A flight area wind direction early warning intelligent adjustment and modulation system and method

Abstract

The application is a divisional application of the Chinese invention patent application with application number 202411131195.3, application date August 17, 2024 and invention name "Airport perimeter monitoring device capable of tilting". The application discloses a flight area wind direction early warning intelligent adjustment system and method. The system comprises a front-end monitoring device, an airport intrusion alarm system management platform and a system sub-control workstation. The front-end monitoring device comprises a wind speed and direction sensor, a noise sensor, an infrared monitoring camera and a sound pickup device. The method is to install the front-end monitoring device at multiple points in the flight area in a distributed manner, to monitor the wind speed, wind direction and noise of the flight area in real time, to adopt a sub-set wind direction take-off and landing risk early warning method, to realize differentiated crosswind, tailwind and headwind risk classification early warning and visual verification for civil aviation passenger and cargo aircrafts and general aviation aircrafts, to ensure the safety of aircraft take-off and landing, to adopt a perimeter intrusion alarm wind noise intelligent adjustment method, to monitor the wind speed and the noise generated by strong wind, heavy rain and hail, to analyze the influence of the environment on the sensitivity of the intrusion alarm detector, to adaptively adjust and reduce the false alarm rate, and to realize flight area wind field safety early warning and perimeter security anti-interference integrated intelligent control.

Description

[0001] This invention is a divisional application of Chinese invention patent application No. 202411131195.3, filed on August 17, 2024, entitled "A tiltable airport perimeter monitoring pole". Technical Field

[0002] This invention relates to the field of airport flight area environmental monitoring and intrusion alarm technology, and in particular to an intelligent wind direction early warning system and method for flight areas. Background Technology

[0003] The flight area is the core safety zone for civil aviation airport operations, directly determining the safety of aircraft takeoff and landing. Low-altitude wind fields in the flight area exhibit significant localization, suddenness, and unpredictable changes, making them a key source of meteorological risk for civil aviation operations. Excessive crosswinds can easily cause aircraft approach attitude deviations, fuselage sideslip, and excessive touchdown deviations, ranging from minor issues like fuselage turbulence and landing gear overload damage to more serious issues like runway veer-off. Excessive tailwinds significantly reduce aircraft approach airspeed and prolong takeoff and landing distances, easily inducing dangerous situations such as hard landings, runway overruns, and missed go-arounds. Excessive headwinds greatly increase aircraft landing loads and prolong braking distances, similarly threatening takeoff and landing safety. Many civil aviation takeoff and landing safety incidents and incident precursors over the years have been caused by sudden crosswinds and tailwind disturbances, posing a significant threat to flight operation safety and the lives and property of passengers.

[0004] Meanwhile, the frequent occurrence of strong winds, heavy rains, and hail in the flight zone has resulted in poor working conditions for the perimeter security intrusion alarm equipment, leading to frequent false alarms. Under these circumstances, it is impossible to effectively monitor and alarm against illegal intrusions into the flight zone, and it is impossible to prevent illegal intrusions that could damage aircraft and runway facilities in a timely manner, posing a significant security risk.

[0005] Existing standardized airport meteorological observation systems and perimeter intrusion security systems can routinely collect and transmit basic meteorological data and perimeter monitoring data, meeting the basic operation and maintenance needs of daily airport safety monitoring. They are the mainstream configuration for current airport flight safety and perimeter security.

[0006] However, the existing meteorological observation system lacks the ability to intelligently identify and classify wind fields based on aircraft type, and the existing perimeter security system lacks a general wind noise anti-interference adaptive sensitivity adjustment mechanism. The intelligent processing capabilities of the two systems are insufficient, and they cannot solve the existing technical pain points of the airport flight area, resulting in significant technical limitations.

[0007] Regarding wind direction monitoring and early warning in the flight area, the existing airport meteorological observation system mainly consists of a single-point fixed automatic meteorological observation system combined with meteorological radar. Among them, conventional meteorological radar and wind profiler radar are mainly for monitoring large-scale meteorological conditions at high altitudes, but they have blind spots in low-altitude near-ground detection. They are highly susceptible to interference from airport buildings, perimeter facilities, and ground clutter. They have poor ability to capture small-scale local wind fields and sudden gusts near the ground in core take-off and landing areas such as runways and airspace, and cannot accurately detect sudden changes in local wind fields at low altitudes. The single-point fixed meteorological observation equipment in the flight area cannot accurately quantify and distinguish the differentiated take-off and landing risk thresholds of civil aviation passenger aircraft, cargo aircraft, and general aviation aircraft. There is no differentiated early warning mechanism based on aircraft type, no multi-point data calibration mechanism for different aircraft types, and no graded risk early warning logic. It is difficult to support refined air traffic control and aircraft type-based take-off and landing scheduling decisions, and it is impossible to effectively avoid take-off and landing safety risks induced by excessive crosswinds, tailwinds, and headwinds for different aircraft types.

