A vertical intelligent take-off and landing control system

Abstract

The present invention discloses a vertical intelligent take-off and landing field take-off and landing control system, which relates to the technical field of take-off and landing of take-off and landing fields, including an environmental monitoring module, an intelligent flight scheduling module, a vertical catapult take-off module, a take-off and landing field tilt control module, a fault accurate warning and processing module and a flight data in-depth analysis module: an environmental monitoring module: real-time monitoring of environmental parameters of the take-off and landing field, and automatic adjustment of monitoring strategies for extreme weather conditions; an intelligent flight scheduling module: real-time monitoring of environmental parameters and aircraft status, and intelligent planning of the take-off and landing path and time of the aircraft; in the present invention, through the real-time monitoring and strategy adjustment functions of the environmental monitoring module, the system can automatically adjust the monitoring strategy for extreme weather conditions to ensure the safety of aircraft take-off and landing, greatly improving the adaptability and survivability of helicopters in complex environments, especially in places with relatively harsh conditions such as mountainous areas and waters, and can significantly reduce take-off and landing accidents caused by weather factors.

Description

Technical Field

[0001] The present invention relates to the field of take-off and landing technology at a take-off and landing field, and specifically to a vertical intelligent take-off and landing control system at a take-off and landing field. Background Art

[0002] As an important aircraft, helicopters play an irreplaceable role in many fields such as military and civil use. However, the take-off and landing process of helicopters is often affected by many factors such as site conditions and weather conditions, which leads to certain challenges in the efficiency and safety of take-off and landing. In particular, with the increasing number of helicopters and the increasing complexity of flight missions, traditional take-off and landing methods have been unable to meet the needs of the modern aviation field. First of all, the choice of helicopter take-off and landing sites is greatly restricted. Helicopters usually require relatively flat and spacious sites for take-off and landing, but in actual applications, such site conditions are often difficult to meet. Especially in complex terrain, mountainous areas, waters and other environments, helicopter take-off and landing become more difficult.

[0003] The impact of weather conditions on helicopter takeoff and landing cannot be ignored. Extreme weather conditions, such as strong winds, heavy rains, lightning, etc., may have a serious impact on helicopter takeoff and landing, and even cause safety accidents. Therefore, how to monitor the environmental parameters of the takeoff and landing field in real time and automatically adjust the takeoff and landing strategy according to extreme weather conditions has become the key to improving the safety of helicopter takeoff and landing. The takeoff and landing process of the helicopter also needs to consider multiple factors such as the status of the aircraft, path planning, and time planning. Traditional flight scheduling methods often cannot monitor these factors in real time, resulting in the inability to guarantee takeoff and landing efficiency and safety. Therefore, the development of a system that can monitor environmental parameters and aircraft status in real time and intelligently plan takeoff and landing paths and times is of great significance to improving the efficiency and safety of helicopter takeoff and landing. Summary of the invention

[0004] The purpose of the present invention is to provide a vertical intelligent take-off and landing field take-off and landing control system to solve the problems raised in the above-mentioned background technology.

[0005] In order to solve the above technical problems, the present invention provides a vertical intelligent take-off and landing field take-off and landing control system: including an environmental monitoring module, an intelligent flight scheduling module, a vertical catapult take-off module, a take-off and landing field tilt control module, a fault accurate warning and processing module and a flight data in-depth analysis module:

[0006] Environmental monitoring module: real-time monitoring of environmental parameters of the take-off and landing field, automatic adjustment of monitoring strategies for extreme weather conditions, specifically: select appropriate sensors, such as temperature sensors, humidity sensors, air pressure sensors, wind speed and direction sensors, etc., for real-time measurement of environmental parameters of the take-off and landing field. These sensors can accurately capture changes in environmental parameters and provide basic data for subsequent monitoring and adjustment. Through the data acquisition system, the output signals of the sensors are collected in real time, and necessary conversion, amplification and filtering are performed. For digital signals, they can be directly read and analyzed; for analog signals, appropriate analog-to-digital conversion is required, and the processed environmental parameter data is transmitted through wired or wireless methods (such as Wi-Fi). i, Bluetooth, LoRa, etc.) to the monitoring center or remote server. Ensuring the real-time and stability of data is crucial for timely response to extreme weather conditions. Based on real-time environmental parameter data, the system can automatically determine whether the current weather conditions are extreme weather. Once extreme weather conditions are identified, the system can automatically adjust the monitoring strategy, such as increasing the monitoring frequency, adjusting the sensor threshold, or starting the emergency monitoring program. The collected environmental parameter data is stored and managed using database technology. Through the analysis of historical data, the monitoring strategy can be further optimized to improve the system's response to extreme weather. Taking the environmental monitoring of airport take-off and landing fields as an example, assuming that the airport is located in an area with changeable climate and frequent extreme weather, in this case, the application of environmental monitoring modules is particularly important. First, at the airport take-off and landing A series of sensors are deployed at key locations of the airport to monitor environmental parameters such as temperature, humidity, air pressure, wind speed and direction in real time. These sensors transmit data to the airport's monitoring center wirelessly. When the system detects that extreme weather conditions (such as heavy rain, strong winds, lightning, etc.) are about to occur, the monitoring center can automatically trigger emergency monitoring procedures, which include increasing the monitoring frequency of sensors to update environmental parameter data more frequently; adjusting the threshold of sensors to make them more sensitive to changes in extreme weather conditions; and starting backup power supplies and other emergency measures to ensure the continuous and stable operation of the monitoring system. In addition, the system can also combine weather forecasts and historical data to predict and warn of the occurrence of extreme weather. When extreme weather is predicted to occur, the system can adjust the monitoring strategy in advance and be prepared to respond.

