An unattended system based on a helicopter airport

Abstract

The application discloses an unattended system based on a helicopter airport, and relates to the technical field of unattended airports, and comprises a collection module, which is used for collecting various original data of the helicopter airport; a processing module, which is connected with the collection module and is used for pre-processing the collected original data to obtain initial data. The unattended system based on the helicopter airport collects and optimizes the original data comprehensively, builds a data foundation for automatic decision-making, carries out risk assessment and decision-making according to the data, realizes automatic decision-making adjustment in three aspects of unmanned aerial vehicle tasks, airport facility maintenance and environmental threat response, and automatically triggers a backup scheme and executes the backup scheme when a fault or an anomaly occurs in the system, so that the automaticity of airport emergency treatment and operation continuity are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned airports, in particular to an unmanned system for helicopter airports. Background Art

[0002] With the widespread adoption of drone technology across multiple industries, demands for increased convenience, safety, and automation are rising. However, traditional on-site manual control or monitoring operations are inefficient and costly for large-scale missions. While drones are popular for their flexibility and maneuverability in areas such as infrastructure inspection, agricultural monitoring, and logistics distribution, they are hindered by issues such as short flight range, data transmission delays, and complex operations. Against this backdrop, the concept of drone-attended heliports has emerged. These integrate multiple functions, including automated control and remote management, enabling drones to complete missions more independently. Simultaneously, socioeconomic development, particularly advances in information technologies such as the Internet of Things, big data, and cloud computing, is supporting the intelligent management of unmanned heliports. Unmanned heliports also reduce carbon emissions and meet sustainable development requirements. Despite the increasing maturity of drone technology and its expanding application, existing operating models fail to meet the demand for automation. Enabling unmanned operations is crucial to addressing this issue. Summary of the Invention

[0003] (1) Technical problems solved

[0004] In view of the shortcomings of the existing technology, the present invention provides an unmanned system for helicopter airports, which solves the problem that the existing operation mode cannot meet the automation requirements, and realizing unmanned operation becomes the key to solving the problem.

[0005] (2) Technical solution

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an unmanned system for a heliport, comprising:

[0007] Acquisition module, used to collect various raw data of the helicopter airport;

[0008] A processing module, connected to the acquisition module, is used to pre-process the collected raw data to obtain initial data; the pre-processing includes data cleaning and format conversion, removing noise and outliers in the raw data, and converting analog signals in the raw data into digital signals;

[0009] The decision-making module generates risk adjustment recommendations based on the results of the analysis module in the processing module, combined with the current airport resource situation and the airport's operational processes. The decision-making module is also used to provide backup plans in the event of system failures or abnormal conditions, including emergency landing procedures, drone failure handling procedures, and emergency maintenance measures for airport facilities.

[0010] The decision module, based on the risk adjustment suggestion, combines the preset safety threshold, historical experience and analysis results to determine whether the task of the unmanned aerial vehicle needs to be adjusted, the airport facility needs to be maintained or the standby scheme needs to be started, and obtains a determination result.

[0011] The processing module further comprises:

[0012] The analysis module is configured to analyze the initial data, extract representative features therefrom, and perform comprehensive risk analysis in combination with historical data to obtain a risk analysis result.

[0013] The decision module further comprises:

[0014] The feedback module feeds back the risk decision result to the airport management personnel and maintenance technical personnel, displays the risk decision result information on a display screen and a mobile terminal application, and provides an interactive function.

[0015] Preferably, the process of collecting various types of original data of the helicopter airport by the collecting module comprises: for the flight data of the unmanned aerial vehicle, the power sensor and the speed sensor on the unmanned aerial vehicle are used to obtain the power data and the flight speed of the unmanned aerial vehicle, respectively, and the positioning base station in the airport is used to obtain the position information of the unmanned aerial vehicle in real time; for the runway condition in the state information of the airport facility, a runway condition monitoring sensor is used to monitor the condition on the runway in real time, including obstacles, icing areas, cracks, potholes, foreign matters, pressure changes and metal foreign matters, for the state of the navigation equipment, the corresponding state information is obtained in real time through the self-checking system of the navigation equipment, the lighting system and the communication system; for the meteorological data of the environment where the airport is located, the anemometer and the wind vane are used to measure the wind speed and the wind direction in real time, the temperature and the humidity are collected in real time through the temperature and humidity sensor, the atmospheric turbulence is monitored and collected in real time using the laser radar, the cloud information is obtained in real time through the ceilometer and the cloud cover meter in combination with manual observation; wherein the runway condition monitoring sensor is composed of a visual sensor, an infrared sensor, a laser radar, an ultrasonic sensor, a pressure sensor and an electromagnetic induction sensor.

[0016] Preferably, the analysis module is used to analyze the initial data, extract representative features therefrom, and conduct a comprehensive risk analysis in combination with historical data to obtain a risk analysis result, and the process includes: based on domain knowledge and experience and in combination with feature importance evaluation, screening out from the initial data representative features highly relevant to the flight state of the unmanned aerial vehicle, the operating state of the airport facility, and the influence of the environment on the operation, i.e., environmental representative features, operating state representative features, and helicopter performance representative features; using the relationship information in the knowledge base, analyzing the causal relationship between the representative features, and integrating single representative features into a multi-dimensional comprehensive evaluation system; quantitatively processing the screened representative features, dividing the environmental parameters into low, medium, and high levels according to wind speed, assigning corresponding numerical values, and standardizing the operating state data, and encoding the quantified representative features; according to the importance and influence degree of the representative features, assigning corresponding weights to each representative feature; based on the screened representative features and the assigned weights, combining a neural network model to train a comprehensive evaluation model for predicting key features and potential risks in system operation; after preprocessing, extracting representative features, and quantitatively encoding newly collected helicopter and airport operation data, inputting the data into the analysis module, using the trained comprehensive evaluation model to intelligently analyze the data, extracting key information and patterns related to system operation, and identifying potential operation abnormalities; predicting the risk situation in system operation according to the analysis result, and outputting the risk analysis result, including the probability of potential failure and the time window for expected emergency treatment.