[0008] In terms of perimeter security intrusion alarm monitoring, existing airport perimeter security intrusion alarm systems are generally equipped with intrusion alarm detection devices with manually fixed sensitivity levels, lacking remote intelligent sensitivity adjustment (referred to as sensitivity adjustment) functions. The system's monitoring sensitivity is fixed and constant, unable to adapt to the complex environment of dynamic coupling between wind and noise in the flight area. False alarms occur frequently in high wind noise conditions, and missed alarms are prone to occur in low interference conditions, resulting in poor monitoring stability. At the same time, existing perimeter security intrusion alarm systems generally use a variety of monitoring devices such as vibration detectors, vibration optical cables, vibration electrical cables, and microwave radar. The monitoring algorithms of each system are only adapted to a single device type, lacking cross-device universal adaptability. Different types of devices require separate debugging and maintenance, resulting in high modification costs and cumbersome operation and maintenance, and a lack of universal intelligent anti-interference monitoring solutions.

[0009] In summary, existing airport meteorological observation systems suffer from technical deficiencies such as lack of wind field monitoring for different aircraft types and lack of differentiated classification and early warning. Existing perimeter security intrusion alarm systems lack intelligent sensitivity adjustment schemes and suffer from technical shortcomings such as weak wind noise anti-interference ability, high false alarm rate, poor adaptability of fixed sensitivity of front-end detectors, and high cost of intelligent upgrades.

[0010] In view of the above-mentioned shortcomings of the existing technology, it is necessary to develop an intelligent wind direction early warning system and method for flight areas. Summary of the Invention

[0011] The purpose of this invention is to provide an intelligent sensitivity adjustment system and method for wind direction early warning in flight areas. The system involves distributing the aforementioned front-end monitoring devices at multiple locations within the flight area to monitor wind speed, wind direction, and noise environment conditions in real time. It employs a wind direction-based takeoff and landing risk early warning method for different aircraft types, enabling differentiated crosswind, tailwind, and headwind risk classification and visual verification for civil aviation passenger aircraft, cargo aircraft, and general aviation aircraft, thus ensuring aircraft takeoff and landing safety. Furthermore, it utilizes an intelligent sensitivity adjustment method for perimeter intrusion alarms, monitoring wind speed and noise generated by strong winds, heavy rain, and hail to analyze the impact of these factors on the sensitivity of intrusion alarm detectors. This allows for adaptive adjustment of detection sensitivity, reducing false alarm rates, saving system modification and maintenance costs, and achieving integrated intelligent control of flight area wind field safety early warning and perimeter security anti-interference monitoring.

[0012] To achieve the above objectives, the present invention provides the following solution: A method for early warning of takeoff and landing risks in flight areas based on wind direction includes the following steps: S1. Distributed network deployment of runways: Multiple sets of front-end monitoring devices are symmetrically distributed on both sides of key areas such as runway entrance, touchdown zone, runway midpoint, runway end, and approach lighting strip entrance in the flight area, and the system is networked and connected to the airport intrusion alarm system management platform to realize real-time monitoring and visual verification of crosswind, tailwind, and headwind speed, wind direction, and noise in key areas of the runway. S2. Wind field data acquisition and filtering: Real-time acquisition of raw wind speed and direction data from multiple points in the flight area, noise reduction and smoothing processing through a preset filtering algorithm, elimination of instantaneous interference data, retention of effective abrupt change signals, and output of stable and continuous wind field monitoring data. S3. Accurate wind speed and direction identification: Based on the standard take-off and landing heading of the airport runway, three independent wind field states are divided into crosswind, tailwind and headwind. Local deviations are calibrated by multi-point monitoring data to eliminate single-point monitoring errors and accurately identify wind speed and direction. S4. Aircraft Type Classification Warning: For crosswind, tailwind, and headwind anomalies of civil aviation passenger aircraft, cargo aircraft, and general aviation aircraft, warnings are triggered according to aircraft type; the wind direction warning subsystem is configured with differentiated takeoff and landing risk warning thresholds according to different aircraft types, and supports dynamic adjustment of thresholds by accessing flight plan data; after the warning is triggered, the warning information is simultaneously pushed to the airport security platform duty room and air traffic control tower workstation; S5. Visual verification of early warning: After triggering a takeoff and landing risk warning, the system accurately links with on-site audio and video equipment to visually verify the warning scenario, identify and filter false warnings, and after verification confirms the existence of a real takeoff and landing risk, execute the subsequent ground-to-air early warning push process; S6. Ground-to-air coordinated early warning push: Air traffic controllers in the tower can push airborne early warning prompts to aircraft in the runway approach, take-off and landing phases through the dedicated air traffic control communication link, informing them of abnormal wind speed and direction information and take-off and landing risk levels for the corresponding aircraft type, and assisting pilots in flight decision-making; S7. Wind Farm Data Closed-Loop Archiving: Fully archive and store all wind farm monitoring data, status judgment results, wind turbine type early warning ledgers, verification vouchers, and ground-to-air early warning push records to achieve traceable and auditable operation and maintenance management of early warning events.

