Unattended system for airport based on helicopters

Abstract

The invention discloses an unattended system for a helicopter airport, and relates to the technical field of unattended airports, and the system comprises a collection module which is used for collecting various types of original data of the helicopter airport; and the processing module is connected with the acquisition module and is used for preprocessing the acquired original data to obtain initial data. According to the unmanned system for the airport based on the helicopters, original data are comprehensively collected and optimized, and a data foundation is built for automatic decision making; then risk assessment and decision making are carried out according to the data, and automatic decision making adjustment is achieved in the three aspects of unmanned aerial vehicle tasks, airport facility maintenance and environmental threat coping; and then, when the system fails or is abnormal, the standby scheme is automatically triggered and executed, and automation and operation continuity of airport emergency processing are guaranteed.

Description

Technical Field

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

[0002] With the widespread application of drone technology in many industries, people's requirements for its convenience, safety and automation are constantly increasing. However, the traditional on-site manual control or monitoring operation mode is inefficient and costly when executing large-scale tasks. In the fields of infrastructure inspection, agricultural monitoring, logistics and distribution, although drones are favored for their flexibility and mobility, problems such as short battery life, data transmission delay, and complex operation hinder their advantages. Against this background, the concept of drone-attended helicopter airports came into being. It integrates multiple functions such as automated control and remote management to help drones complete tasks more independently. At the same time, the development of social economy, especially the progress of information technology such as the Internet of Things, big data, and cloud computing, has provided support for the intelligent management of unmanned airports. Unmanned airports reduce carbon emissions and meet the needs of sustainable development. Although drone technology is becoming increasingly mature and its application scope continues to expand, the existing operation mode cannot meet the needs of automation. Realizing unmanned operations has become the key to solving the problem. Summary of the invention

[0003] 1. Technical issues to be resolved

[0004] In view of the deficiencies in the prior art, the present invention provides an unmanned system for a helicopter airport, 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] (II) Technical solution

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

[0007] The acquisition module is 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 abnormal values ​​in the raw data, and converting analog signals in the raw data into digital signals;

[0009] The decision module generates risk adjustment suggestions based on the results of the analysis module in the processing module, combined with the current airport resource situation and the airport's operating procedures; the decision module is also used to provide backup plans when the system fails or abnormal conditions occur, including emergency landing procedures, drone failure handling procedures, and emergency maintenance measures for airport facilities;

[0010] The decision-making module also determines whether it is necessary to adjust the mission of the drone, maintain the airport facilities, or activate the backup plan based on the risk adjustment suggestions, combined with the preset safety thresholds, historical experience and analysis results, and obtains the judgment result;

[0011] The processing module also includes:

[0012] 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;

[0013] The decision module also includes:

[0014] 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.

[0015] Preferably, the process of the acquisition module collecting various types of raw data of the helicopter airport 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 the conditions on the runway in real time, including obstacles, ice areas, cracks, potholes, foreign objects, pressure changes and metal foreign objects; for the navigation equipment status, 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 environment where the airport is located, the wind speed and wind direction are measured in real time by an anemometer and a wind vane, the temperature and humidity are collected in real time by a temperature and humidity sensor, the atmospheric turbulence is monitored and collected in real time by a laser radar, and the cloud condition information is obtained in real time by a ceilometer and a cloud meter combined 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 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, representative features that are highly correlated with the flight status of the drone, the operating status of airport facilities, and the impact of the environment on the operation are screened out 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 the representative features, and integrating the single representative features 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 evaluation on the operating status data. The data is standardized and the quantified representative features are encoded; corresponding weights are assigned to each representative feature according to its importance and influence; 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, and then input into the analysis module, and 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 estimated time window for emergency treatment.

[0017] Preferably, differentiated weights are assigned to representative features of different dimensions based on the risk analysis results output by the analysis module; the risk analysis results output by the analysis module are combined with the environmental representative feature scores, the operating status scores, and the helicopter performance scores to calculate the system risk assessment coefficient and evaluate the risk urgency of the system; different risk levels are divided into high risk level, medium risk level, low risk level, and normal risk level based on the system risk urgency, and a corresponding assessment threshold is matched for each risk level; according to the system risk level, corresponding suggestions are matched from a predefined decision suggestion strategy library, and the decision suggestion strategy library includes maintenance plans, troubleshooting suggestions, and emergency response measures for different risk levels.