[0007] Intelligent flight scheduling module: real-time monitoring of environmental parameters and aircraft status, intelligent planning of aircraft take-off and landing paths and times, and judgment of whether it is suitable for vertical catapult take-off. Take-off condition assessment includes environmental assessment and aircraft status assessment. The vertical catapult take-off module uses the catapult device to provide additional thrust to achieve rapid take-off of the aircraft, enabling the aircraft to achieve sufficient lift in a shorter period of time. In extreme weather or emergency situations, vertical catapult take-off can significantly improve take-off efficiency and safety. Among them, the catapult device usually includes a catapult, a launch hook and other components. When the aircraft is ready to take off, it will drive above the catapult and connect with the launch hook. Once the take-off command is received, the catapult The launch hook of the launcher will be released quickly, and the catapult will start working, providing a strong thrust to accelerate the aircraft forward. During this process, the aircraft engine will also run at full capacity, and work together with the thrust generated by the catapult to enable the aircraft to reach take-off speed in a short time. It should be noted that the scheduling module can use advanced prediction models, such as machine learning or deep learning algorithms, to predict future weather changes and aircraft status trends. In this way, the scheduling module can more accurately plan the take-off and landing path and time of the aircraft, and determine whether it is suitable for vertical catapult take-off. In addition to real-time monitoring of environmental parameters and aircraft status, the scheduling module can also integrate data from other sources, such as meteorological satellite data , radar data, air traffic control information, etc. to improve the accuracy of decision-making. During the flight, if the environmental parameters or the status of the aircraft change significantly, the intelligent flight scheduling module should be able to adjust the flight path, altitude or speed and other parameters in real time to ensure the safety and efficiency of the flight. The design of the ejection device needs to take into account the weight, size and take-off performance of the aircraft. The catapult needs to provide sufficient thrust, and the design of the launch hook needs to ensure that it is firmly connected to the aircraft and easy to release. During the vertical catapult take-off, safety is of vital importance. Therefore, the ejection device should be equipped with a variety of safety mechanisms, such as overload protection, emergency stop device, etc., to prevent accidents. When deciding to use a vertical ejection, Before takeoff, a takeoff performance evaluation is required, which includes evaluating the relationship between the aircraft's takeoff speed, lift, thrust, and the additional thrust provided by the ejection device to ensure that the aircraft can achieve sufficient lift in a short time and take off safely. The vertical ejection takeoff module needs to be closely integrated with the aircraft's flight control system, so that when the catapult starts working, the flight control system can adjust the aircraft's attitude and engine thrust accordingly to achieve a smooth and efficient takeoff. It should be added that the vertical ejection takeoff module provides the aircraft with powerful thrust and achieves rapid takeoff through core components such as pneumatic catapults, launch hooks, and connecting mechanisms. The vertical ejection takeoff module consists of:

[0008] Gas pressure catapult:

[0009] The pneumatic catapult is the core component of the vertical catapult takeoff module. It generates sufficient thrust to propel the aircraft forward and accelerate by precisely controlling the release of high-pressure gas. The specific implementation method is as follows:

[0010] High-pressure gas storage: A high-pressure gas storage device, such as a high-pressure gas cylinder, is provided inside the catapult to store high-pressure gas;

[0011] Gas release control: Through solenoid valves, pressure reducing valves and other control components, the release amount and speed of high-pressure gas can be accurately controlled to meet the take-off requirements of aircraft of different weights and types;

[0012] Thrust adjustability: By adjusting the gas release control parameters, the thrust can be precisely adjusted; this adjustability enables the pneumatic catapult to adapt to the take-off requirements of a variety of aircraft;

[0013] Example: A certain type of UAV uses a pneumatic catapult to take off. Before takeoff, the operator sets the corresponding gas release parameters according to the weight and type of the UAV. When the UAV drives over the catapult and connects with the launch hook, the operator issues a takeoff command, and the pneumatic catapult quickly releases high-pressure gas, generating a strong thrust to accelerate the UAV forward and achieve a quick takeoff.

[0014] Launch hook:

[0015] The launch hook is located at the front end of the catapult. Its shape and size are carefully designed to perfectly match the connection mechanism at the bottom of the aircraft. The specific implementation method is as follows:

[0016] Matching design: The shape and size of the launch hook are designed according to the connection mechanism at the bottom of the aircraft to ensure that the two can be tightly matched and locked;

[0017] Automatic locking mechanism: When the aircraft enters the catapult, the connection mechanism will automatically lock with the launch hook to form a stable connection; this automatic locking mechanism can ensure that the aircraft will not shake or fall off during the ejection process;

[0018] Example: A certain type of fixed-wing aircraft uses a vertical catapult takeoff module to take off. Before takeoff, the connecting mechanism at the bottom of the aircraft is aligned with the launch hook of the catapult and driven in. Once the connecting mechanism contacts the launch hook, the automatic locking mechanism is immediately activated to lock the two tightly together. Then, the operator issues a takeoff command, and the pneumatic catapult starts working, accelerating the aircraft forward for takeoff;

[0019] Connection mechanism:

[0020] The connecting mechanism is the bridge between the aircraft and the catapult. It is not only responsible for tightly connecting the aircraft and the launch hook, but also undertakes the important tasks of transmitting thrust and maintaining stability. The specific implementation methods are as follows:

[0021] High-strength materials: The connection mechanism is made of high-strength materials, such as carbon fiber composite materials or titanium alloys, to ensure that it has sufficient strength and durability;

[0022] Precision machining: The connection mechanism is precision machined and tested to ensure that it can closely match the connection mechanism between the launch hook and the bottom of the aircraft and smoothly transmit thrust;

[0023] Stability design: The connection mechanism is also designed with stability structures, such as shock absorbers or support frames, to ensure that the aircraft remains stable during the ejection process;

[0024] Example: A certain type of vertical take-off and landing aircraft uses a vertical catapult take-off module to take off. The bottom of the aircraft is equipped with a special connection mechanism that matches the launch hook of the catapult. Before take-off, the operator aligns the connection mechanism of the aircraft with the launch hook and drives it in to ensure that the two are tightly locked. Then, the pneumatic catapult starts working, transmitting a strong thrust to the aircraft through the connection mechanism, pushing it forward and accelerating to take off. At the same time, the stability design of the connection mechanism ensures that the aircraft remains stable during the ejection process and takes off smoothly;

[0025] It is also necessary to add that in order to ensure the safety of the vertical catapult take-off module in this system, the specific implementation methods of the various safety mechanisms are as follows:

[0026] Overload protection:

[0027] Implementation method: In the take-off and landing control system of the vertical intelligent take-off and landing field, the overload protection system monitors the thrust generated by the catapult in real time through high-precision sensors. When the thrust exceeds the preset safety threshold, the system will immediately activate the overload protection mechanism, which is usually achieved by automatically adjusting the gas release amount of the pneumatic catapult, controlling the opening and closing of the solenoid valve, or triggering the emergency disconnection device, etc., to reduce the thrust or disconnect the connection with the aircraft, thereby preventing damage to the aircraft or accidents;