[0013] A method for intelligently adjusting wind noise sensitivity in airport perimeter intrusion alarms includes the following steps: A1. Distributed Network Deployment of the Perimeter: Multiple sets of front-end monitoring devices are deployed in a differentiated manner within 5 meters of the airside of the physical perimeter of the flight area and the system is networked and connected to the airport intrusion alarm system management platform to realize real-time monitoring and visual verification of wind speed, wind direction and noise in the perimeter intrusion alarm monitoring area. A2. Preset reference parameters: The system solidifies multi-level wind noise interference ranges and corresponding monitoring sensitivity references, and adopts a reverse adaptation mechanism between wind noise intensity and monitoring sensitivity. The stronger the wind noise interference, the lower the monitoring sensitivity. The front-end hardware level is locked and the software sensitivity template is stored to provide a reference for adaptive sensitivity adjustment. A3. Multi-source data acquisition and filtering: Real-time acquisition of multi-source environmental data such as wind speed, wind direction, noise, and perimeter vibration in the flight area. The data is then processed by a unified filtering algorithm to reduce noise, eliminate instantaneous environmental interference, and retain real environmental changes and effective intrusion detection signals. A4. Adaptive Anti-shake Sensitivity Adjustment: The system presets five discrete sensitivity levels, with each level range being non-overlapping and having clear boundaries. Based on real-time wind noise conditions, it matches the corresponding sensitivity level according to the reverse adaptation principle; the stronger the wind noise, the lower the sensitivity. Level switching is only performed when the wind noise parameter crosses the level boundary and remains stable for a preset duration. No fine-tuning is performed during the level lock period to avoid frequent parameter adjustments caused by instantaneous disturbances. Under complex wind noise coupling conditions, it adapts according to the principle of prioritizing high interference, and parameter adaptation is completed throughout the process through software template switching without the need to modify the front-end hardware. A5. Cross-verification of intrusion behavior: After an intrusion alarm is triggered, the system combines the matching results of five sensitivity levels and cross-verifies the data from multiple sources and video footage features to distinguish between real intrusion behavior and false alarms caused by wind noise interference, thus filtering out false alarms. At the same time, the system continuously optimizes the wind noise matching standard and the level switching rules based on the verification results. A6. Intrusion Alarm Information Push: After a genuine intrusion is confirmed, alarm information is simultaneously pushed to the airport security platform duty room, the system sub-control workstation of the air traffic control tower, and other networked platforms, triggering screen pop-ups and audible and visual alarms to achieve multi-terminal linkage early warning prompts; A7. Closed-loop archiving of monitoring data: Collect and archive wind noise monitoring data, sensitivity adjustment logs, equipment operation data and alarm verification vouchers to achieve system parameter iteration and traceable auditing of abnormal events.

[0014] Preferably, a smart sensitivity adjustment system for wind direction early warning in flight areas includes: a front-end monitoring device, an airport intrusion alarm system management platform, and a system sub-control workstation; the front-end monitoring device includes a wind speed and wind direction sensor, a noise sensor, an infrared monitoring camera, and a microphone; the front-end monitoring device is installed on the airport perimeter monitoring poles, and is respectively deployed in key areas of the flight area runway and key areas of the perimeter, connected to the same network and connected to the management platform; The management platform includes a wind direction early warning subsystem and a wind noise intelligent sensitivity adjustment subsystem, which are used to execute the takeoff and landing risk early warning method described in claim 1 and the perimeter intrusion alarm wind noise intelligent sensitivity adjustment method described in claim 2, respectively. The airport intrusion alarm system management platform has a reserved software interface that can access airport flight plan data and dynamically adjust the takeoff and landing risk early warning threshold according to parameters such as takeoff and landing time and aircraft weight. It can also be integrated with airport ground monitoring system data to accurately analyze the wind field status of the flight area. It can also be connected to the perimeter security system intrusion alarm detectors via network and linked with the airport perimeter security platform.

[0015] Preferably, the intelligent adjustment system for wind direction early warning in the flight area is characterized in that the total height of the tiltable airport perimeter monitoring pole is limited to not penetrating the airspace restriction surface, and is not less than 3.5 meters within 5 meters of the physical boundary airspace side, depending on the installation location.

[0016] Preferably, the intelligent sensitivity adjustment system for flight area wind direction early warning adopts pure software control in both methods, without the need to modify the front-end hardware; by suppressing frequent parameter fluctuations through level-based sensitivity adjustment, the system modification cost and operation and maintenance cost are reduced, and integrated intelligent control of flight area wind field safety early warning and perimeter security anti-interference is realized.

[0017] According to specific embodiments provided by the present invention, the present invention discloses the following beneficial effects: 1. The design adopts a wind speed and direction warning system that differentiates between aircraft models. It can dynamically adjust the takeoff and landing risk warning threshold by accessing flight plan data through a reserved software interface, accurately match the wind resistance capabilities of different aircraft models, effectively avoid differentiated takeoff and landing risks, and significantly improve the accuracy and reliability of wind field takeoff and landing warnings.

[0018] 2. An innovative gear-based adaptive anti-shake and sensitivity adjustment mechanism can adapt to complex wind noise environments in real time, significantly reducing the false alarm rate of the perimeter boundary, reducing the frequency of manual parameter adjustment, and improving the stability of system operation.

[0019] 3. Construct a closed-loop control process for alarm verification, interference callback, and multi-terminal linkage to effectively filter false alarms, achieve rapid early warning of real intrusion events, and enhance perimeter security response efficiency.

[0020] 4. The entire process adopts a pure software strategy to achieve intelligent control, without the need to modify the front-end hardware. It has strong engineering adaptability, is easy to implement, and has low modification costs.