[0017] Preferably, different weights are assigned to different dimension representative features according to the risk analysis result output by the analysis module; the risk analysis result output by the analysis module is combined with the environmental representative feature score, the operating state score, and the helicopter performance score to calculate a system risk evaluation coefficient for evaluating the risk emergency degree of the system; different risk levels are divided in combination with the system risk emergency degree, including a high-risk level, a medium-risk level, a low-risk level, and a normal-risk level, and corresponding evaluation thresholds are matched for each risk level; according to the system risk level, a corresponding suggestion is matched from a predefined decision suggestion strategy library, and the decision suggestion strategy library includes maintenance schemes, troubleshooting suggestions, and emergency response measures for different risk levels.

[0018] Preferably, the process of assigning different weights to different dimension representative features includes: for environmental parameters deviating from the normal range, when the wind speed exceeds 25 meters per second, the atmospheric pressure deviates from the standard atmospheric pressure (1013.25 hPa) by more than ± 10 hPa, a weight coefficient of 0.4-0.5 is assigned according to the incidence of high-risk situations corresponding to past risk data; for abnormal key risk parameters, when the helicopter fuel is less than 20% of the total fuel capacity or the remaining fuel is insufficient to support at least 30 minutes of emergency return and emergency landing operation, it is considered that the fuel is below the safe level, in addition, if the fuel flow fluctuation is detected by the fuel monitoring system, the fuel pressure is lower than the minimum threshold set by the system 5 bar, the engine temperature exceeds 120 degrees Celsius or is lower than 60 degrees Celsius, the oil pressure is lower than 4 bar or higher than 15 bar, the values detected by the key sensors (such as attitude sensors, speed sensors) deviate from the normal range by more than ± 10%; In addition, if cracks are detected on the blades, the fuselage is deformed, or the braking system and navigation system fail, it will be considered as an abnormal mechanical state, and a weight of 0.3-0.4 will be assigned according to its impact on system safety; For helicopter performance characteristics, including speed deviation and position deviation, when the actual flight speed of the helicopter exceeds 10% of its normal operating speed or is less than 10% of its normal operating speed, it is considered that the speed deviates, and when the actual position of the helicopter deviates from the target position set by the navigation system by more than 50 meters horizontally or by more than 20 meters vertically, it is considered that the position deviates, and a weight of 0.2-0.3 is assigned according to the risk incidence corresponding to the historical data; Ensure that the sum of the weight coefficients of each representative feature is 1.

[0019] Preferably, the calculation expression of the risk assessment coefficient is:

[0020] ;

[0021] Wherein: C is the risk assessment coefficient, the value range is between 0 and 1, the value is closer to 1, indicating that the system risk is more urgent; W1, W2, W3 are the weight coefficients of the environmental representative feature, the risk state representative feature and the helicopter performance representative feature respectively; S1, S2, S3 are the environmental assessment score, the risk state score and the helicopter performance score respectively; R is the reference minimum value of each representative feature score; k is the adjustment coefficient, which is a constant greater than 0, used to adjust the shape of the exponential function curve; The value of the risk assessment coefficient is matched with the risk evaluation threshold preset by the risk level to match the four risk levels: high-risk level: 0.75≤C≤1.0; Medium-risk level: 0.5≤C<0.75; Low-risk level: 0.25≤C<0.5; Normal risk level: 0≤C<0.25.

[0022] Preferably, the decision module comprises:

[0023] receive the results from the analysis module, including the system risk level, risk assessment coefficient, and related environmental parameters, risk state information, and comprehensively analyze the current airport resource situation, including runway usage status, helicopter parking situation, and availability of maintenance equipment; according to the airport operation process, match the system risk level with the corresponding operation strategy to determine the maintenance measures, risk adjustment, or emergency response steps to be taken; based on the analysis results, the decision module generates risk adjustment suggestions and sends the decision suggestions to relevant management personnel, including airport operation management personnel and maintenance technical personnel, through the internal communication system; after receiving the decision suggestions, the management personnel check and adjust according to the actual situation of the airport, and once the decision suggestions are confirmed, the relevant risk adjustment or maintenance measures will be immediately implemented.

[0024] Preferably, in the decision module, based on the risk-adjusted recommendations, combined with the preset safety threshold, historical experience and risk analysis results, the judgment result is obtained, the process includes: through the authentication mode of username plus password plus digital certificate, through security identity verification and permission verification, accessing the database storing the safety threshold, and according to the preset query condition or API interface, retrieving the required safety threshold from the database, parsing and extracting the numerical value or range of the safety threshold, at the same time, checking the data to ensure the integrity and accuracy of the data, avoiding the use of outdated or incorrect safety threshold, and then storing the checked safety threshold data in the internal storage of the decision module, at the same time, the decision module will regularly check whether the safety threshold in the database is updated, to ensure that the latest safety standard is always used for judgment, the safety threshold includes the power safety range of the unmanned aerial vehicle, the flight height limit, the speed limit, the maintenance period of the airport facility, and the safety standard of the environmental condition; review historical experience data, including past failure cases, maintenance records and successful strategies for dealing with specific situations; set the unmanned aerial vehicle judgment logic, including: comparing the flight status report of the unmanned aerial vehicle with the preset safety threshold, if the unmanned aerial vehicle is found to be insufficient in power or deviating from the predetermined flight route, judging whether the task needs to be adjusted, including shortening the flight time, changing the flight route or emergency landing; generating the judgment result of the unmanned aerial vehicle, that is, the adjustment instruction of the unmanned aerial vehicle task; set the airport facility judgment logic, including: according to the maintenance suggestion and historical maintenance record of the airport facility, evaluating whether the current state of the airport facility is consistent with the preset maintenance period or standard, if the facility has a failure risk or has reached the maintenance period, judging whether immediate maintenance or preventive maintenance plan needs to be arranged; generating the judgment result of the airport facility, that is, the maintenance task list of the airport facility; set the environmental judgment logic, including: combining the environmental adaptability measures and the current environmental conditions (such as severe weather), if the environment poses a significant threat to the operation, judging whether the standby scheme needs to be started, including using the standby runway, adjusting the flight time or taking other emergency measures, generating the environmental judgment result, that is, the start-up notice of the standby scheme, and implementing the standby scheme based on the start-up notice of the standby scheme.