[0028] Example: In a vertical intelligent take-off and landing field, when a heavy-loaded aircraft is preparing for vertical catapult takeoff, the weight of the aircraft exceeds the normal carrying capacity of the catapult, causing the thrust generated by the catapult to increase rapidly. At this time, the overload protection system responds quickly and automatically adjusts the gas release amount of the pneumatic catapult to reduce the thrust, ensuring that the aircraft takes off within a safe thrust range;

[0029] Emergency stop device:

[0030] Implementation method: The emergency stop device is usually designed as an easy-to-operate manual or automatic trigger device. In an emergency, the operator can trigger the emergency stop device by simple operations such as pressing a button or pulling a joystick. The device will immediately cut off all power sources related to the ejection, such as the supply of high-pressure gas, circuits, etc., so that the ejection process stops quickly;

[0031] Example: During a test flight at a vertical intelligent take-off and landing field, the aircraft experienced abnormal vibrations during the ejection process due to unknown reasons. To prevent possible accidents, the operator quickly triggered the emergency stop device, which immediately cut off the high-pressure gas supply and circuit related to the ejection device, stopping the ejection process before the aircraft left the ground, ensuring the safety of personnel and aircraft.

[0032] Fault detection and diagnosis system:

[0033] Implementation: The fault detection and diagnosis system integrates multiple sensors, data acquisition devices, and central processing units to monitor the operating status and various parameters of the catapult in real time. Once an abnormality or fault signal is detected, the system will immediately issue an alarm, analyze the cause of the fault through the central processing unit, and initiate corresponding emergency measures;

[0034] Example: During the long-term operation of the vertical intelligent take-off and landing field, the fault detection and diagnosis system has always been running stably in the background. One day, the system detected an abnormal signal from the solenoid valve of the catapult, which may cause unstable gas release. The system immediately issued an alarm and analyzed the cause of the solenoid valve failure through the central processor. Subsequently, the system automatically switched to the backup solenoid valve and notified the maintenance personnel to carry out maintenance, ensuring the continuous and stable operation of the take-off and landing control system;

[0035] Landing pad tilt control module: adjust the landing pad tilt angle to optimize the control performance of vertical take-off and vertical catapult take-off; adjust the landing pad tilt angle to change the take-off and landing posture of the aircraft and optimize the take-off and landing process; specifically: design the landing pad tilt mechanism, which should have sufficient strength and stability to support the weight and dynamic load of the aircraft during take-off and landing. The tilt mechanism adopts electric, hydraulic or pneumatic drive to achieve precise tilt angle adjustment. Angle sensors are installed to monitor the tilt angle of the landing pad in real time and feed the data back to the control system. Other necessary sensors are installed. Sensors, such as anemometers and temperature sensors, are used to obtain data on environmental factors that affect takeoff and landing performance. The tilt control module is integrated with the flight control system of the aircraft to ensure that the two can work together to optimize the takeoff and landing process. The optimal tilt angle is calculated through an algorithm based on the type, weight, takeoff speed and environmental factors (such as wind speed and wind direction) of the aircraft. The calculation process takes into account the dynamic characteristics of the aircraft and the physical conditions of the take-off and landing field to ensure safety and performance optimization. The control logic is written to calculate and output control instructions based on the real-time data fed back by the sensors and the preset algorithm to drive the tilt mechanism to adjust the angle;Design safety strategies, including overload protection and tilt angle limitation, to prevent the tilt mechanism from being damaged or causing danger in extreme situations, implement fault detection and alarm mechanisms, and promptly issue alarms and take corresponding countermeasures when sensors or actuators fail. It should be noted that the design of the tilt mechanism should take into account structural strength, stability and durability, and use advanced engineering analysis and simulation tools, such as finite element analysis (FEA), to ensure that the structure has sufficient rigidity and fatigue resistance when bearing the weight and dynamic loads of the aircraft. Use high-strength and lightweight materials, such as aluminum alloy or composite materials, to manufacture key components of the tilt mechanism, so that the overall weight can be reduced while maintaining structural strength, and the system efficiency can be improved. Select electric, hydraulic or pneumatic actuators with high precision and high reliability to achieve precise control of the tilt angle. The actuator should have fast response capabilities and stable output characteristics to ensure that the tilt angle can be adjusted quickly and accurately during takeoff and landing. Regularly calibrate and verify the installed angle sensors to ensure the accuracy and reliability of their measurement results. In addition, multi-sensor fusion technology can be used to integrate multiple sensors. The data of each sensor is processed comprehensively to improve the robustness and anti-interference ability of the system. When calculating the optimal tilt angle, in addition to considering the type, weight and take-off speed of the aircraft, multiple environmental factors such as wind speed, wind direction, temperature and humidity should also be considered comprehensively. The environmental parameters of the take-off and landing sites can be obtained in real time through the installed anemometer, temperature sensor and other environmental sensing devices. These data can provide real-time feedback for the control system, so that the tilt control module can be dynamically adjusted according to the current environmental conditions. When integrating with the flight control system of the aircraft, standardized interface protocols and data transmission formats should be followed, which can ensure stable and reliable communication between the two, realize real-time data sharing and accurate transmission of instructions, and introduce redundant designs in key components and systems, such as backup drives and backup power supplies. In this way, when the main system fails, it can quickly switch to the backup system to ensure the normal operation of the take-off and landing site tilt control module and the safety of the aircraft. Advanced fault prediction and health management technologies are used to monitor and evaluate the status of the tilt control module in real time. By collecting and analyzing system data, potential faults can be discovered in advance and early warnings can be issued to avoid accidents.