[0021] 5. It integrates wind speed and direction early warning, boundary sensitivity adjustment, and data archiving into a unified architecture, ensuring full traceability and auditability, and meeting the requirements for safe and compliant operation of civil aviation. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 System topology diagram of the present invention; Figure 2 Installation diagram of the front-end equipment of the system of this invention; Figure 3 Flowchart of the wind direction takeoff and landing risk early warning method for the flight area of ​​this invention; Figure 4 Flowchart of the intelligent noise sensitivity adjustment method for airport perimeter intrusion alarm in this invention. Figure Labels

[0024] 1. Tiltable airport perimeter monitoring pole; 1-1. Monitoring pole body; 1-101. Poles reinforced concrete foundation; 1-102. Tilting device; 1-103. Cable trough column; 1-104. Cable trough crossarm; 1-2. Built-in control box; 2. Perimeter security equipment box; 3. Airport intrusion alarm system management platform; 4. System sub-control workstation; 5. Wind speed and direction sensor; 6. Noise sensor; 7. Infrared monitoring camera; 8. Microphone. Detailed Implementation

[0025] The purpose of this invention is to provide an intelligent sensitivity adjustment system and method for wind direction early warning in flight areas. The system involves distributing the aforementioned front-end monitoring devices at multiple locations within the flight area to monitor wind speed, wind direction, and noise environment conditions in real time. It employs a wind direction-based takeoff and landing risk early warning method for different aircraft types, enabling differentiated crosswind, tailwind, and headwind risk classification and visual verification for civil aviation passenger aircraft, cargo aircraft, and general aviation aircraft, thus ensuring aircraft takeoff and landing safety. Furthermore, it utilizes an intelligent sensitivity adjustment method for perimeter intrusion alarms, monitoring wind speed and noise generated by strong winds, heavy rain, and hail to analyze the impact of these factors on the sensitivity of intrusion alarm detectors. This allows for adaptive adjustment of detection sensitivity, reducing false alarm rates, saving system modification and maintenance costs, and achieving integrated intelligent control of flight area wind field safety early warning and perimeter security anti-interference monitoring.

[0026] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0027] like Figure 1 , Figure 2 As shown, a smart sensitivity adjustment system for wind direction early warning in flight zones includes: a front-end monitoring device, an airport intrusion alarm system management platform 3, and a system sub-control workstation 4; the front-end monitoring device includes a wind speed and direction sensor 5, a noise sensor 6, an infrared monitoring camera 7, and a microphone 8; the front-end monitoring device is installed on a tiltable airport perimeter monitoring pole 1, and is electrically connected to the built-in control box 1-2 of the tiltable airport perimeter monitoring pole 1, and the built-in control box 1-2 is connected to the perimeter security equipment box 2 or the navigation station network equipment and networked with the airport intrusion alarm system management platform 3 via a network; the system sub-control workstation 4 is located in the airport security platform duty room, air traffic control tower seating area, etc., and is connected to the airport intrusion alarm system management platform 3 via a network; The airport intrusion alarm system management platform 3 is equipped with a wind direction early warning subsystem and an intrusion alarm wind noise intelligent sensitivity adjustment subsystem. The airport intrusion alarm system management platform 3 has a reserved software interface that can access airport flight plan data and dynamically adjust the take-off and landing risk early warning threshold according to parameters such as take-off and landing time and aircraft type and weight. It can also be integrated with airport ground monitoring system data to accurately analyze the wind field status of the flight area. It can also be connected to the intrusion alarm detector of the perimeter security system through the network and linked with the airport perimeter security platform. The wind speed and direction sensor 5 is an ultrasonic wind speed and direction sensor that uses the ultrasonic time-of-flight method to measure wind speed and direction. The noise sensor 6 is used to monitor noise generated by strong winds, heavy rain, and hail. Combined with wind speed data, it comprehensively analyzes the impact of strong winds, heavy rain, and hail on the sensitivity of the intrusion alarm detector, and automatically adjusts the detection sensitivity accordingly. The noise sensor 6 is a high-precision capacitive noise sensor with a monitoring range covering 30dB to 130dB and a monitoring resolution of up to 0.1dB. It can accurately distinguish between low, medium, and high levels of wind noise interference, has standard A-weighted noise acquisition capability, and can accurately capture dynamic noise signals such as airport environmental wind noise and aircraft take-off and landing noise. It has no frequency distortion and good monitoring linearity. The infrared monitoring camera 7 is used for visual verification of the scene. The microphone 8 is used for verification of the sound at the scene. The tiltable airport perimeter monitoring poles 1 are distributed and installed at appropriate locations outside the runway threshold, touchdown zone, runway midpoint, runway end, and both sides of the runway end rise and fall strips, as well as at the approach lighting strip entrance and within 5 meters of the physical boundary (within the flight area) of other areas of the flight area; the total height of the tiltable airport perimeter monitoring poles 1 is limited to not penetrating the airspace restriction surface, and the total height within 5 meters of the physical boundary is not less than 3.5 meters to avoid the effect of the physical boundary (standard height 2.5 meters) obstructing the monitoring effect; like Figure 2 As shown, the tiltable airport perimeter monitoring pole 1 includes: a monitoring pole body 1-1 and an internal control box 1-2; the monitoring pole body 1-1 includes: a pole steel reinforcement cage foundation 1-101, a tilting device 1-102, a cable trough column 1-103, and a cable trough cross arm 1-104; the tilting device 1-102 can tilt the monitoring pole body 1-1, except for the pole steel reinforcement cage foundation 1-101, to the airside, facilitating maintenance of the monitoring pole body 1-1 and the equipment installed on it within the flight area; the cable trough column 1-103 and the cable trough cross arm 1-104 are made of metal channel steel, facilitating cable laying and installation of sensors and other equipment; the length of the cable trough cross arm 1-104 is determined according to site requirements.