[0018] Preferably, the process of assigning different weights to representative features of different dimensions includes: when environmental parameters seriously deviate 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 (1013.25hPa) by more than ±10hPa, a weight coefficient of 0.4-0.5 is assigned based on the incidence rate 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 alternate landing 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, the oil pressure is lower than 4 bar or higher than 15 If the values ​​detected by key sensors (such as attitude sensors and speed 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 an abnormal mechanical state, and a weight of 0.3-0.4 will be assigned based on its impact on system safety; 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; 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 will be assigned with reference to the corresponding risk occurrence rate of 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, ranging from 0 to 1. The closer the value is to 1, the higher the urgency of the system risk; 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, risk status scores, and 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.

[0022] Preferably, the decision module includes:

[0023] 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 airport resource situation, 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 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 implemented immediately.

[0024] Preferably, in the decision module, based on the risk adjustment suggestion, combined with the preset safety threshold, historical experience and risk analysis results, the judgment result is obtained, and the process includes: through the authentication method of username plus password plus digital certificate, through security identity verification and permission verification, access to the database storing the safety threshold, and according to the preset query conditions or API interface, retrieve the required safety threshold from the database, parse and extract the value or range of the safety threshold, and at the same time, verify the data to ensure the integrity and accuracy of the data, avoid using outdated or erroneous safety thresholds, and then store the verified safety threshold data in the internal memory of the decision module. At the same time, the decision module will regularly check whether the safety threshold in the database has been updated to ensure that the latest safety standards are always used for judgment. The safety threshold includes the safety range of the drone's power, flight altitude limit, speed limit, maintenance cycle of airport facilities, and safety standards for environmental conditions; review historical experience data, including past failure cases, maintenance records, and successful strategies for dealing with specific situations; set the drone The judgment logic includes: comparing the flight status report of the drone with the preset safety threshold. If it is found that the drone is low on battery or deviates from the scheduled route, determine whether the mission needs to be adjusted, including shortening the flight time, changing the flight route or making an emergency landing; generating the drone judgment result, that is, the adjustment instruction of the drone mission; setting the airport facility judgment logic, including: based on the maintenance recommendations and historical maintenance records of the airport facilities, evaluating whether the current status of the airport facilities is consistent with the preset maintenance cycle or standards. If the facilities are at risk of failure or have reached the maintenance cycle, determine whether immediate maintenance or preventive maintenance plans are required; generating the airport facility judgment result, that is, the maintenance task list of the airport facilities; setting the environmental judgment logic, including: combining environmental adaptability measures and current environmental conditions (such as bad weather), if the environment poses a major threat to the operation, determine whether it is necessary to activate the backup plan, including using the backup runway, adjusting the flight time or taking other emergency measures, generating the environmental judgment result, that is, the activation notification of the backup plan, and implementing the backup plan based on the activation notification of the backup plan.

[0025] Preferably, 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 when a fault or abnormal signal is detected, immediately triggering the backup plan in the decision-making module; according to the type of fault or abnormality detected, selecting the most appropriate backup plan from a predefined backup plan library, the backup plan library includes emergency landing procedures, drone fault handling procedures, and airport facility emergency maintenance measures; based on the selected backup plan, making corresponding execution preparations, 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; according to the content of the backup plan, guiding relevant personnel to execute corresponding control strategies and operating procedures; 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 during the execution of the backup plan is collected for optimization and improvement of subsequent plans. When the backup plan is successfully executed and the problem is solved, the relevant data and information are recorded, and the execution of the current plan is ended. Subsequently, the execution effect of the plan is evaluated to obtain evaluation results, including the efficiency of problem solving and the rationality of resource use. The evaluation results will be used to optimize and improve subsequent plans to improve the stability and reliability of the system. After ensuring the stability of the system, the decision-making module guides the system to gradually return to normal operation. At the same time, notifications are sent to relevant personnel to ensure that they understand the current status of the system and are ready for subsequent work.