[0036] Accurate fault warning and processing module: monitors the operating status of the aircraft and take-off and landing field in real time, uses machine learning algorithms to conduct in-depth analysis of monitoring data, realizes accurate warning and positioning of faults, and pays attention to the status and performance of the ejection device during vertical catapult takeoff, predicts the type of fault that may occur, and provides early warning and processing;Specifically: using various sensors installed on the aircraft and take-off and landing field, real-time operation data of key components including the ejection device is collected, and the collected raw data is preprocessed, including noise removal, missing value filling, standardization, etc., to improve data quality and provide a reliable basis for subsequent analysis. Based on the preprocessed data, machine learning algorithms are used to extract characteristic parameters related to faults to reflect changes in the working status of aircraft and ejection devices, select feature combinations, and build fault warning models. Using historical fault data and real-time monitoring data, fault warning models are built. These models can be based on statistics, machine learning or deep learning models, and are selected according to specific application scenarios. The appropriate model type can be used to identify abnormal patterns, predict possible fault types, and give corresponding warning signals. The constructed fault warning model can be integrated into the real-time monitoring system to continuously monitor the status of the aircraft and the ejection device. When abnormal data is detected or an impending failure is predicted, the system automatically triggers the warning mechanism and sends warning information to relevant personnel. Based on the warning information, the system locates the specific location or component where the fault occurs, such as a mechanical component or control system of the ejection device, and provides fault handling suggestions or automatically executes preset emergency handling measures to reduce the impact of the fault on the aircraft and the take-off and landing field. Finally, the actual fault data and the performance of the warning system are continuously collected and analyzed. The early warning model is continuously optimized and improved, and the accuracy and reliability of the early warning system are continuously improved through the feedback mechanism. It should be added that the fault early warning system not only relies on a single type of sensor data, but can also enhance the accuracy of the early warning by integrating multi-source data (such as meteorological data, historical maintenance records, operation logs, etc.). Multi-source data fusion can provide a more comprehensive and multi-dimensional fault analysis perspective, which helps to identify complex fault modes that may be overlooked by a single data source. By continuously accumulating and analyzing fault cases, a knowledge base for fault pattern recognition can be established. This knowledge base contains the characteristics, causes, effects and corresponding treatment measures of various fault types. When the system detects When a fault matching a pattern in the knowledge base is detected, processing suggestions can be quickly provided to reduce the time for fault diagnosis. The early warning system can dynamically adjust the warning level according to the severity and potential impact of the fault, which helps ensure that relevant personnel take appropriate countermeasures according to the urgency of the warning. For example, for faults that may cause serious consequences, the system can issue a high-level emergency warning. When a fault occurs, the system can support remote fault diagnosis and collaboration functions. Experts or technicians can remotely access system data, perform fault analysis and diagnosis, provide processing suggestions or remotely assist in solving problems. This can not only improve the efficiency of fault handling, but also reduce the cost and risk of on-site maintenance.

[0037] Flight data in-depth analysis module: conduct in-depth analysis and mining of data from processes such as vertical catapult takeoff and take-off and landing field tilt control, compare take-off and landing data from different take-off and landing fields, including water and land, accurately control them respectively, and put forward targeted optimization suggestions to further improve the efficiency and safety of take-off and landing; specifically: collect real-time data from processes such as vertical catapult takeoff and take-off and landing field tilt control, including but not limited to sensor data, control system logs, and video images, integrate data from different take-off and landing fields (water and land), ensure unified data format, facilitate subsequent analysis, clean the collected raw data, remove noise, duplicate or invalid data, ensure data quality, convert and standardize the data according to analysis needs, so as to conduct in-depth analysis and mining, and use data mining and machine learning algorithms to obtain accurate and reliable data. The method conducts in-depth analysis on the preprocessed data, identifies key features and patterns, compares data from different take-off and landing fields, and analyzes key factors that affect take-off and landing efficiency and safety, such as the tilt angle, wind speed, temperature, etc. of the take-off and landing field. According to the analysis results, an optimization model for vertical catapult takeoff and take-off and landing field tilt control is constructed. The model is trained and optimized using machine learning algorithms to improve the accuracy of prediction and control. According to the model prediction results and real-time data, targeted optimization suggestions are provided for the take-off and landing field tilt control module, such as adjusting the tilt angle, optimizing the control strategy, etc. The characteristics of different take-off and landing fields are analyzed, and corresponding take-off and landing plans are proposed to improve take-off and landing efficiency and safety. Through data visualization technology, the analysis results and optimization suggestions are presented to operators in an intuitive way for quick understanding and application.

[0038] Furthermore, the environmental monitoring module includes using high-precision sensors to collect meteorological and electromagnetic environmental data of the take-off and landing field in real time. The meteorological data includes temperature, humidity, wind speed, wind direction, and visibility. The electromagnetic environmental data includes electric field strength, magnetic field strength, and radio frequency. It also performs data preprocessing, uses deep learning algorithms to identify extreme weather conditions and adjust strategies, and includes a preset sampling frequency adjustment function expression:

[0039] f_new=f_old*k*e*s*d

[0040] Where: f_new is the new sampling frequency, f_old is the original sampling frequency, k is the adjustment factor calculated based on weather conditions, e is the adjustment factor calculated based on environmental factors, s is the adjustment factor calculated based on sensor status, and d is the adjustment factor calculated based on data quality assessment.

[0041] Furthermore, in the intelligent flight scheduling module, environmental parameter monitoring includes meteorological data, geographic data, and other environmental factors; aircraft status monitoring includes hardware status, software status, position and attitude; path planning includes algorithm selection and obstacle avoidance strategy; time planning includes meteorological windows and task priorities; take-off condition assessment includes environmental assessment and aircraft status assessment; decision making includes rule-based and machine learning.

[0042] Furthermore, takeoff rules include rule definition, data collection, rule evaluation, decision making, notification and feedback, and rule optimization.

[0043] Furthermore, the fault accurate warning and processing module further includes a warning level setting module, which automatically sets warning signals of different levels according to the fault type, severity and expected impact time.

[0044] Furthermore, the flight data in-depth analysis module can compare with historical data in real time, discover potential performance bottlenecks or safety hazards through data mining technology, and provide data support for the continuous improvement of take-off and landing sites and the optimal design of aircraft.

[0045] Furthermore, it also includes a remote monitoring and operation module, which realizes real-time monitoring and remote control of the take-off and landing field through wireless communication technology.

[0046] Furthermore, the environmental monitoring module also includes a data security assurance module, which ensures the security and integrity of the collected environmental data during transmission and storage through means such as data encryption, backup and recovery.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] Through the real-time monitoring and strategy adjustment functions of the environmental monitoring module, the system can automatically adjust the monitoring strategy according to extreme weather conditions to ensure the safety of the aircraft's takeoff and landing, greatly improving the adaptability and survivability of the helicopter in complex environments, especially in mountainous areas, water areas and other places with harsh conditions. It can significantly reduce take-off and landing accidents caused by weather factors.

[0049] The intelligent flight scheduling module improves the efficiency and accuracy of take-off and landing by monitoring environmental parameters and aircraft status in real time, and intelligently planning the aircraft's take-off and landing paths and times. It not only reduces the aircraft's waiting time and fuel consumption, but also enables more optimized scheduling arrangements in multi-task scenarios, thereby improving overall operational efficiency.