[0028] The cable tray column 1-103 has a sealed internal space in the middle where electrical devices are installed, namely the built-in control box 1-2. The electrical devices installed in the built-in control box 1-2 include a 1-optical-4-electrical transceiver and a serial-to-network protocol converter. The front end of the built-in control box 1-2 supports the connection of various RS232 / RS485 / RS422 serial port devices and TCP / IP network devices, such as various vibration alarm processors, monitoring sensors, and surveillance cameras. The back end of the built-in control box 1-2 is connected to the perimeter security equipment box 2 or the navigation station network equipment.

[0029] A method for intelligent adjustment of wind direction warning in flight areas, applied to a system for intelligent adjustment of wind direction warning in flight areas, includes: a method for early warning of takeoff and landing risks in flight areas and a method for intelligent adjustment of wind noise in airport perimeter intrusion alarm.

[0030] like Figure 3 As shown, the flight area wind direction takeoff and landing risk early warning method includes the following steps: S1. Distributed network deployment of the runway: Adopting a symmetrical deployment rule for key longitudinal areas of the runway, two sets of tiltable airport perimeter monitoring poles 1 and the front-end monitoring devices, with heights not penetrating the airspace restriction surface, are deployed at appropriate locations outside the runway entrance, touchdown zone, runway midpoint, and runway end on both sides of the riser strip. The spacing between the two sets of tiltable airport perimeter monitoring poles 1 is 150-200 meters. At the same time, within 5 meters of the physical perimeter airspace on both sides of the entrance of the long approach lighting strip at the runway, one set of tiltable airport perimeter monitoring poles 1 and the front-end monitoring devices, with a height of not less than 3.5 meters, are installed. These are connected to the navigation station via network or to the airport intrusion alarm system management platform 3 at the nearest perimeter security equipment box 2, to achieve real-time monitoring and visual verification of crosswind, tailwind, and headwind speed, wind direction, and noise in key areas of the runway. S2. Wind Field Data Acquisition and Filtering: Multiple ultrasonic wind speed and direction sensors deployed on-site synchronously acquire raw wind speed and direction data for key areas across the entire region. A fixed-parameter Kalman filter algorithm is used to perform data noise reduction and smoothing. Preset fixed parameters adapted to airport low-altitude wind field monitoring: process noise covariance Q=0.01, measurement noise covariance R=0.1, and initial state covariance P=1. This parameter configuration adapts to the gradual change characteristics of the wind field, effectively filtering out invalid abnormal clutter data generated by sensor electromagnetic interference, sampling jitter, and instantaneous turbulent airflow, while retaining the effective changes of real wind field abrupt changes such as crosswinds and tailwinds, ultimately outputting stable, continuous, and highly reliable full-area wind field monitoring data. S3. Accurate Wind Speed ​​and Direction Judgment: Using the aforementioned ultrasonic wind speed and direction sensor, based on the standard runway takeoff and landing heading, the system accurately classifies wind field states into three categories: crosswind, tailwind, and headwind according to the angle range between the wind direction and the runway takeoff and landing heading. Each interval is independent and has no overlapping coverage: a wind direction angle within the range of 0°±15° is determined to be a headwind state, a wind direction angle within the range of 60°~120° is determined to be a crosswind state, and a wind direction angle within the range of 180°±15° is determined to be a tailwind state. A multi-point wind speed difference calibration threshold of 0.8 m / s is set. When the wind speed and direction difference between any two sets of monitoring points exceeds this threshold, it is determined that there is an uneven deviation in the local wind field. The wind direction early warning subsystem of the airport intrusion alarm system management platform 3 uses the average value of the effective monitoring data from multiple points as the correction benchmark to complete the local wind field data calibration, effectively eliminating single-point monitoring disturbance deviations and ensuring the accuracy of wind speed and direction state judgment. S4. Aircraft Type-Based Early Warning: For crosswind, tailwind, and headwind anomalies in civil aviation passenger aircraft, cargo aircraft, and general aviation aircraft, early warnings are triggered according to aircraft type; the wind direction early warning subsystem is configured with differentiated takeoff and landing risk early warning thresholds based on different aircraft types, and supports dynamic adjustment of thresholds by accessing flight plan data; after an early warning is triggered, the corresponding aircraft type, risk level, wind field location, wind speed, and wind direction data are simultaneously pushed to the airport security platform duty room, the system sub-control workstation 4 at the air traffic control tower, and other networked platforms via screen pop-ups and audible and visual alarms, realizing multi-terminal linkage early warning prompts; The classification and early warning thresholds in this embodiment are as follows: Civil aviation passenger and cargo aircraft takeoff and landing warning: When the crosswind speed is ≥6 (10.8–13.8 m / s), the tailwind speed is ≥4 (5.5–7.9 m / s), and the headwind speed is ≥7 (13.9–17.1 m / s), a cautious takeoff and landing warning will be triggered. General aviation single-engine light aircraft takeoff and landing warning: When the crosswind speed is ≥5 (8–10.7 m / s), the tailwind speed is ≥3 (3.4–5.4 m / s), and the headwind speed is ≥6 (10.8–13.8 m / s), a cautious takeoff and landing warning is triggered; S5. Early Warning Visualization Verification: When the wind direction early warning subsystem triggers a takeoff and landing risk warning, it will precisely link the infrared monitoring camera 7 and microphone 8 corresponding to the warning point to automatically capture real-time on-site images and retain audio and video recordings for the time period. The wind direction early warning subsystem relies on the dynamic disturbance characteristics between frames of audio and video images for intelligent identification. It comprehensively judges the three-dimensional characteristics of image pixel jitter amplitude, regional disturbance coverage, and continuous disturbance duration to effectively distinguish the real environmental disturbances caused by strong winds. It accurately filters out false early warning events from invalid interference such as instantaneous equipment interference, instantaneous clutter, and passing foreign objects. After verification confirms the existence of a real takeoff and landing risk, it enters the ground-air collaborative early warning push stage. S6. Ground-to-air coordinated early warning push: After receiving the early warning information through the system's sub-control workstation 4 or other networked platforms, the tower air traffic control staff will push standardized airborne early warning prompts to the pilots of aircraft in the approach, take-off and landing phases of the corresponding runways through the airport's dedicated air traffic control communication link. The prompts will clearly inform the pilots of the corresponding aircraft type, the current abnormal wind speed and direction parameters, and the risk level of take-off and landing, guiding them to adjust their flight attitude in a timely manner and make reasonable decisions on whether to go around or land cautiously, thus achieving integrated ground-to-air coordinated safety early warning and control. S7. Wind field data closed-loop archiving: The wind direction early warning subsystem will archive and store all wind field monitoring data, wind speed and wind direction status judgment results, early warning ledger records for different types of wind turbines, video verification vouchers and ground-to-air early warning push records, so as to realize that wind field early warning events are traceable, data is traceable, and operation and maintenance are verifiable.