[0026] Preferably, the feedback module includes: obtaining the final risk decision result from the decision module, including the risk assessment situation, recommended maintenance measures, estimated adjustment time and assessment results; displaying the relevant information of the risk decision result to relevant personnel through the display screen and mobile application in the airport, the airport manager views it on the control center or mobile device, and the maintenance technician obtains the risk information through the designated query interface; the airport manager and the maintenance technician confirm, adjust or supplement the risk decision result through the interactive interface, and when the manager or technician confirms, adjusts or supplements the risk decision result, feedback is received, processed and the risk information of the system is updated; according to the feedback, the system dynamically adjusts the operation strategy and decision suggestions to ensure that the risk status of the system is consistent with actual needs and improve the flexibility and responsiveness of the system.

[0027] (III) Beneficial effects

[0028] The present invention provides an unmanned system for helicopter airports, which has the following beneficial effects:

[0029] This unmanned system for helicopter airports, through the collaborative work of the acquisition module and the processing module, comprehensively collects and optimizes the original data, laying a solid data foundation for automated decision-making; then, through the close cooperation of the analysis module and the decision-making module, risk assessment and decision-making are carried out based on the data, and automated decision-making adjustments are realized in three aspects: UAV missions, airport facility maintenance, and response to environmental threats; then, when a failure or abnormality occurs in the system, the backup plan is automatically triggered and executed to ensure the automation and operational continuity of the airport's emergency response; in addition, the feedback module is used to collect personnel opinions, optimize operation strategies, and enhance system flexibility, so that automated operations can accurately meet the real-time needs of the airport, and the level of automated operations of the airport can be improved in many aspects. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a schematic diagram of the framework of the unattended system of the present invention;

[0031] Figure 2 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

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

[0033] See also Figure 1 and Figure 2 The present invention provides a technical solution: an unmanned system for a helicopter airport, comprising:

[0034] The acquisition module is used to collect various raw data of the helicopter airport;

[0035] The processing module is connected to the acquisition module and 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 abnormal values ​​in the raw data, and converting the analog signals in the raw data into digital signals;

[0036] The decision module generates risk adjustment suggestions based on the results of the analysis module in the processing module, combined with the current airport resource situation and the airport's operating procedures; the decision module is also used to provide backup plans when the system fails or abnormal conditions occur, including emergency landing procedures, drone failure handling procedures, and emergency maintenance measures for airport facilities;

[0037] The decision-making module also determines whether it is necessary to adjust the mission of the drone, maintain the airport facilities, or activate the backup plan based on the risk adjustment suggestions, combined with the preset safety thresholds, historical experience and analysis results, and obtains the judgment result;

[0038] The processing module also includes:

[0039] 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;

[0040] The decision module also includes:

[0041] 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.

[0042] The process of collecting various raw data of the helicopter airport by the acquisition 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 the conditions on the runway in real time, including obstacles, ice areas, cracks, potholes, foreign objects, pressure changes and metal foreign objects; for the navigation equipment status, 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 using an anemometer and a wind vane, the temperature and humidity are collected in real time through temperature and humidity sensors, the atmospheric turbulence is monitored and collected in real time using a laser radar, and the cloud condition information is obtained in real time through a cloud height meter and a cloud meter combined with manual observation; among them, 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 should be further explained that in the specific implementation process, atmospheric turbulence includes turbulence intensity and turbulence frequency. In turbulence intensity, atmospheric turbulence will cause the flight instability of the UAV and increase the difficulty of flight control, especially around complex terrain and buildings, where turbulence is more common; in turbulence frequency, frequent turbulence will increase the energy consumption of the UAV, shorten the battery life, and may also cause damage to the structure of the UAV;

[0044] Cloud conditions include cloud height and cloud thickness. For medium cloud height, low clouds will affect the takeoff and landing of the UAV, and high clouds will affect visibility and communication signals during flight. For medium cloud thickness, thick clouds will increase flight resistance, affect the flight performance of the UAV, and also hide potential meteorological risks, such as thunderstorms.