[0050] The vertical catapult take-off module and the take-off and landing field tilt control module enable the aircraft to achieve fast and stable take-off and landing under different site conditions. The vertical catapult take-off method can reduce the take-off and landing distance and take-off time, and improve the flexibility and convenience of take-off and landing; while the take-off and landing field tilt control module can fine-tune the take-off and landing field according to actual needs to ensure the stability and safety of the aircraft during take-off and landing. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a system block diagram of a vertical intelligent take-off and landing field take-off and landing control system of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0053] See also Figure 1 , the present invention provides a technical solution:

[0054] See also Figure 1 As shown, a vertical intelligent take-off and landing field take-off and landing control system includes an environmental monitoring module, an intelligent flight scheduling module, a vertical catapult take-off module, a take-off and landing field tilt control module, a fault accurate warning and processing module, and a flight data in-depth analysis module:

[0055] Environmental monitoring module: real-time monitoring of environmental parameters at the take-off and landing field, and automatic adjustment of monitoring strategies for extreme weather conditions;

[0056] Intelligent flight scheduling module: real-time monitoring of environmental parameters and aircraft status, intelligent planning of aircraft take-off and landing paths and times, and judgment of whether vertical catapult take-off is suitable. Take-off condition assessment includes environmental assessment and aircraft status assessment. The vertical catapult take-off module uses the catapult device to provide additional thrust to achieve rapid take-off of the aircraft, enabling the aircraft to achieve sufficient lift in a shorter period of time. In extreme weather or emergency situations, vertical catapult take-off can significantly improve take-off efficiency and safety. Among them, the catapult device usually includes a catapult, a launch hook and other components. When the aircraft is ready to take off, it will drive above the catapult and connect with the launch hook. Once the take-off command is received, the launch hook of the catapult will be quickly released, and the catapult will start working, providing powerful thrust to accelerate the aircraft forward. During this process, the aircraft engine will also run at full capacity, and work together with the thrust generated by the catapult to enable the aircraft to reach take-off speed in a short time.

[0057] Landing pad tilt control module: adjust the landing pad tilt angle to optimize the control performance of vertical take-off and vertical catapult take-off; adjust the landing pad tilt angle to change the take-off and landing posture of the aircraft and optimize the take-off and landing process; specifically: design the landing pad tilt mechanism, which should have sufficient strength and stability to support the weight and dynamic load of the aircraft during take-off and landing. The tilt mechanism adopts electric, hydraulic or pneumatic drive to achieve precise tilt angle adjustment. Angle sensors are installed to monitor the tilt angle of the landing pad in real time and feed the data back to the control system. Other necessary sensors, such as anemometers, temperature sensors, etc., are installed to obtain data on environmental factors that affect take-off and landing performance. The tilt control module is connected to the aircraft. The flight control system is integrated to ensure that the two can work together to optimize the take-off and landing process. According to the type, weight, take-off speed and environmental factors (such as wind speed and wind direction) of the aircraft, the optimal tilt angle is calculated through an algorithm. The calculation process takes into account the dynamic characteristics of the aircraft and the physical conditions of the take-off and landing field to ensure safety and performance optimization. The control logic is written to calculate and output control instructions based on the real-time data fed back by the sensor and the preset algorithm to drive the tilt mechanism to adjust the angle; design safety strategies, including overload protection, tilt angle limitation, etc., to prevent the tilt mechanism from being damaged or causing danger in extreme cases, and implement fault detection and alarm mechanisms. When a sensor or actuator fails, an alarm can be issued in time and corresponding countermeasures can be taken;

[0058] Accurate fault warning and processing module: real-time monitoring of the operating status of aircraft and take-off and landing fields, in-depth analysis of monitoring data using machine learning algorithms, accurate warning and positioning of faults, and attention to the status and performance of the ejection device during vertical catapult takeoff, predicting the type of fault that may occur, and early warning and processing; specifically: using various sensors installed on aircraft and take-off and landing fields to collect real-time operating data of key components including the ejection device, pre-processing the collected raw data, including noise removal, missing value filling, standardization, etc., to improve data quality and provide a reliable basis for subsequent analysis; based on the pre-processed data, machine learning algorithms are used to extract characteristic parameters related to the fault, reflecting changes in the working status of aircraft and ejection devices, selecting feature combinations, and building fault warning models; using historical fault data and real-time monitoring data to build fault warning models. These models It can be a model based on statistics, machine learning or deep learning. The appropriate model type is selected according to the specific application scenario, and abnormal patterns are identified, the possible fault types are predicted, and corresponding warning signals are given. The constructed fault warning model is integrated into the real-time monitoring system to continuously monitor the status of the aircraft and the ejection device. When abnormal data is detected or an impending fault is predicted, the system automatically triggers the warning mechanism and sends warning information to relevant personnel. According to the warning information, the system locates the specific location or component where the fault occurs, such as a mechanical component or control system of the ejection device, and provides fault handling suggestions or automatically executes preset emergency handling measures to reduce the impact of the fault on the aircraft and the take-off and landing field. Finally, the actual fault data and the performance of the warning system are continuously collected and analyzed, and the warning model is continuously optimized and improved. Through the feedback mechanism, the accuracy and reliability of the warning system are continuously improved;

[0059] Flight data in-depth analysis module: conduct in-depth analysis and mining of data from processes such as vertical catapult takeoff and take-off and landing field tilt control, compare take-off and landing data from different take-off and landing fields, including water and land, accurately control them respectively, and put forward targeted optimization suggestions to further improve the efficiency and safety of take-off and landing; specifically: collect real-time data from processes such as vertical catapult takeoff and take-off and landing field tilt control, including but not limited to sensor data, control system logs, and video images, integrate data from different take-off and landing fields (water and land), ensure unified data format, facilitate subsequent analysis, clean the collected raw data, remove noise, duplicate or invalid data, ensure data quality, convert and standardize the data according to analysis needs, so as to conduct in-depth analysis and mining, and use data mining and machine learning algorithms to obtain accurate and reliable data. The method conducts in-depth analysis on the preprocessed data, identifies key features and patterns, compares data from different take-off and landing fields, and analyzes key factors that affect take-off and landing efficiency and safety, such as the tilt angle, wind speed, temperature, etc. of the take-off and landing field. According to the analysis results, an optimization model for vertical catapult takeoff and take-off and landing field tilt control is constructed. The model is trained and optimized using machine learning algorithms to improve the accuracy of prediction and control. According to the model prediction results and real-time data, targeted optimization suggestions are provided for the take-off and landing field tilt control module, such as adjusting the tilt angle, optimizing the control strategy, etc. The characteristics of different take-off and landing fields are analyzed, and corresponding take-off and landing plans are proposed to improve take-off and landing efficiency and safety. Through data visualization technology, the analysis results and optimization suggestions are presented to operators in an intuitive way for quick understanding and application.