[0025] Preferably, the process of implementing the backup solution includes: based on the monitoring devices installed in the acquisition module, continuously monitoring the flight status of the unmanned aerial vehicle, the operation status of the airport facility and the environmental parameters, and triggering the backup solution in the decision module immediately when detecting a fault or abnormal signal; according to the type of detected fault or abnormality, selecting the most suitable backup solution from the predefined backup solution library, which includes emergency landing procedures, unmanned aerial vehicle fault handling processes and airport facility emergency maintenance measures; based on the selected backup solution, corresponding execution preparation is carried out, including starting the corresponding control system, deploying necessary maintenance personnel and backup equipment; at the same time, notifications are sent to relevant personnel to ensure that they are aware of the current situation and are prepared; according to the content of the backup solution, relevant personnel are guided to execute the corresponding control strategy and operation process; during the execution of the backup solution, the state and progress of the system are continuously monitored, and if any new problems or adjustment of the solution are found, the decision module immediately adjusts and notifies the relevant personnel, and at the same time, feedback data during the execution of the backup solution is collected for subsequent optimization and improvement of the solution; when the backup solution is successfully executed and the problem is solved, relevant data and information are recorded, and the execution of the current solution is ended; subsequently, the execution effect of the solution is evaluated to obtain an evaluation result, including the efficiency of solving the problem and the rationality of resource use; the evaluation result will be used for optimization and improvement of subsequent solutions to improve the stability and reliability of the system; after ensuring the stability of the system, the decision module guides the system to gradually recover to the normal operation state, and at the same time, notifications are sent to relevant personnel to ensure that they are aware of the current state of the system and prepare for subsequent work.

[0026] Preferably, the feedback module includes: obtaining the final risk decision result from the decision module, including risk assessment, recommended maintenance measures, predicted adjustment time and evaluation result; through the display screen in the airport and the mobile terminal application, relevant information of the risk decision result is displayed to relevant personnel, and the airport management personnel view on the control center or mobile device, and the maintenance technical personnel obtain the risk information through the designated query interface; the airport management personnel and the maintenance technical personnel confirm, adjust or supplement the risk decision result through the interactive interface, and when the management personnel or the technical personnel confirm, adjust or supplement the risk decision result, the feedback opinions are received and processed, and the risk information of the system is updated; according to the feedback opinions, the system dynamically adjusts the operation strategy and the decision suggestion to ensure that the risk state of the system is consistent with the actual demand, and the flexibility and response ability of the system are improved.

[0027] (Three) beneficial effects

[0028] The application provides an unattended system based on a helicopter airport. The following beneficial effects are provided:

[0029] The unmanned system based on the helicopter airport, through the cooperation of the acquisition module and the processing module, comprehensively acquires and optimizes the original data, and builds a data foundation for automatic decision-making; then, through the close cooperation of the analysis module and the decision module, risk assessment and decision-making are carried out according to the data, automatic decision-making adjustment is realized in three aspects of unmanned aerial vehicle task, airport facility maintenance and response to environmental threats; then, when the system fails or abnormity occurs, the standby scheme is automatically triggered and executed, ensuring the automation of airport emergency processing and the continuity of operation; in addition, the feedback module collects personnel opinions, optimizes the operation strategy, enhances the flexibility of the system, so that the automatic operation can accurately meet the real-time needs of the airport, and the automatic operation level of the airport can be improved in multiple ways. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 It is a framework schematic diagram of the unmanned system of the application.

[0031] Figure 2 It is a flowchart of the application. DETAILED DESCRIPTION

[0032] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, not all. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the application.

[0033] Please refer to Figure 1 and Figure 2 The application provides a technical solution: an unmanned system based on a helicopter airport, comprising:

[0034] The acquisition module is used for acquiring various types of original data of the helicopter airport.

[0035] The processing module is connected with the acquisition module and is used for preprocessing the acquired original data to obtain initial data; the preprocessing includes data cleaning and format conversion, removing noise and abnormal values in the original data, and converting analog signals in the original data into digital signals.

[0036] The decision module generates risk adjustment suggestions according to the results of the analysis module in the processing module, in combination with the current resource situation of the airport and the operation process of the airport; the decision module is also used for providing a standby scheme when the system fails or abnormity occurs, including an emergency landing program, an unmanned aerial vehicle fault handling process and an airport facility emergency maintenance measure.

[0037] The decision module further judges whether the task of the unmanned aerial vehicle needs to be adjusted, the airport facility needs to be maintained or a backup plan needs to be started based on the risk adjustment suggestion, the preset safety threshold, historical experience and analysis results, and obtains a judgment result.

[0038] The processing module further comprises:

[0039] The analysis module is configured to analyze the initial data, extract representative features therefrom, and perform comprehensive risk analysis in combination with historical data to obtain a risk analysis result.

[0040] The decision module further comprises:

[0041] The feedback module feeds back the risk decision result to the airport management personnel and maintenance technical personnel, displays the risk decision result information on a display screen and a mobile terminal application, and provides an interactive function.