[0045] It should 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, which is used to detect foreign objects, cracks, water accumulation, and snow on the runway, and identify obstacles on the runway, such as birds, vehicles, and tools, to ensure the cleanliness and safety of the runway; the infrared sensor uses a thermal imaging camera to detect the temperature distribution on the runway surface through thermal imaging technology, identify snow, water accumulation, and ice layers, and detect ice areas on the runway in advance and perform de-icing in time; the lidar 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; Ultrasonic sensors use distance sensors to measure the distance between the runway surface and the sensor through the principle of ultrasonic reflection, and detect foreign objects on the runway, such as small tools and debris; Pressure sensors use ground pressure sensors, which are installed on the runway surface or underground to detect pressure changes on the runway, identify the pressure of heavy objects (such as vehicles and large equipment) on the runway, prevent heavy vehicles from mistakenly entering the runway, and ensure the structural safety of the runway; Electromagnetic induction sensors use metal detectors to detect metal foreign objects on the runway, such as screws and tools, to prevent metal foreign objects from causing damage to drones. Before the drone takes off and lands, ensure that there are no metal foreign objects on the runway surface to improve take-off and landing safety;

[0046] In the processing module, the collected raw data is preprocessed to obtain the initial data. The process includes: first, the raw data from the acquisition module is received through the communication interface (such as the network interface, the serial port), and then the noise and outliers in the raw data are removed through the data cleaning algorithm integrated in the software of the processing module. Specifically, the high-frequency noise or random fluctuations in the data are removed through smoothing filtering and median filtering, and then the 3σ principle is used to detect outliers, and the outliers are deleted, replaced or corrected according to the actual situation. Then, based on the collaborative work of ADC and data format conversion algorithm, the analog signal (such as the output of the temperature, humidity and other sensors) is converted into a digital signal through the analog-to-digital converter ADC according to a unified format standard, such as timestamp, data accuracy, and unit. Then, the digital signal is verified by checksum to obtain the initial data, and the initial data is stored in the database.

[0047] 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. The process of obtaining the risk analysis results includes: based on domain knowledge and experience and combined with feature importance assessment, 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 are screened out 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 the representative features, and synthesize the single representative features 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 values, and performing Standardization processing is performed to encode the quantified representative features; corresponding weights are assigned to each representative feature according to its importance and influence; a comprehensive evaluation model is trained based on the selected representative features and the assigned weights 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, and then input into the analysis module, where 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 estimated time window for emergency processing.

[0048] It should be further explained that, in the specific implementation process, statistical methods are used to analyze the correlation of representative features with the analysis structure obtained by subsequent evaluation, and value features that are highly correlated with the analysis results are screened out, namely, the value features of the flight status of the UAV, the value features of the operation status of the airport facilities, and the value features of the operation impact; then, based on the value features of the flight status of the UAV, combined with historical data, the trajectory matching algorithm and the power consumption model are used to evaluate the flight status of the UAV, including whether it deviates from the scheduled route and whether the power is sufficient, and the flight status evaluation results of the UAV are obtained; sensor data, historical maintenance records and the value features of the operation status of the airport facilities are used to evaluate the operation status of the airport facilities, including whether the runway is flat and whether the navigation equipment is accurate, and the operation status evaluation results of the airport facilities are obtained;

[0049] Combined with meteorological data, historical records of weather impacts on flight safety, and operational impact value characteristics, assess whether bad weather affects flight safety and obtain environmental impact assessment results on operations; analyze and summarize the UAV flight status assessment results, operational status assessment results, and environmental impact assessment results, and add them to the process of generating risk analysis results. The risk analysis results also include UAV flight status reports, airport facility maintenance recommendations, and environmental adaptability measures;

[0050] 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 scores, operating status scores, and helicopter performance scores to calculate the system risk assessment coefficient and evaluate the risk urgency of the system; different risk levels are divided into high-risk risk level, medium-risk risk level, low-risk risk level, and normal risk level according to the system risk urgency, and the corresponding assessment threshold is 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.

