, changing the flight altitude or speed can be taken to ensure flight safety; pre-processing is performed during the weather data collection process to remove noise and outliers, thereby improving data accuracy and reliability; at the same time, comprehensive collection of aircraft performance parameters and establishment of a database provide accurate input for model calculations; in risk assessment, reasonable calculation formulas (such as flight safety risk assessment formulas) are used to comprehensively consider multiple factors to make the assessment results more scientific and reliable; although the model verification process is not mentioned in detail in the document, it can be inferred that during the technology development process, the model was verified and optimized through a large amount of experimental data and actual flight cases to ensure that the model can accurately reflect the actual situation of the aircraft under the influence of weather, thereby improving the reliability and practicality of the technology;

[0131] In summary, the digital twin potential deduction and risk assessment method for aircraft in complex meteorological environments has significant advantages in innovation, practicality and reliability, and provides an effective technical solution for improving the flight safety and mission success rate of aircraft in complex weather conditions.

[0132] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for analyzing the potential of digital twins of aircraft in complex meteorological environments and for risk assessment, characterized by: The steps include: S1. Collect real-time weather data using meteorological equipment integrated with novel quantum sensor technology. This quantum sensor technology can sense wind direction with picometer-level accuracy, wind speed with sub-micron-per-second accuracy, temperature with millikelvin accuracy, air pressure with micropascal accuracy, and humidity with part-per-million accuracy in complex meteorological environments. The collected data is pre-processed to remove noise and outliers, and analyzed and predicted using meteorological models based on quantum computing principles. S2. Collect the weight and dimensions of the aircraft. By obtaining detailed design parameters of the specific aircraft model and combining them with actual flight history data, use deep learning algorithms to optimize and calibrate the aircraft's weight, dimensions and other performance parameters, and establish a database containing the optimized and calibrated parameters. S3. Input the flight plan of the aircraft and convert it into a flight trajectory; S4. Build a three-dimensional aircraft situation deduction model based on the collected weather data, aircraft parameters, and flight plan. This model includes an aircraft dynamics model for describing the aircraft's motion state and forces, a weather impact model based on quantum entanglement theory for describing the impact of weather conditions on the aircraft, and a flight environment model for describing the aircraft's flight environment. S5. Use the established three-dimensional aircraft situation deduction model to deduce the flight situation of the aircraft under different weather conditions; S6. Based on the deduction results, a dynamic weight allocation mechanism is used to adjust the weights of the evaluation indicators in real time according to different meteorological conditions and aircraft status based on the principle of quantum state superposition, and the flight safety risk, flight performance risk, and flight mission risk of the aircraft under different weather conditions are evaluated; S7. Output the situation simulation results and risk assessment report of the aircraft under different weather conditions. When the risk assessment report results exceed the set threshold, an early warning signal is issued through an audible and visual alarm or SMS notification that integrates quantum encryption communication technology.

2. The method for potential deduction and risk assessment of digital twin aircraft in complex meteorological environments according to claim 1 is characterized by: In step S1, when meteorological equipment is used to collect real-time weather data, the data can be transmitted to the data processing module in real time through the quantum communication link to ensure the security and accuracy of data transmission. The weather data includes wind direction angle parameters, wind speed parameters, temperature parameters, air pressure parameters, and humidity parameters.

3. The method for potential deduction and risk assessment of digital twin aircraft in complex meteorological environments according to claim 2 is characterized by: In step S2, when optimizing and calibrating aircraft performance parameters, blockchain technology is used to record and trace the source and processing of data throughout the entire process to ensure the authenticity and reliability of the data.

4. The method for potential deduction and risk assessment of digital twin aircraft in complex meteorological environments according to claim 3 is characterized by: In the S4 step, the weather impact model uses quantum entanglement to accurately describe the complex relationship between meteorological factors and aircraft status, thereby improving the accuracy of the model in predicting the aircraft status in complex meteorological environments. The three-dimensional aircraft situation deduction model includes an aircraft dynamics model, a weather impact model and a flight environment model. The aircraft dynamics model is used to describe the motion state and force conditions of the aircraft; the weather impact model is used to describe the impact of weather conditions on the aircraft; and the flight environment model is used to describe the flight environment in which the aircraft is located.

5. The method for potential deduction and risk assessment of digital twin aircraft in complex meteorological environments according to claim 4 is characterized by: In step S6, the dynamic weight allocation mechanism uses a quantum annealing algorithm to quickly search for the optimal weight combination when adjusting the evaluation indicator weights, thereby improving the efficiency and accuracy of risk assessment. The risk assessment includes flight safety risk assessment, flight performance risk assessment, and flight mission risk assessment. The flight safety risk assessment is calculated as follows: R 安全 =P 故障 ×C 影响 , Where R 安全 For flight safety risks, P 故障 is the probability of aircraft component failure, C 影响 is the impact coefficient of the fault on flight safety.

6. The method for potential deduction and risk assessment of digital twin aircraft in complex meteorological environments according to claim 5 is characterized by: The risk assessment includes a flight safety risk assessment for aircraft under different weather conditions, a flight performance risk assessment for aircraft under different weather conditions, and a flight mission risk assessment for aircraft under different weather conditions. During the assessment process, quantum machine learning algorithms are used to deeply mine and analyze historical data and real-time data to provide a more comprehensive and accurate basis for risk assessment.

7. The method for potential deduction and risk assessment of digital twin aircraft in complex meteorological environments according to claim 6 is characterized by: In the step S7, when the risk assessment report result exceeds the set threshold, the warning signal issued is transmitted through quantum encryption communication technology to prevent the warning information from being stolen or tampered with.

8. The method for potential deduction and risk assessment of digital twin aircraft in complex meteorological environments according to claim 7 is characterized by: The aircraft is one of an airplane, a helicopter or a drone, and when conducting digital twin potential deduction and risk assessment, quantum simulation technology is used to simulate the operating status of the aircraft in a complex meteorological environment, providing a more realistic and reliable reference for risk assessment.

9. The method for potential deduction and risk assessment of digital twin aircraft in complex meteorological environments according to claim 8, characterized in that: The digital twin potential deduction and risk assessment method of the aircraft is integrated with the aircraft's navigation and control systems, and quantum computing technology is used to provide real-time decision support for the aircraft's safe flight. This method also achieves remote monitoring and management through the Internet integrated with quantum satellite communication technology.

10. The method for potential deduction and risk assessment of digital twin aircraft in complex meteorological environments according to claim 9, characterized in that: During the entire digital twin trend deduction and risk assessment process, quantum error correction code technology is used to protect data, ensure data integrity and accuracy, and improve the reliability of the entire assessment method.

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