[0042] The process of collecting various types of original data of the helicopter airport by the collection module includes: for the flight data of the unmanned aerial vehicle, the power sensor and the speed sensor on the unmanned aerial vehicle are used to obtain the power data and the flight speed of the unmanned aerial vehicle respectively, and the positioning base station in the airport is used to obtain the position information of the unmanned aerial vehicle in real time; for the runway condition in the state information of the airport facility, a runway condition monitoring sensor is used to monitor the condition on the runway in real time, including obstacles, icing areas, cracks, potholes, foreign matters, pressure changes and metal foreign matters, for the state of the navigation equipment, the corresponding state information is obtained in real time through the self-checking system of the navigation equipment, the lighting system and the communication system; for the meteorological data of the environment where the airport is located, the anemometer and the wind vane are used to measure the wind speed and the wind direction in real time, the temperature and humidity sensor is used to collect the temperature and humidity in real time, the laser radar is used to monitor and collect the atmospheric turbulence in real time, the cloud height instrument and the cloud cover meter are used to obtain the cloud information in real time in combination with manual observation; wherein the runway condition monitoring sensor is composed of a visual sensor, an infrared sensor, a laser radar, an ultrasonic sensor, a pressure sensor and an electromagnetic induction sensor.

[0043] It needs to be further explained that in the specific implementation process, the atmospheric turbulence includes turbulence intensity and turbulence frequency, in the turbulence intensity, the atmospheric turbulence will cause the flight of the unmanned aerial vehicle to be unstable, increase the difficulty of flight control, especially around complex terrain and buildings, turbulence is more common; in the turbulence frequency, frequent turbulence will increase the energy consumption of the unmanned aerial vehicle, shorten the battery endurance time, and also may cause damage to the structure of the unmanned aerial vehicle;

[0044] The cloud condition includes the cloud layer height and the cloud layer thickness, in the cloud layer height, low clouds will affect the take-off and landing of the unmanned aerial vehicle, and high clouds will affect the visibility and communication signals during flight; in the cloud layer thickness, thick cloud layers will increase the flight resistance, affect the flight performance of the unmanned aerial vehicle, and also hide potential meteorological risks such as thunderstorms.

[0045] It needs to be further explained that in the specific implementation process, the visual sensor uses a high-definition camera to capture high-definition images of the runway surface for detecting foreign objects, cracks, water accumulation, and snow on the runway, identifying obstacles on the runway such as birds, vehicles, and tools, and ensuring the cleanliness and safety of the runway; the infrared sensor uses a thermal imaging camera to detect the temperature distribution of the runway surface through thermal imaging technology, identify snow, water accumulation, and ice layer, and discover icing areas on the runway in advance for timely deicing; the laser radar uses a laser scanner to scan the runway surface with a laser beam to generate three-dimensional point cloud data, detect the flatness, cracks, and potholes of the runway, and discover potential safety hazards such as runway settlement and cracks; the ultrasonic sensor uses a distance sensor to measure the distance between the runway surface and the sensor through ultrasonic reflection principles to detect foreign objects on the runway such as small tools and debris; the pressure sensor uses a ground pressure sensor installed on the runway surface or underground to detect changes in pressure on the runway, identify heavy objects (such as vehicles and large equipment) that press on the runway, prevent heavy vehicles from entering the runway, and ensure the structural safety of the runway; the electromagnetic induction sensor uses a metal detector to detect metal foreign objects on the runway such as screws and tools to prevent damage to the unmanned aerial vehicle caused by metal foreign objects, ensure that the runway surface is free of metal foreign objects before the unmanned aerial vehicle takes off or lands, and improve the safety of takeoff and landing.

[0046] In the processing module, the process of preprocessing the collected raw data to obtain initial data includes: first, through the communication interface (such as network interface, serial port), receiving the raw data from the acquisition module, then through the data cleaning algorithm integrated in the software of the processing module, removing the noise and outliers in the raw data, specifically, through smoothing filter, median filter to remove high-frequency noise or random fluctuations in the data, then use 3σ principle to detect outliers, and according to the actual situation, select to delete, replace or correct outliers, then based on the cooperation of ADC and data format conversion algorithm, the analog signal (such as the output of temperature, humidity and other sensors) is converted by analog-to-digital converter ADC, and the corresponding data is converted into digital signal according to the unified format standard such as timestamp, data precision, unit, then the digital signal is checked through checksum, and the initial data is obtained and stored in the database.

[0047] The process of analyzing the initial data to extract representative features and conducting a comprehensive risk analysis combined with historical data to obtain a risk analysis result includes: based on domain knowledge and experience and combined with feature importance evaluation, screening out highly relevant representative features from the initial data, which are related to the flight state of the unmanned aerial vehicle, the operation state of the airport facility, and the influence of the environment on the operation, respectively, the environmental representative feature, the operation state representative feature, and the helicopter performance representative feature; using the relationship information in the knowledge base, analyzing the causal relationship between each representative feature, and synthesizing a single representative feature into a multi-dimensional comprehensive evaluation system; quantizing the screened representative features, dividing the environmental parameters into low, medium and high levels according to the wind speed, assigning corresponding numerical values, and standardizing the operation state data, and encoding the quantized representative features; according to the importance and influence degree of the representative features, assigning corresponding weights to each representative feature; based on the screened representative features and the assigned weights, combining a neural network model to train a comprehensive evaluation model for predicting key features and potential risks in system operation; after preprocessing, extracting representative features and quantizing and encoding the newly collected helicopter and airport operation data, inputting them into the analysis module, using the trained comprehensive evaluation model to intelligently analyze the data, extracting key information and patterns related to system operation, and identifying potential operation abnormalities; predicting the risk situation in system operation according to the analysis result, and outputting the risk analysis result, including the probability of potential failure and the time window for emergency treatment.