[0051] The process of assigning different weights to representative features of different dimensions includes: for environmental parameters that seriously deviate from the normal range, when the wind speed exceeds the wind speed threshold of 25 meters per second, and the air pressure deviates from the standard atmospheric pressure (1013.25hPa) 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, the oil pressure is lower than 4 bar or higher than 15 bar, 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 during the system self-test; in addition If blade cracks, fuselage deformation, or failure of the braking system or navigation system are detected, they will also be regarded as abnormal mechanical status, and a weight of 0.3-0.4 will be assigned based on their impact on system safety. 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 speed deviation. In addition, when the instantaneous rate of change of flight speed exceeds 30 kilometers per hour (km / h) per minute, it is also determined as 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 regarded as position deviation. In addition, if the deviation of the heading angle of the helicopter from the predetermined heading angle exceeds 15 degrees, it is also determined as position deviation. With reference to the corresponding risk occurrence rate of historical data, a weight of 0.2-0.3 is assigned. Ensure that the sum of the weight coefficients of each representative feature is 1, and adjust each weight coefficient to reflect its importance in the comprehensive assessment.

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

[0053] ;

[0054] Wherein: C is the risk assessment coefficient, ranging from 0 to 1. The closer the value is to 1, the higher the urgency of the system risk; 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, risk status scores, and 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 is obtained and the risk assessment threshold preset by the risk level is matched to 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.

[0055] The decision-making module includes: receiving the results from the analysis module, including the system risk level, risk assessment coefficient, and related environmental parameters and risk status information, and comprehensively analyzing the current airport resource situation, including runway usage status, helicopter parking status, and availability of maintenance equipment; matching the system risk level with the corresponding operating strategy according to the airport's operating procedures, and determining the maintenance measures, risk adjustments, or emergency response steps to be taken; based on the analysis results, the decision-making 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 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.

[0056] In the decision-making module, the judgment result is obtained based on the risk adjustment suggestion, combined with the preset safety threshold, historical experience and risk analysis results. The process includes: through the authentication method of username plus password plus digital certificate, through security identity verification and permission verification, access to the database storing the safety threshold, and according to the preset query conditions or API interface, retrieve the required safety threshold from the database, parse and extract the value or range of the safety threshold, and at the same time, verify the data to ensure the integrity and accuracy of the data, avoid using outdated or erroneous safety thresholds, and then store the verified safety threshold data in the internal memory of the decision-making module. At the same time, the decision-making module will regularly check whether the safety threshold in the database has been updated to ensure that the latest safety standards are always used for judgment. The safety threshold includes the safety range of the drone's power, flight altitude limit, speed limit, maintenance cycle of airport facilities, and safety standards for environmental conditions; review historical experience data, including past failure cases, maintenance records, and successful strategies for dealing with specific situations; set the drone's judgment logic The logic of judgment of airport facilities is as follows: comparing the flight status report of the UAV with the preset safety threshold, and judging whether the mission needs to be adjusted, including shortening the flight time, changing the flight route or making an emergency landing, if the UAV is found to be low on battery or deviates from the scheduled route; generating the judgment result of the UAV, i.e. the adjustment instruction of the UAV mission; setting the judgment logic of airport facilities, including: evaluating whether the current status of the airport facilities is consistent with the preset maintenance cycle or standard according to the maintenance recommendations and historical maintenance records of the airport facilities, and judging whether immediate maintenance or preventive maintenance plan is required if the facilities are at risk of failure or have reached the maintenance cycle; generating the judgment result of airport facilities, i.e. the maintenance task list of the airport facilities; setting the environmental judgment logic, including: combining the environmental adaptability measures and the current environmental conditions (such as bad weather), judging whether the backup plan needs to be activated, including using the backup runway, adjusting the flight time or taking other emergency measures, if the environment poses a major threat to the operation, generating the environmental judgment result, i.e. the activation notification of the backup plan, and implementing the backup plan based on the activation notification of the backup plan.