[0060] Furthermore, the environmental monitoring module includes the use of high-precision sensors to collect meteorological and electromagnetic environmental data of the take-off and landing field in real time. The meteorological data includes temperature, humidity, wind speed, wind direction, and visibility. The electromagnetic environmental data includes electric field strength, magnetic field strength, and radio frequency. It also performs data preprocessing, uses deep learning algorithms to identify extreme weather conditions and adjust strategies, and includes a preset sampling frequency adjustment function expression:

[0061] f_new=f_old*k*e*s*d

[0062] Where: f_new is the new sampling frequency, f_old is the original sampling frequency, k is the adjustment factor calculated based on weather conditions, e is the adjustment factor calculated based on environmental factors, s is the adjustment factor calculated based on sensor status, d is the adjustment factor calculated based on data quality assessment, k is the function that calculates the adjustment factor based on current weather conditions (such as temperature, humidity, wind speed, visibility, etc.). For example, in extreme weather conditions (such as heavy rain, blizzards, thunderstorms), the function may return a higher value to increase the sampling frequency, and e is the function that takes into account environmental factors such as terrain, topography, altitude, and any other factors that may affect sensor performance. For example, at high altitudes In some regions or special terrains, a higher sampling frequency may be required to ensure the accuracy of the data. The function s calculates the adjustment factor based on the current state of the sensor (such as operating time, temperature, humidity, calibration status, etc.). If the sensor fails or its performance degrades, the function may return a lower value to reduce reliance on unreliable data. The function d should evaluate the quality of the collected data and return an adjustment factor accordingly. The data quality is evaluated based on noise level, signal stability, data consistency, etc. If the data quality is poor, the function may return a higher value to increase the sampling frequency in order to obtain more data to improve the quality.

[0063] Furthermore, in the intelligent flight scheduling module, environmental parameter monitoring includes meteorological data, geographic data, and other environmental factors; aircraft status monitoring includes hardware status, software status, and position and attitude; path planning includes algorithm selection and obstacle avoidance strategy; time planning includes meteorological window and task priority; take-off condition assessment includes environmental assessment and aircraft status assessment; decision making includes rule-based and machine learning; specifically: in meteorological data, real-time meteorological data including wind speed, wind direction, temperature, humidity, air pressure, visibility, etc. are obtained through meteorological stations, satellites or online APIs; in geographic data, geographic information system (GIS) is used to obtain geographic information of the flight area, including terrain, obstacles, no-fly zones, etc.; in other environmental factors, electromagnetic interference and noise limit specific environmental factors are considered; hardware status includes monitoring battery power, engine / motor status, and sensor status; software status is to check the working status of software components such as flight control system and navigation system; position and attitude, namely, the position, speed and attitude information of the aircraft are obtained in real time through sensors such as GPS and IMU; in algorithm selection, A*, Di jkstra or other path planning algorithms generate the optimal path based on environmental parameters and aircraft status. When using obstacle avoidance strategies, terrain, obstacles and no-fly zones are considered to plan a safe flight path; weather window: select the most suitable time period for flight based on weather forecasts; mission priority, that is, allocating flight time based on the importance and urgency of the mission; environmental assessment is to check whether the wind speed is within a safe range and whether the ground is flat and free of obstacles; in the aircraft status assessment, ensure that the battery is fully charged, the engine / motor is in good condition, and the vertical take-off and landing system is working properly; rule-based is to set take-off rules; machine learning is to use machine learning models to predict whether it is suitable for vertical catapult take-off based on historical data and real-time data; it should be supplemented that the performance of the intelligent scheduling module is tested in a simulation environment, including the accuracy of path planning, time planning and take-off decisions; verification is carried out in an actual flight environment, feedback data is collected, and the intelligent scheduling module is continuously optimized and improved.

[0064] Furthermore, the implementation of rule-based takeoff decision involves the following steps: rule definition: determine the key factors that affect takeoff, such as wind speed, battery power, temperature, etc., and set one or more thresholds for each key factor. For example, set the maximum threshold of wind speed to 20 km / h and the minimum threshold of battery power to 80%; data collection: obtain data on key factors that affect takeoff in real time from sensors or other data sources to ensure the accuracy and real-time nature of the data so that accurate decisions can be made; rule evaluation: write a rule evaluation function or logic that accepts real-time data as input and determines whether takeoff can be made based on the defined rules. For each rule, check whether the real-time data meets the conditions of the rule; decision making: if the conditions of all rules are met, the decision is "can take off", and if the conditions of any rule are not met, the decision is "cannot take off"; notification and feedback: notify the relevant system or operator of the takeoff decision, and record each decision result and related information for subsequent analysis and optimization of the rules; rule optimization: regularly check and adjust the threshold of the rules or add new rules based on historical data and experience, The takeoff decision process is continuously optimized through feedback loops. It should be noted that the rules may need to be adjusted dynamically to take into account different seasons, weather conditions or aircraft types. For example, in winter, battery performance may decline, so the battery power threshold may need to be increased accordingly. Use machine learning or statistical methods to dynamically adjust the threshold based on historical data and real-time environmental data. In addition to wind speed and battery power, consider other factors such as temperature, humidity, air pressure, etc. These factors may affect the performance and safety of the aircraft, set weights for each factor, and use weighted summation or other algorithms to comprehensively evaluate whether it is suitable. When sensor data is abnormal or missing, execute the corresponding processing mechanism, such as using default values, interpolating data or triggering alarms. Suppose there is a drone system that needs to judge whether it is suitable for takeoff based on rules. The following is a specific example: Example description: The drone is ready to take off on a sunny summer day. The current wind speed is 15 km / h, the battery power is 85%, the temperature is 30 degrees Celsius, the humidity is 50%, and the air pressure is normal. We need to determine whether the drone can take off under these conditions; rule definition: maximum wind speed threshold: 20 km / h, minimum battery power threshold: 80% (considering that high temperatures in summer may affect battery performance, this threshold may be higher than in winter), temperature range: 0-50 degrees Celsius (exceeding this range may affect drone performance), humidity range: 0-80% (exceeding this range may affect the operation of electronic equipment), air pressure range: within normal range (the specific range depends on the design of the drone) Data collection: Get real-time data from sensors on the drone: wind speed 15 km / h, battery power 85%, temperature 30 degrees Celsius, humidity 50%, normal air pressure; rule evaluation:

[0065] Wind speed 15 km / h <= 20 km / h, meets the conditions;

[0066] The battery power is 85%>=80%, which meets the condition;

[0067] The temperature is 30 degrees Celsius and is within the range of 0-50 degrees Celsius, which meets the conditions;

[0068] Humidity 50% is within the range of 0-80%, which meets the conditions;

[0069] The air pressure is normal and meets the conditions;

[0070] Decision making: Since all the conditions of the rules are met, the decision is "take-off is possible"; Notification and feedback: The UAV system receives the take-off decision notification and starts to execute the take-off procedure. At the same time, the data and decision results of this take-off are recorded for subsequent analysis and optimization of rules. Rule optimization: After a period of operation and data accumulation, the threshold of the rule is adjusted according to historical data and experience. For example, if it is found that the performance of the UAV has declined under certain conditions, the threshold of certain factors is increased accordingly to ensure safe take-off.

[0071] Furthermore, the fault accurate warning and processing module further includes a warning level setting module, which automatically sets different levels of warning signals according to the fault type, severity and expected impact time, so that operators can respond quickly and take corresponding processing measures. Specifically: based on historical fault data, expert knowledge and industry experience, faults are divided into different types (such as mechanical faults, electrical faults, control system faults, etc.) and levels (such as minor, general, severe, etc.). For abnormal data monitored in real time, the system uses a pre-trained model to evaluate the severity of the fault, which involves a comprehensive analysis of multiple key indicators, such as the frequency, duration, and scope of impact of the fault. The development trend and historical data of faults, and the system predict the estimated time of impact of faults, help operators better arrange maintenance and emergency response plans, and reduce the impact of faults on aircraft and take-off and landing sites. Based on a comprehensive evaluation of fault type, severity and estimated impact time, the warning level setting module will automatically set the corresponding warning level for each fault event, which is achieved by setting thresholds and rules. For example, when the severity of the fault exceeds a certain threshold, a high-level warning signal is automatically triggered. Once the warning level is set, the system outputs and displays the corresponding warning signal. The signal can be an audible and visual alarm, SMS notification, email reminder or other forms of visual display to ensure that operators can quickly notice and take action.

[0072] Furthermore, the flight data in-depth analysis module can compare with historical data in real time, discover potential performance bottlenecks or safety hazards through data mining technology, and provide data support for the continuous improvement of the take-off and landing field and the optimal design of the aircraft; specifically: first, it is necessary to build an integrated data storage system that can receive and store flight data in real time, including all data in the process of vertical catapult takeoff, take-off and landing field tilt control, etc. At the same time, the system should also contain historical data for real-time and historical comparison analysis. Use stream processing technology to pre-process the flight data received in real time, such as cleaning, conversion and standardization, to ensure that the quality and format of the real-time data meet the analysis requirements, to facilitate subsequent comparison and mining work, determine the comparison algorithm or model, and compare the real-time data with the corresponding historical data. It can be implemented based on time series analysis, pattern recognition and other technologies to discover anomalies or trend changes in the data, compare flight parameters such as speed, altitude, attitude, etc., and find out situations that are inconsistent with historical data or exceed the normal range, which may indicate potential performance bottlenecks or safety hazards. Apply data mining technologies such as cluster analysis, association rule mining, anomaly detection, etc. to conduct in-depth analysis of real-time and historical data to identify hidden Hidden patterns and associations are identified, with special attention paid to those patterns that frequently appear in historical data and are related to safety issues. These may be indicators of performance bottlenecks or safety hazards. Based on the results of data mining, potential performance bottlenecks and safety hazards are identified, involving multiple aspects such as aircraft component performance, take-off and landing field conditions, and operating procedures. Statistical analysis or machine learning models are used to quantitatively evaluate the identified problems to determine their severity and likelihood of occurrence. The analysis results are presented in a visual form, such as dashboards, heat maps, trend maps, etc., to facilitate operators and decision makers to intuitively understand the problems. A detailed analysis report is generated, including a description of performance bottlenecks and safety hazards, impact assessment, and recommended improvement measures. Based on the analysis report, continuous improvements are made to the take-off and landing field, such as adjusting take-off and landing strategies, optimizing equipment layout, etc. At the same time, the analysis results are fed back to the aircraft design team to provide data support for the optimization design of the aircraft to improve its performance and safety. A feedback loop mechanism is established to collect feedback data and new flight data in actual applications for verification and improvement of the analysis model. With the accumulation of data and the advancement of analysis technology, the flight data deep analysis module is continuously updated and optimized to improve its accuracy and effectiveness.