[0048] It should be further pointed out that in the specific implementation process, the statistical method is used to analyze the correlation of the representative features to the analysis structure obtained by subsequent evaluation, and the value features highly related to the analysis result are screened out, which are the flight state value feature of the unmanned aerial vehicle, the operation state value feature of the airport facility, and the operation influence value feature; then based on the flight state value feature of the unmanned aerial vehicle, combining historical data, using trajectory matching algorithm and power consumption model to evaluate the flight state of the unmanned aerial vehicle, including whether to deviate from the predetermined route and whether the power is sufficient, to obtain the flight state evaluation result of the unmanned aerial vehicle; using sensor data, historical maintenance records and airport facility operation state value features to evaluate the operation state of the airport facility, including whether the runway is flat and whether the navigation equipment is accurate, to obtain the operation state evaluation result of the airport facility;

[0049] Combining meteorological data, historical weather influence on flight safety records and operation influence value features, evaluating whether the bad weather affects the flight safety, obtaining the influence of the environment on the operation evaluation result; based on the flight state evaluation result of the unmanned aerial vehicle, the operation state evaluation result and the influence of the environment on the operation evaluation result, the process of generating the risk analysis result is joined, and the risk analysis result also includes the flight state report of the unmanned aerial vehicle, the maintenance suggestion of the airport facility, and the environmental adaptability measure;

[0050] According to the risk analysis result output by the analysis module, different weights are given to different dimension representative features; the risk analysis result output by the analysis module is combined with the environmental representative feature score, the running state score and the helicopter performance score to calculate a system risk assessment coefficient, and the risk emergency degree of the system is evaluated; combined with the system risk emergency degree, different risk levels are divided, including a high-risk level, a medium-risk level, a low-risk level and a normal-risk level, and corresponding evaluation thresholds are matched for each risk level; according to the system risk level, a corresponding suggestion is matched from a predefined decision suggestion strategy library, and the decision suggestion strategy library includes maintenance schemes, fault troubleshooting suggestions and emergency response measures for different risk levels.

[0051] The process of giving different weights to different dimension representative features includes: for the environmental parameter seriously deviating from the normal range, when the wind speed exceeds 25 meters per second and the air pressure deviates from the standard atmospheric pressure (1013.25 hPa) by more than ±10 hPa, a weight coefficient of 0.4-0.5 is given according to the incidence of high-risk conditions in the past risk data; for key risk parameters, when the helicopter fuel is less than 20% of the total fuel capacity or the remaining fuel is insufficient to support at least 30 minutes of emergency return and alternate landing operation, it is considered that the fuel is below the safety level, in addition, if the fuel flow monitoring system detects abnormal fluctuations in fuel flow, the fuel pressure is lower than the minimum threshold set by the system by 5 bars, the engine temperature exceeds 120 degrees Celsius or is lower than 60 degrees Celsius, the oil pressure is lower than 4 bars or higher than 15 bars, the values detected by key sensors (such as attitude sensors and speed sensors) deviate from the normal range by more than ±10%, and any fault code triggered in the system self-checking process; in addition, if cracks are detected on the blades, the fuselage is deformed, or the braking system and navigation system fail, it will also be considered as a mechanical state anomaly, and a weight of 0.3-0.4 will be given according to its impact on system safety; for helicopter performance features, including speed deviation and position deviation, when the actual flight speed of the helicopter exceeds its normal operating speed by more than 10% or is lower than the normal operating speed by more than 10%, it is considered to be speed deviation, in addition, if the instantaneous change rate of flight speed exceeds 30 kilometers per hour (km / h) per minute, it is also considered to be speed deviation, when the horizontal distance between the actual position of the helicopter and the target position set by the navigation system exceeds 50 meters, or the vertical height deviation exceeds 20 meters, it is considered to be position deviation, in addition, if the deviation between the heading angle of the helicopter and the predetermined heading angle exceeds 15 degrees, it is also considered to be position deviation, and a weight of 0.2-0.3 is given according to the risk incidence corresponding to the historical data; the sum of the weight coefficients of each representative feature is ensured to be 1, and each weight coefficient is adjusted to reflect its importance in comprehensive evaluation.

[0052] The calculation expression of the risk assessment coefficient is:

[0053] ;

[0054] Wherein: C is the risk assessment coefficient, the value range is between 0 to 1, the value is closer to 1, indicating the system risk emergency degree is higher; W1, W2, W3 are the weight coefficients of the environmental representative features, risk state representative features and helicopter performance representative features respectively; S1, S2, S3 are the environmental assessment score, risk state score and helicopter performance score respectively; R is the reference minimum value of each representative feature score; k is the adjustment coefficient, which is a constant greater than 0, used to adjust the shape of the exponential function curve; the value of the risk assessment coefficient is matched with the risk evaluation threshold of the risk level preset, and four risk levels are matched, which are: high-risk level: 0.75≤C≤1.0; medium-risk level: 0.5≤C<0.75; low-risk level: 0.25≤C<0.5; normal risk level: 0≤C<0.25.

[0055] The decision module includes: receiving the results from the analysis module, including the system risk level, the risk assessment coefficient and the related environmental parameters, risk state information, and comprehensively analyzing the current airport resource situation, including the runway use state, the helicopter parking situation, the availability of maintenance equipment; according to the airport operation process, the system risk level is matched with the corresponding operation strategy to determine the maintenance measures, risk adjustment or emergency response steps to be taken; based on the analysis result, the decision module generates risk adjustment suggestions, and sends the decision suggestions to the relevant management personnel through the internal communication system, including the airport operation management personnel, the maintenance technical personnel; after receiving the decision suggestions, the management personnel check and adjust according to the actual situation of the airport, once the decision suggestions are confirmed, the related risk adjustment or maintenance measures will be immediately executed.