[0031] like Figure 4As shown, the intelligent noise sensitivity adjustment method for airport perimeter intrusion alarm includes the following steps: A1. Distributed Network Deployment of the Perimeter: Adopting a differentiated deployment rule for the entire perimeter, in areas of the flight zone physical perimeter that are significantly affected by weather throughout the year and have a high false alarm rate for intrusion alarms, one set of the tiltable airport perimeter monitoring pole 1 and the front-end monitoring device are installed every 100 meters along the physical perimeter on average. In other conventional areas of the perimeter, one set of the tiltable airport perimeter monitoring pole 1 and the front-end monitoring device are installed every 300 meters along the physical perimeter on average. The tiltable airport perimeter monitoring pole 1 is installed within 5 meters of the airside of the perimeter and has a height of not less than 3.5 meters. It is connected to the airport intrusion alarm system management platform 3 via a network to realize real-time monitoring and visual verification of wind speed, wind direction, and noise in the perimeter intrusion alarm monitoring area. A2. Baseline Parameter Preset: During the initial deployment and debugging, and after program startup, the system completes a one-time global parameter initialization. The database of the intelligent sensitivity adjustment subsystem for intrusion alarm wind noise on the airport intrusion alarm system management platform 3 is pre-set with five wind force ranges and five noise interference ranges, and pre-matched with five discrete sensitivity levels, establishing a reverse adaptation mechanism between sensitivity and wind noise intensity: the higher the wind noise interference level, the lower the corresponding sensitivity level; the lower the wind noise interference level, the higher the corresponding sensitivity level. On-site, all manual sensitivity level vibration detectors at the front end of the perimeter security system are uniformly locked to the fixed hardware mid-range to prevent on-site... Manual gear shifting disturbance; the intrusion alarm wind noise intelligent sensitivity adjustment subsystem establishes and solidifies five sets of independent software sensitivity threshold template libraries as the standard reference source for long-term dynamic adaptive parameter adjustment of the system. Subsequently, the intrusion alarm wind noise intelligent sensitivity adjustment subsystem will not require repeated initialization configuration during normal operation of the system and normal online operation of the equipment; at the same time, the intrusion alarm wind noise intelligent sensitivity adjustment subsystem solidifies a 45-second anti-shake lag parameter adjustment time to avoid frequent shaking sensitivity adjustment problems, and synchronously solidifies the video linkage verification trigger logic to permanently lock the initial reference state of the system, ensuring the long-term stable operation of the intrusion alarm wind noise intelligent sensitivity adjustment subsystem; The specific parameters for the five levels in this embodiment are as follows: Level 1: Highest sensitivity, vibration threshold 10–30, wind noise ≤ Level 1 / noise ≤ 50dB; Level 2: High sensitivity, vibration threshold 31–50, wind noise level 2 / noise 51–70dB; Level 3: Medium sensitivity, vibration threshold 51–70, wind noise level 3–4 / noise level 71–90dB; Level 4: Low sensitivity, vibration threshold 71–85, wind noise level 5 / noise 91–105dB; Level 5: Lowest sensitivity, vibration threshold 86–100, wind noise ≥ 6 / noise ≥ 106dB; A3. Multi-source data acquisition and filtering: The airport intrusion alarm system management platform 3 collects real-time wind force data, environmental noise data, and perimeter vibration monitoring data from multiple points in the flight area. It adopts a fixed Kalman filter algorithm with the same source and parameters as the wind field monitoring to carry out unified noise reduction processing, effectively eliminating instantaneous wind and sand, turbulent airflow, sampling jitter, and electromagnetic noise interference signals, while retaining the real wind noise environment changes and effective intrusion vibration characteristic signals. It outputs time-aligned, stable, and reliable multi-source monitoring data, providing a unified data foundation for subsequent wind noise collaborative sensitivity adjustment algorithms. A4. Adaptive Anti-shake Sensitivity Adjustment: The system presets five discrete sensitivity levels, with each level range being non-overlapping and having clear boundaries. Based on real-time wind noise conditions, it matches the corresponding sensitivity level according to the reverse adaptation principle; the stronger the wind noise, the lower the sensitivity. Level switching is only performed when the wind noise parameter crosses the level boundary and remains stable for a preset duration. No fine-tuning is performed during the level lock period to avoid frequent parameter adjustments caused by instantaneous disturbances. Under complex wind noise coupling conditions, it adapts according to the principle of prioritizing high interference, and parameter adaptation is completed throughout the process through software template switching without the need to modify the front-end hardware. A5. Cross-verification of Intrusion Behavior: When the intrusion alarm wind noise intelligent sensitivity adjustment subsystem identifies abnormal boundary vibration and triggers an alarm based on the five sensitivity levels matching results, it accurately links the infrared monitoring camera and microphone corresponding to the alarm point for collaborative verification; relying on the three-dimensional dynamic characteristics of audio and video image pixel jitter amplitude, regional disturbance coverage, and continuous disturbance duration, and combining real-time wind noise level and corresponding sensitivity level information for cross-verification, it accurately distinguishes between real intrusion behavior and false alarms caused by environmental interference from strong winds, noise, and external object disturbances; at the same time, the system continuously optimizes the wind noise matching standard and level switching rules based on the verification results; A6. Intrusion Alarm Information Push: After a genuine intrusion is confirmed, alarm information is simultaneously pushed to the airport security platform duty room, the system sub-control workstation of the air traffic control tower, and other networked platforms, triggering screen pop-ups and audible and visual alarms to achieve multi-terminal linkage early warning prompts; A7. Closed-loop archiving of monitoring data: The intrusion alarm wind noise intelligent sensitivity adjustment subsystem collects in real time the wind field status parameters, wind noise level data, sensitivity adaptive adjustment logs, equipment operation status data, intrusion anomaly alarms and video verification voucher data of the entire domain, and archives and stores all operation and maintenance ledgers in full, so as to realize remote real-time monitoring of the wind noise monitoring status of the flight area, traceable parameter iteration records, and auditable abnormal events, ensuring the long-term intelligent and stable operation of the system.