[0073] Furthermore, it also includes a remote monitoring and operation module, which realizes real-time monitoring and remote control of the take-off and landing field through wireless communication technology, so that operators can manage and control the take-off and landing process at a location far away from the take-off and landing field. Specifically, it is as follows: Network architecture design and deployment: Design and build a stable and reliable network architecture to support data transmission of wireless communication technologies, such as 5G, WiFi, satellite communication, etc., to ensure the real-time and reliability of remote monitoring and operation; deploy necessary communication equipment and sensors at the take-off and landing field to collect real-time data of the take-off and landing process and transmit it to the remote monitoring center; Data transmission and reception: Use the wireless communication network to transmit the real-time data of the take-off and landing field to the remote monitoring center. This can include various types of data such as video streams, sensor data, and operation instructions; Set up receiving equipment in the remote monitoring center to receive real-time data from the take-off and landing field, and decode and process it for operators to view and analyze; Real-time monitoring interface development: Develop a user-friendly real-time monitoring interface to display the real-time situation of the take-off and landing field. The interface should be able to display video images, sensor data, operating status and other information, and provide necessary operating buttons and controls; operators can observe the take-off and landing process in real time through the interface and perform remote control as needed; remote control function implementation: remote control function is integrated into the remote monitoring and operation module, allowing operators to send operating instructions to the take-off and landing site through the interface; these instructions may include adjusting take-off and landing parameters, controlling take-off and landing equipment, initiating emergency procedures, etc., to achieve remote management and control of the take-off and landing process; security and authority management: considering the sensitivity of remote monitoring and operation, a strict security and authority management mechanism must be established; encryption technology is used to protect the security of data transmission to ensure that data is not intercepted or tampered with modification; set different user roles and permission levels to ensure that only authorized personnel can perform remote monitoring and operation; fault response and emergency response: integrate fault response and emergency response mechanisms in the remote monitoring and operation module; when a fault or abnormal situation is detected, the system should be able to automatically trigger an alarm and notify the operator through the remote monitoring interface; the operator can quickly take corresponding emergency measures, such as starting the backup system, adjusting operating parameters, etc., to reduce the impact of the fault on the take-off and landing process; testing and verification: before actual application, the remote monitoring and operation module should be fully tested and verified; simulate the take-off and landing process in different scenarios, test the stability and reliability of the module, and ensure that it can work normally and meet actual needs.Furthermore, the environmental monitoring module also includes a data security assurance module, which ensures the security and integrity of the collected environmental data during transmission and storage through data encryption, backup and recovery, etc. Specifically: data encryption technologies, such as symmetric encryption, asymmetric encryption, hash algorithms and digital signatures, are used to encrypt the transmitted and stored environmental data. Symmetric encryption uses the same key for encryption and decryption, which is suitable for encryption of large amounts of data. Asymmetric encryption uses public and private keys for encryption and decryption, which is suitable for key management and digital signature scenarios. The hash algorithm can convert data into a hash value of a fixed length for verifying the integrity of the data. Digital signatures can ensure the integrity of data and the identity authentication of the sender, and adopt multiple backup strategies to regularly back up environmental data to independent servers to prevent data loss caused by failure of the main server. Backup data is stored in different geographical locations to prevent data loss caused by natural disasters or man-made damage. Data integrity checks and recovery tests are regularly performed to ensure the availability and integrity of backup data. Real-time backup and recovery: Implement real-time backup technology to perform uninterrupted backup of environmental data to ensure that data can be quickly restored even in the event of an emergency. Adopt a business-level real-time backup strategy, and the backup content includes operating systems, software applications, information data, environmental configurations, etc. to support rapid business recovery. Use backup virtualization technology to monitor disk changes in real time, implement asynchronous replication and offline snapshots to improve backup efficiency and reliability. Backup virtualization technology can also realize data backup and recovery between different physical machines and virtual machines, improving the flexibility and applicability of backup; Use secure storage devices to ensure the physical security of environmental data during the storage process; Establish strict data access permission management to ensure that only authorized personnel can access and modify environmental data; Network security protection: During data transmission, adopt network security protection measures such as firewalls, intrusion detection systems, etc. to prevent data from being illegally intercepted or tampered with, and use secure communication protocols and encryption technologies to ensure the confidentiality and integrity of data during transmission; Security audit and log recording: Establish a security audit mechanism to record operations such as access, modification and transmission of environmental data in order to track and investigate possible security incidents; Regularly analyze and review security logs to identify potential security risks and take corresponding measures.

Claims

1. A vertical intelligent take-off and landing control system, characterized by: It includes environment monitoring module, intelligent flight dispatch module, vertical catapult takeoff module, take-off and landing field tilt control module, fault accurate warning and processing module and flight data in-depth analysis module: Environmental monitoring module: real-time monitoring of environmental parameters at the take-off and landing field, and automatic adjustment of monitoring strategies for extreme weather conditions; Intelligent flight scheduling module: real-time monitoring of environmental parameters and aircraft status, intelligent planning of aircraft take-off and landing paths and times, and judgment of whether vertical catapult take-off is suitable. Take-off condition assessment includes environmental assessment and aircraft status assessment; Vertical catapult takeoff module: uses the catapult device to provide additional thrust to achieve rapid takeoff of the aircraft; Landing pad tilt control module: adjusts the tilt angle of the landing pad; Accurate fault warning and processing module: monitors the operating status of the aircraft and take-off and landing field in real time, uses machine learning algorithms to conduct in-depth analysis of monitoring data, realizes accurate warning and positioning of faults, and pays attention to the status and performance of the ejection device during vertical catapult takeoff, predicts the type of fault that may occur, and provides early warning and processing; Flight data in-depth analysis module: conducts in-depth analysis and mining of data during vertical catapult takeoff and take-off and landing field tilt control, compares take-off and landing data at different take-off and landing fields, including water and land, and precisely controls each.

2. A vertical intelligent take-off and landing control system as claimed in claim 1, characterized in that: The environmental monitoring module uses high-precision sensors to collect meteorological and electromagnetic environmental data of the take-off and landing field in real time. Meteorological data includes temperature, humidity, wind speed, wind direction, and visibility. Electromagnetic environmental data includes electric field strength, magnetic field strength, and radio frequency. It also performs data preprocessing, uses deep learning algorithms to identify extreme weather conditions and adjust strategies, and includes a preset sampling frequency adjustment function expression: f_new=f_old*k*e*s*d Where: f_new is the new sampling frequency, f_old is the original sampling frequency, k is the adjustment factor calculated based on weather conditions, e is the adjustment factor calculated based on environmental factors, s is the adjustment factor calculated based on sensor status, and d is the adjustment factor calculated based on data quality assessment.

3. A vertical intelligent take-off and landing control system as claimed in claim 1, characterized in that: In the intelligent flight scheduling module, environmental parameter monitoring includes meteorological data, geographic data, and other environmental factors; aircraft status monitoring includes hardware status, software status, position and attitude; path planning includes algorithm selection and obstacle avoidance strategy; time planning includes meteorological windows and task priorities; take-off condition assessment includes environmental assessment and aircraft status assessment; decision making includes rule-based and machine learning.

4. A vertical intelligent take-off and landing control system as claimed in claim 3, characterized in that: Takeoff rules include rule definition, data collection, rule evaluation, decision making, notification and feedback, and rule optimization.

5. A vertical intelligent take-off and landing control system as claimed in claim 1, characterized in that: The fault accurate warning and processing module further includes a warning level setting module, which automatically sets warning signals of different levels according to the fault type, severity and expected impact time.

6. A vertical intelligent take-off and landing control system as claimed in claim 1, characterized in that: The flight data in-depth analysis module can compare with historical data in real time, discover potential performance bottlenecks or safety hazards through data mining technology, and provide data support for the continuous improvement of take-off and landing sites and the optimal design of aircraft.

7. A vertical intelligent take-off and landing control system as claimed in claim 1, characterized in that: It also includes a remote monitoring and operation module, which realizes real-time monitoring and remote control of the take-off and landing field through wireless communication technology.

8. The vertical intelligent take-off and landing control system according to claim 1, characterized in that: The environmental monitoring module also includes a data security assurance module, which ensures the security and integrity of the collected environmental data during transmission and storage through data encryption, backup and recovery.

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