[0056] In the decision module, based on the risk adjustment suggestion, combined with the preset safety threshold, historical experience and risk analysis result, the judgment result is obtained, the process includes: through the authentication mode of username plus password plus digital certificate, through security identity verification and permission verification, access the database storing the safety threshold, and according to the preset query condition or API interface, retrieve the required safety threshold from the database, parse and extract the numerical value or range of the safety threshold, at the same time, check the data to ensure the integrity and accuracy of the data, avoid using outdated or incorrect safety threshold, and then store the checked safety threshold data in the internal storage of the decision module, at the same time, the decision module will regularly check whether the safety threshold in the database is updated, to ensure that the latest safety standard is always used for judgment, the safety threshold includes the power safety range of the unmanned aerial vehicle, the flight height limit, the speed limit, the maintenance period of the airport facility, and the safety standard of the environmental condition; Review historical experience data, including past failure cases, maintenance records and successful strategies for dealing with specific situations; Set the unmanned aerial vehicle judgment logic, including: comparing the flight status report of the unmanned aerial vehicle with the preset safety threshold, if the unmanned aerial vehicle is found to be insufficient in power, deviating from the predetermined route, judging whether the task needs to be adjusted, including shortening the flight time, changing the flight route or emergency landing; Generate the judgment result of the unmanned aerial vehicle, that is, the adjustment instruction of the unmanned aerial vehicle task; Set the airport facility judgment logic, including: according to the maintenance suggestion and historical maintenance record of the airport facility, evaluate whether the current state of the airport facility is consistent with the preset maintenance period or standard, if the facility has a failure risk or has reached the maintenance period, judge whether it needs to be maintained immediately or arrange a preventive maintenance plan; Generate the judgment result of the airport facility, that is, the maintenance task list of the airport facility; Set the environment judgment logic, including: combining the environmental adaptability measures and the current environmental conditions (such as severe weather), if the environment poses a major threat to the operation, judge whether to start the backup plan, including using the backup runway, adjusting the flight time or taking other emergency measures, generate the environment judgment result, that is, the start-up notice of the backup plan, and implement the backup plan based on the start-up notice of the backup plan.

[0057] The process of implementing the backup solution includes: based on the monitoring devices installed in the acquisition module, continuously monitoring the flight status of the unmanned aerial vehicle, the operation status of the airport facility and the environmental parameters, when detecting a fault or abnormal signal (such as the unmanned aerial vehicle deviating from the predetermined route, the airport facility fault alarm, the severe weather warning), immediately trigger the backup solution in the decision module; according to the type of detected fault or abnormality, select the most suitable backup solution from the predefined backup solution library, which includes emergency landing procedures, unmanned aerial vehicle fault handling procedures, and airport facility emergency maintenance measures; based on the selected backup solution, make corresponding execution preparations, including starting the corresponding control system, deploying necessary maintenance personnel and backup equipment; at the same time, send notifications to relevant personnel (such as operators, maintenance personnel, management personnel, etc.) to ensure that they are aware of the current situation and are prepared; according to the content of the backup solution, guide relevant personnel to execute the corresponding control strategy and operation process; in the emergency landing procedure, guide the unmanned aerial vehicle to fly according to the predetermined emergency landing route and ensure safe landing; in the unmanned aerial vehicle fault handling procedure, provide steps for troubleshooting and repair, and guide maintenance personnel to quickly solve the problem; in the airport facility emergency maintenance measures, arrange maintenance personnel to perform emergency repair or replacement of damaged facilities; during the execution of the backup solution, continuously monitor the status and progress of the system, and if any new problems or adjustments to the solution are found, the decision module immediately adjusts and notifies relevant personnel, and at the same time, collects feedback data during the execution of the backup solution for subsequent optimization and improvement of the solution; when the backup solution is successfully executed and the problem is solved, record the relevant data and information, and end the execution of the current solution; then, evaluate the execution effect of the solution to obtain the evaluation result, including the efficiency of solving the problem and the rationality of resource use; the evaluation result will be used for optimization and improvement of subsequent solutions to improve the stability and reliability of the system; after ensuring the stability of the system, the decision module guides the system to gradually recover to the normal operating state, and at the same time, sends notifications to relevant personnel to ensure that they are aware of the current state of the system and prepare for subsequent work.

[0058] The feedback module includes: obtaining the final risk decision result from the decision module, including risk assessment, recommended maintenance measures, estimated adjustment time, and evaluation result; displaying relevant information of the risk decision result to relevant personnel through display screens in the airport and mobile applications, airport managers view on control center or mobile devices, and maintenance technicians obtain risk information through designated query interface; the airport managers and maintenance technicians confirm, adjust or supplement the risk decision result through the interactive interface, and when the managers or technicians confirm, adjust or supplement the risk decision result, receive feedback opinions and process the feedback opinions to update the risk information of the system; according to the feedback opinions, the system dynamically adjusts the operation strategy and decision suggestion to ensure that the risk state of the system is consistent with the actual demand, and improves the flexibility and response ability of the system.

[0059] It needs to be further explained that, in the specific implementation process, through the cooperation of the acquisition module and the processing module, the original data is comprehensively collected and optimized, laying a solid data foundation for automatic decision-making; then through the close cooperation of the analysis module and the decision module, risk assessment and decision-making are carried out according to the data, and automatic decision-making adjustment is realized in the three aspects of unmanned aerial vehicle task, airport facility maintenance and response to environmental threats; then when the system fails or abnormity, the standby scheme is automatically triggered and executed, ensuring the automation of airport emergency handling and the continuity of operation; in addition, the feedback module collects personnel opinions, optimizes operation strategy, enhances system flexibility, so that the automatic operation can accurately meet the real-time needs of the airport, and can improve the level of airport automation operation from multiple aspects.

[0060] In the unmanned operation of the helicopter airport, due to the complexity of environmental conditions, helicopter state and airport facility state, if a single indicator (such as fuel remaining or the working temperature of a mechanical component) is relied on to judge the safety and operation efficiency of the system, there will often be a large deviation. For example, an aircraft may still have flight risks due to mechanical component aging or sudden weather changes (such as sudden changes in wind direction and speed) even if it has sufficient fuel. In order to avoid misjudgment and missed judgment, the above technical solutions are used to comprehensively consider multiple evaluation indicators, including airport weather conditions, runway state, helicopter mechanical health, communication network quality and flight trajectory, so as to more accurately evaluate the overall state and potential risks of the unmanned system, help the system discover fault hidden dangers in the early stage and perform preventive maintenance or scheduling adjustment, so as to ensure that the helicopter airport can still be safely and efficiently operated in the highly automated and unmanned mode.