[0057] 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 (such as the drone deviating from the scheduled route, the airport facility fault alarm, and the severe weather warning); according to the type of fault or abnormality detected, the most appropriate backup plan is selected from the predefined backup plan library, and the backup plan library includes emergency landing procedures, drone fault handling procedures, and airport facility emergency maintenance measures; based on the selected backup plan, corresponding execution preparations are made, including starting the corresponding control system, deploying necessary maintenance personnel, and backup equipment; at the same time, notifications are sent to relevant personnel (such as operators, maintenance personnel, management personnel, etc.) to ensure that they understand the current situation and are prepared; according to the content of the backup plan, guide relevant personnel to implement corresponding control strategies and operating procedures; in the emergency landing procedure, guide the drone to fly along the predetermined emergency landing route and ensure a safe landing; In the UAV fault handling process, troubleshooting and repair steps are provided to guide maintenance personnel to quickly solve problems; in the emergency maintenance measures for airport facilities, maintenance personnel are arranged to carry out emergency repairs or replacements of damaged facilities; during the execution of the backup plan, the status and progress of the system are continuously monitored. If any new problems are found or the plan needs to be adjusted, the decision module will make adjustments immediately and notify relevant personnel. At the same time, feedback data during the execution of the backup plan is collected for optimization and improvement of subsequent plans; when the backup plan is successfully executed and the problem is solved, the relevant data and information are recorded, and the execution of the current plan is terminated; then, the execution effect of the plan is evaluated to obtain evaluation results, including the efficiency of problem solving and the rationality of resource use; the evaluation results will be used for optimization and improvement of subsequent plans to improve the stability and reliability of the system; after ensuring the stability of the system, the decision module guides the system to gradually return to normal operating status. At the same time, notifications are sent to relevant personnel to ensure that they understand the current status of the system and are ready for subsequent work.

[0058] The feedback module includes: obtaining the final risk decision results from the decision-making module, including risk assessment status, recommended maintenance measures, estimated adjustment time and assessment results; displaying relevant information of the risk decision results to relevant personnel through display screens and mobile applications in the airport, airport managers viewing them in the control center or on mobile devices, and maintenance technicians obtaining 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; based on the feedback, the system dynamically adjusts the operating strategy and decision recommendations to ensure that the system's risk status is consistent with actual needs and to enhance the system's flexibility and responsiveness.

[0059] It needs to be further explained that, in the specific implementation process, the acquisition module and the processing module work together to comprehensively collect and optimize the original data, thus laying a solid data foundation for automated decision-making; then, the analysis module and the decision-making module work closely together to conduct risk assessment and decision-making based on the data, and realize automated decision-making adjustments in three aspects: UAV missions, airport facility maintenance, and response to environmental threats; then, when a failure or abnormality occurs in the system, the backup plan is automatically triggered and executed to ensure the automation and operational continuity of the airport's emergency response; in addition, the feedback module is used to collect personnel opinions, optimize operation strategies, and enhance system flexibility, so that automated operations can accurately meet the real-time needs of the airport, and can improve the airport's automated operation level in many aspects.

[0060] In the unmanned operation of a helicopter airport, due to the complexity of environmental conditions, the status of the helicopter itself, and the status of airport facilities, if a single indicator (such as the remaining fuel or the operating temperature of a mechanical component) is relied upon to judge the safety and operational efficiency of the system, large deviations will often occur. For example, even if a helicopter has sufficient fuel, it may still face flight risks due to aging of mechanical components or sudden weather changes (such as sudden changes in wind direction and speed). In order to avoid misjudgments and missed judgments, the above technical solution is used to comprehensively consider a variety of evaluation indicators, including airport meteorological conditions, runway conditions, helicopter mechanical health, communication network quality, and flight trajectory, so as to more accurately evaluate the overall status and potential risks of the unmanned system, help the system to promptly detect potential faults at an early stage and perform preventive maintenance or scheduling adjustments to ensure that the helicopter airport can still operate safely and efficiently in a highly automated and unmanned mode.