[0032] The present invention provides an intelligent sensitivity adjustment system and method for wind direction early warning in flight zones, which discloses the following beneficial effects: 1. The design adopts a wind speed and direction warning system that differentiates between aircraft models. It can dynamically adjust the takeoff and landing risk warning threshold by accessing flight plan data through a reserved software interface, accurately match the wind resistance capabilities of different aircraft models, effectively avoid differentiated takeoff and landing risks, and significantly improve the accuracy and reliability of wind field takeoff and landing warnings.

[0033] 2. An innovative gear-based adaptive anti-shake and sensitivity adjustment mechanism can adapt to complex wind noise environments in real time, significantly reducing the false alarm rate of the perimeter boundary, reducing the frequency of manual parameter adjustment, and improving the stability of system operation.

[0034] 3. Construct a closed-loop control process for alarm verification, interference callback, and multi-terminal linkage to effectively filter false alarms, achieve rapid early warning of real intrusion events, and enhance perimeter security response efficiency.

[0035] 4. The entire process adopts a pure software strategy to achieve intelligent control, without the need to modify the front-end hardware. It has strong engineering adaptability, is easy to implement, and has low modification costs.

[0036] 5. It integrates wind field early warning, boundary sensitivity adjustment, and data archiving into a unified architecture, ensuring full traceability and auditability, and meeting the requirements for safe and compliant operation of civil aviation.

[0037] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for early warning of takeoff and landing risks in flight zones based on wind direction, characterized in that, Includes the following steps: S1. Distributed network deployment of runways: Multiple sets of front-end monitoring devices are symmetrically distributed on both sides of key areas such as runway entrance, touchdown zone, runway midpoint, runway end, and approach lighting strip entrance in the flight area, and the system is networked and connected to the airport intrusion alarm system management platform to realize real-time monitoring and visual verification of crosswind, tailwind, and headwind speed, wind direction, and noise in key areas of the runway. S2. Wind field data acquisition and filtering: Real-time acquisition of raw wind speed and direction data from multiple points in the flight area, noise reduction and smoothing processing through a preset filtering algorithm, elimination of instantaneous interference data, retention of effective abrupt change signals, and output of stable and continuous wind field monitoring data. S3. Accurate wind speed and direction identification: Based on the standard take-off and landing heading of the airport runway, three independent wind field states are divided into crosswind, tailwind and headwind. Local deviations are calibrated by multi-point monitoring data to eliminate single-point monitoring errors and accurately identify wind speed and direction. S4. Aircraft Type Classification Warning: For abnormal crosswind, tailwind, and headwind conditions of civil aviation passenger aircraft, cargo aircraft, and general aviation aircraft, warnings are triggered according to aircraft type; The wind direction warning subsystem is configured with differentiated takeoff and landing risk warning thresholds according to different aircraft models, and supports dynamic adjustment of thresholds by accessing flight plan data. Once the warning is triggered, the warning information will be simultaneously pushed to the airport security platform duty room and the air traffic control tower workstation. S5. Visual verification of early warning: After triggering a takeoff and landing risk warning, the system accurately links with on-site audio and video equipment to visually verify the warning scenario, identify and filter false warnings, and after verification confirms the existence of a real takeoff and landing risk, execute the subsequent ground-to-air early warning push process; S6. Ground-to-air coordinated early warning push: Air traffic controllers in the tower can push airborne early warning prompts to aircraft in the runway approach, take-off and landing phases through the dedicated air traffic control communication link, informing them of abnormal wind speed and direction information and take-off and landing risk levels for the corresponding aircraft type, and assisting pilots in flight decision-making; S7. Wind Farm Data Closed-Loop Archiving: Fully archive and store all wind farm monitoring data, status judgment results, wind turbine type early warning ledgers, verification vouchers, and ground-to-air early warning push records to achieve traceable and auditable operation and maintenance management of early warning events.