[0061] It should be noted that in this document, the terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment. Without more limitations, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, method, article or equipment including the element.

[0062] While embodiments of the application have been shown and described, it is to be understood that the embodiments described are merely exemplary of the principles and application of the present application. Numerous modifications and adaptions can be effected without departing from the spirit and scope of the present application, which is not limited to the exact construction and arrangement described. It is intended, therefore, to cover all modifications and adaptions that fall within the scope of the claims and their equivalents.

Claims

1. An unmanned system for helicopter airports, characterized in that: The unmanned system for heliports includes: Acquisition module, used to collect various raw data of the helicopter airport; A processing module, connected to the acquisition module, for preprocessing the collected raw data to obtain initial data; The decision-making module generates risk adjustment recommendations based on the results of the processing module, combined with the current airport's resource situation and operational processes. The decision-making module is also used to provide backup plans in the event of system failures or abnormal situations. The decision-making module also determines whether it is necessary to adjust the drone's mission, perform airport facility maintenance, or activate a backup plan based on risk adjustment recommendations, combined with preset safety thresholds, historical experience, and analysis results. The processing module also includes: The analysis module is used to analyze the initial data, extract representative features from it, and conduct comprehensive risk analysis in combination with historical data to obtain risk analysis results; The decision module also includes: The feedback module feeds back the risk decision results to airport managers and maintenance technicians, displays the risk decision result information through display screens and mobile applications, and provides interactive functions.

2. The unmanned system for a heliport according to claim 1, characterized in that: The process of collecting various types of raw data of the helicopter airport by the collection module includes: for the flight data of the drone, the power data and flight speed of the drone are obtained respectively through the power sensor and speed sensor on the drone, and the location information of the drone is obtained in real time by using the positioning base station in the airport; for the runway conditions in the status information of the airport facilities, the runway condition monitoring sensor is used to monitor and obtain them in real time; for the status of the navigation equipment, the corresponding status information is obtained in real time through the self-test systems of the navigation equipment, lighting system and communication system; for the meteorological data of the airport environment, the wind speed and wind direction are measured in real time by using an anemometer and a wind vane, the temperature and humidity are collected in real time by using a temperature and humidity sensor, the atmospheric turbulence is monitored and collected in real time by using a lidar, and cloud condition information is obtained in real time by using a ceilometer and a cloud meter combined with manual observation.

3. The unmanned system for a heliport according to claim 2, characterized in that: The analysis module is used to analyze the initial data, extract representative features from it, and conduct a comprehensive risk analysis in combination with historical data. The process of obtaining the risk analysis results includes: based on domain knowledge and experience and combined with feature importance assessment, screening out representative features that are highly correlated with the flight status of drones, the operating status of airport facilities, and the impact of the environment on operations from the initial data, namely, environmental representative features, operating status representative features, and helicopter performance representative features; using the relationship information in the knowledge base to analyze the causal relationship between each representative feature, and integrating a single representative feature into a multi-dimensional comprehensive evaluation system; quantifying the screened representative features, dividing the environmental parameters into low, medium, and high levels according to the wind speed level, assigning corresponding numerical values, and performing an analysis on the operating status data. Standardization is performed and the quantified representative features are encoded. A corresponding weight is assigned to each representative feature according to its importance and impact. Based on the screened representative features and the assigned weights, a comprehensive evaluation model is trained in combination with a neural network model to predict key features and potential risks in system operation. The newly collected helicopter and airport operation data are preprocessed, representative features are extracted, and quantified and encoded before being input into the analysis module. The trained comprehensive evaluation model is used to perform intelligent analysis on the data, extract key information and patterns related to system operation, and identify potential operational anomalies. Based on the analysis results, the risk situation in system operation is predicted, and the risk analysis results are output, including the probability of potential failures and the expected time window for emergency treatment.

4. The unmanned system for a heliport according to claim 3, characterized in that: According to the risk analysis results output by the analysis module, differentiated weights are assigned to representative features of different dimensions; The risk analysis results output by the analysis module are combined with the environmental representative feature score, operating status score, and helicopter performance score to calculate the system risk assessment coefficient and evaluate the system risk urgency. Based on the system risk urgency, different risk levels are divided into high risk level, medium risk level, low risk level, and normal risk level, and corresponding assessment thresholds are matched for each risk level. According to the system risk level, corresponding suggestions are matched from the predefined decision suggestion strategy library, which includes maintenance plans, troubleshooting suggestions, and emergency response measures for different risk levels.

5. The unmanned system for a heliport according to claim 4, characterized in that: The process of assigning different weights to representative features of different dimensions includes: when environmental parameters deviate seriously from the normal range, the wind speed exceeds the wind speed threshold of 25 meters per second, and the air pressure deviates from the standard atmospheric pressure by more than ±10hPa, a weight coefficient of 0.4-0.5 is assigned based on the incidence of high-risk situations corresponding to past risk data; for abnormal key risk parameters, when the helicopter fuel is less than 20% of the total fuel capacity or the remaining fuel is insufficient to support at least 30 minutes of emergency return and diversion operations, the fuel is considered to be below the safe level. In addition, if the fuel monitoring system detects abnormal fluctuations in fuel flow and the fuel pressure is lower than the minimum threshold of 5 bar set by the system, it can also be determined that the fuel is below the safe level; the engine temperature exceeds 120 degrees Celsius or is lower than 60 degrees Celsius, and the oil pressure is lower than 4 bar or higher than 15 bar. , the values ​​detected by key sensors deviate from the normal range by more than ±10%; in addition, if blade cracks, fuselage deformation, or failure of the braking system or navigation system are detected, it will also be regarded as a mechanical state abnormality, and according to its impact on system safety, it will be assigned a weight of 0.3-0.4; for helicopter performance characteristics, including speed and position deviation, when the actual flight speed of the helicopter exceeds its normal operating speed by more than 10%, or is less than 10% of the normal operating speed, it is regarded as a speed deviation, and when the horizontal distance between the actual position of the helicopter and the target position set by the navigation system exceeds 50 meters, or the vertical height deviation exceeds 20 meters, it is regarded as a position deviation, and a weight of 0.2-0.3 is assigned based on the corresponding risk occurrence rate of historical data; ensure that the sum of the weight coefficients of each representative feature is 1.