[0061] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0062] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An unmanned system for a helicopter airport, characterized in that: The unmanned system for helicopter airports includes: The acquisition module is used to collect various raw data of the helicopter airport; A processing module, connected to the acquisition module, for preprocessing the acquired raw data to obtain initial data; The decision module generates risk adjustment suggestions based on the results of the processing module, combined with the current airport resource situation and the airport's operating procedures; the decision module is also used to provide backup plans when the system fails or anomalies occur; The decision-making module also determines whether it is necessary to adjust the mission of the drone, maintain the airport facilities, or activate the backup plan based on the risk adjustment suggestions, combined with the preset safety thresholds, historical experience and analysis results, and obtains the judgment result; 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 helicopter airport according to claim 1 is characterized in that: The process of collecting various 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 condition in the status information of the airport facilities, the runway condition monitoring sensor is used to monitor and obtain it in real time, and for the navigation equipment status, the corresponding status information is obtained in real time through the self-test systems of the navigation equipment, the lighting system and the communication system; for the meteorological data of the environment where the airport is located, 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 laser radar, and the 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 helicopter airport according to claim 2 is 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, 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 are screened out 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 the representative features, and integrating the single representative features 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 values, and performing an analysis on the operating status data. Standardization is performed and the quantified representative features are encoded. According to the importance and influence of the representative features, corresponding weights are assigned to each representative feature. 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 estimated time window for emergency treatment.

4. The unmanned system for helicopter airport according to claim 3 is 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, the operating status score, and the helicopter performance score to calculate the system risk assessment coefficient and evaluate the system risk urgency. Different risk levels are divided according to the system risk urgency, namely high risk level, medium risk level, low risk level, and normal risk level, and the corresponding assessment threshold is matched for each risk level. According to the system risk level, the 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 helicopter airport according to claim 4 is 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 braking system or navigation system failure are detected, it will also be regarded as an abnormal mechanical state, and a weight of 0.3-0.4 will be assigned based on its impact on system safety; 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 with reference to 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 helicopter airport according to claim 5, characterized in that: The calculation expression of the risk assessment coefficient is: ； Wherein: C is the risk assessment coefficient, and its value range is between 0 and 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, risk status scores, and 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 helicopter airport according to claim 6 is characterized by: The decision module comprises: 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 airport resource situation, 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 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 implemented immediately.

8. The unmanned system for helicopter airport according to claim 7 is characterized in that: In the decision-making module, based on the risk adjustment suggestion, combined with the preset safety 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, access to the database storing the safety threshold, and according to the preset query conditions or API interface, the required safety threshold is retrieved from the database, and the value or range of the safety threshold is extracted by parsing. At the same time, the data is verified, and then the verified safety threshold data is stored 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 power or deviates from the scheduled route, judging whether the mission needs to be adjusted, including shortening the 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 the airport facilities, evaluate whether the current status of the airport facilities is consistent with the preset maintenance cycle or standards. If the facilities are at risk of failure or have reached the maintenance cycle, determine whether immediate maintenance is required or a preventive maintenance plan is arranged; generate airport facility judgment results; set environmental judgment logic, including: combining environmental adaptability measures and current environmental conditions (such as bad weather), if the environment poses a major threat to the operation, 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 helicopter airport 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 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 module will make adjustments immediately and notify the relevant personnel. At the same time, feedback data during the execution of the backup plan will be collected. When the backup plan is successfully executed and the problem is solved, the relevant data and information will be recorded, and the execution of the current plan will be ended. 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 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 follow-up work.

10. The unmanned system for helicopter airport according to claim 9, characterized in that: The feedback module includes: obtaining the final risk decision result from the decision module, including the risk assessment situation, recommended maintenance measures, estimated adjustment time and assessment results; displaying the relevant information of the risk decision result to relevant personnel through the display screen and mobile application in the airport, the airport manager views it on the control center or mobile device, and the maintenance technician obtains the risk information through the designated query interface; the airport manager and the maintenance technician confirm, adjust or supplement the risk decision result through the interactive interface, and when the manager or technician confirms, adjusts or supplements the risk decision result, the feedback is received, processed and the risk information of the system is updated.

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