2. A method for intelligently adjusting wind noise sensitivity in airport perimeter intrusion alarms, characterized in that, Includes the following steps: A1. Distributed Network Deployment of the Perimeter: Multiple sets of front-end monitoring devices are deployed in a differentiated manner within 5 meters of the airside of the physical perimeter of the flight area and the system is networked and connected to the airport intrusion alarm system management platform to realize real-time monitoring and visual verification of wind speed, wind direction and noise in the perimeter intrusion alarm monitoring area. A2. Preset reference parameters: The system has fixed multi-level wind noise interference ranges and corresponding monitoring sensitivity references. It adopts a reverse adaptation mechanism between wind noise intensity and monitoring sensitivity. The stronger the wind noise interference, the lower the monitoring sensitivity. The front-end hardware level is locked and the software sensitivity template is stored to provide a reference for adaptive sensitivity adjustment. A3. Multi-source data acquisition and filtering: Real-time acquisition of multi-source environmental data such as wind speed, wind direction, noise, and perimeter vibration in the flight area. The data is then processed by a unified filtering algorithm to reduce noise, eliminate instantaneous environmental interference, and retain real environmental changes and effective intrusion detection signals. A4. Adaptive Anti-shake Sensitivity Adjustment: The system presets five discrete sensitivity levels, with each level range not overlapping and having clear boundaries. Based on the real-time wind noise status, it matches the corresponding sensitivity level according to the reverse adaptation principle; the stronger the wind noise, the lower the sensitivity. The level switch is only performed when the wind noise parameter crosses the level boundary and remains stable for a preset duration. No fine-tuning is performed during the level lock period to avoid frequent parameter adjustments caused by instantaneous disturbances. Under complex wind noise coupling conditions, it adapts according to the principle of prioritizing high interference, and parameter adaptation is completed throughout the process through software template switching without the need to modify the front-end hardware. A5. Cross-verification of intrusion behavior: After an intrusion alarm is triggered, the system combines the matching results of five sensitivity levels and cross-verifies the data from multiple sources and video footage features to distinguish between real intrusion behavior and false alarms caused by wind noise interference, thus filtering out false alarms. At the same time, the system continuously optimizes the wind noise matching standard and the level switching rules based on the verification results. A6. Intrusion Alarm Information Push: After a genuine intrusion is confirmed, alarm information is simultaneously pushed to the airport security platform duty room, the system sub-control workstation of the air traffic control tower, and other networked platforms, triggering screen pop-ups and audible and visual alarms to achieve multi-terminal linkage early warning prompts; A7. Closed-loop archiving of monitoring data: Collect and archive wind noise monitoring data, sensitivity adjustment logs, equipment operation data and alarm verification vouchers to achieve system parameter iteration and traceable auditing of abnormal events.

3. The method according to claim 1 or 2, characterized in that, It also includes an intelligent sensitivity adjustment system for wind direction early warning in the flight area. The system includes: a front-end monitoring device, an airport intrusion alarm system management platform, and a system sub-control workstation. The front-end monitoring device includes a wind speed and wind direction sensor, a noise sensor, an infrared monitoring camera, and a microphone. The front-end monitoring device is installed on the airport perimeter monitoring poles and is deployed in key areas of the flight area runway and key areas of the perimeter, and is connected to the same network and the management platform. The airport intrusion alarm system management platform includes a wind direction early warning subsystem and a wind noise intelligent sensitivity adjustment subsystem, which are used to execute the takeoff and landing risk early warning method described in claim 1 and the perimeter intrusion alarm wind noise intelligent sensitivity adjustment method described in claim 2, respectively. The airport intrusion alarm system management platform has a reserved software interface that can access airport flight plan data and dynamically adjust the takeoff and landing risk early warning threshold according to parameters such as takeoff and landing time and aircraft type and weight. It can also be integrated with airport ground monitoring system data to accurately analyze the wind field status of the flight area. It can also be connected to the perimeter security system intrusion alarm detectors via network and linked with the airport perimeter security platform.

4. The intelligent wind direction early warning system for flight zones according to claim 3, characterized in that, The total height of the tiltable airport perimeter monitoring poles is limited to not penetrating the airspace restriction surface, and shall not be less than 3.5 meters within 5 meters of the physical boundary airspace.

5. The intelligent wind direction early warning system for flight zones according to claim 3, characterized in that, Both methods employ pure software control, requiring no modification to the front-end hardware; by using level-based sensitivity adjustment to suppress frequent parameter fluctuations, they reduce system modification and maintenance costs, achieving integrated intelligent control of flight area wind field safety early warning and perimeter security and anti-interference.

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