6. The unmanned system for a heliport according to claim 5, characterized in that: The calculation expression of the risk assessment coefficient is: ； Wherein: C is the risk assessment coefficient, ranging from 0 to 1; W1, W2, and W3 are the weight coefficients of the representative characteristics of the environment, the representative characteristics of the risk status, and the representative characteristics of the helicopter performance, respectively; S1, S2, and S3 are the environmental assessment scores, the risk status scores, and the helicopter performance scores, respectively; R is the reference minimum value of each representative characteristic score; k is the adjustment coefficient, which is a constant greater than 0 and is used to adjust the shape of the exponential function curve; the value of the risk assessment coefficient and the risk assessment threshold preset for the risk level are obtained to match the four risk levels, namely: high risk level: 0.75≤C≤1.0; medium risk level: 0.5≤C<0.75; low risk level: 0.25≤C<0.5; normal risk level: 0≤C<0.

25.

7. The unmanned system for a heliport according to claim 6, characterized in that: The decision module includes: Receive the results from the analysis module, including the system risk level, risk assessment coefficient, and related environmental parameters and risk status information, and comprehensively analyze the current resource situation of the airport, including runway usage status, helicopter parking status, and availability of maintenance equipment; match the system risk level with the corresponding operation strategy according to the airport's operating procedures, and determine the maintenance measures, risk adjustments or emergency response steps to be taken; based on the analysis results, the decision module generates risk adjustment recommendations and sends the decision recommendations to relevant managers, including airport operation managers and maintenance technicians, through the internal communication system; after receiving the decision recommendations, managers will check and adjust them according to the actual situation of the airport. Once the decision recommendations are confirmed, the relevant risk adjustments or maintenance measures will be immediately implemented.

8. The unmanned system for a heliport according to claim 7, characterized in that: In the decision-making module, based on the risk adjustment suggestion, combined with the preset security threshold, historical experience and risk analysis results, the judgment result is obtained. The process includes: through the authentication method of username plus password plus digital certificate, through security identity verification and permission verification, accessing the database storing the security threshold, and according to the preset query conditions or API interface, retrieving the required security threshold from the database, parsing and extracting the value or range of the security threshold, and at the same time, verifying the data, and then storing the verified security threshold data in the internal memory of the decision-making module; reviewing historical experience data; setting the drone judgment logic, including: comparing the drone's flight status report with the preset safety threshold, if it is found that the drone is low on battery or deviates from the scheduled route, judging whether the mission needs to be adjusted, including shortening Shorten flight time, change flight route or make emergency landing; generate drone judgment results; set airport facility judgment logic, including: based on the maintenance recommendations and historical maintenance records of airport facilities, evaluate whether the current status of airport facilities is consistent with the preset maintenance cycle or standards, and if the facilities are at risk of failure or have reached the maintenance cycle, determine whether immediate maintenance is required or arrange a preventive maintenance plan; generate airport facility judgment results; set environmental judgment logic, including: combining environmental adaptability measures and current environmental conditions, if the environment poses a major threat to operations, determine whether it is necessary to activate a backup plan, including using a backup runway, adjusting flight time or taking other emergency measures, generate an environmental judgment result, that is, a notification to activate the backup plan, and implement the backup plan based on the notification to activate the backup plan.

9. The unmanned system for a heliport according to claim 8, characterized in that: The process of implementing the backup plan includes: based on the monitoring equipment installed in the acquisition module, continuously monitoring the flight status of the drone, the operating status of the airport facilities and the environmental parameters, and immediately triggering the backup plan in the decision-making module when a fault or abnormal signal is detected; selecting a backup plan from the predefined backup plan library according to the type of fault or abnormality detected; making corresponding execution preparations based on the selected backup plan, including starting the corresponding control system, deploying necessary maintenance personnel and backup equipment; at the same time, sending notifications to relevant personnel to ensure that they understand the current situation and are prepared; guiding relevant personnel to implement the corresponding control strategies and operating procedures according to the content of the backup plan; executing During the backup plan process, the system status and progress are continuously monitored. If any new problems are found or the plan needs to be adjusted, the decision-making module will make adjustments immediately and notify the relevant personnel. At the same time, feedback data from the implementation of the backup plan will be collected. When the backup plan is successfully implemented and the problem is solved, the relevant data and information will be recorded, and the execution of the current plan will be terminated. Subsequently, the execution effect of the plan will be evaluated to obtain evaluation results, including the efficiency of problem solving and the rationality of resource utilization. After ensuring the stability of the system, the decision-making module will guide the system to gradually return to normal operation. At the same time, notifications will be sent to relevant personnel to ensure that they understand the current status of the system and are ready for subsequent work.

10. The unmanned system for a heliport according to claim 9, characterized in that: described The feedback module includes: The final risk decision results are obtained from the decision-making module, including the risk assessment status, recommended maintenance measures, estimated adjustment time and assessment results; the relevant information of the risk decision results is displayed to relevant personnel through display screens and mobile applications within the airport. Airport managers view the information in the control center or on mobile devices, and maintenance technicians obtain risk information through designated query interfaces; airport managers and maintenance technicians confirm, adjust or supplement relevant opinions on the risk decision results through interactive interfaces. When managers or technicians confirm, adjust or supplement the risk decision results, they receive feedback, process the feedback, and update the system's risk information.

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