34 results about "Aerodrome" patented technology

The invention discloses an extended-range hybrid propulsion double-source dynamic coupling energy management method, which comprises the following steps: carrying out global physical modeling on a double-source power system and a flight scene, and establishing a double-source dynamic coupling model; designing a reinforcement learning physical constraint reward function, performing optimization training on each coefficient of the reward function by adopting a QMPSO algorithm, and outputting an optimized reward function coefficient; a qualified double-source dynamic coupling model is verified, and a power distribution coefficient is optimized; outputting the optimal power distribution coefficient of the battery and the range extender; the superiority of the dual-source power cooperative control strategy in the aspects of flight economy, operation stability and system life guarantee is verified through multi-dimensional comparative analysis of each performance index. Cooperative power distribution of the battery and the range extender is achieved through dynamic coupling modeling and reinforcement learning, the flight scene load requirement is met, the system energy efficiency is improved, and the service life of parts is prolonged.

The invention relates to the technical field of aviation safety, in particular to a fixed-wing aircraft natural icing prediction system based on a prediction model and big data analysis. Comprising a multi-source data acquisition module, a data processing module, a feature extraction module, an icing case database, a prediction model module, a prediction analysis module and an early warning result output module. The data processing module is used for preprocessing and cleaning the collected original data; the feature extraction module is used for extracting key feature variables having significant influence on natural icing of the aircraft from the processed data; the prediction model module is used for taking the extracted key feature variables as input and combining big data analysis to construct a prediction model; and the prediction analysis module is used for inputting the currently collected multi-source data into the trained prediction model for analysis, and by adopting the mode, the icing risk is predicted in advance, the operation fault-tolerant space is greatly increased, and the accurate prediction requirement in the flight scene can be met.

An unmanned aerial vehicle fine path planning method for flight domain map dynamic refinement comprises the three steps of flight scene omnidirectional elastic grid model preparation, initial flight domain map construction and flight path recursion refinement, and the method has the capability of achieving high-resolution unmanned aerial vehicle path planning in a large-range city scene; the method has lower space complexity, and the time efficiency is higher when unmanned aerial vehicle path planning is carried out in a large-range city scene.

The invention discloses a spatial orientation real-time analysis method based on eye movement, relates to the related technical field of flight training, and aims to overcome the defects of low analysis accuracy and poor adaptability in the prior art. The method comprises the following steps: acquiring pilot eye movement data through eye movement tracking equipment, acquiring head space orientation data through a flight helmet space sensor, and acquiring environment data containing instrument visual complexity and aircraft attitude from a virtual flight simulator; performing time synchronization on the three types of data; extracting features such as coordinates of a fixation point from the synchronous eye movement data; comparing the head orientation data with the reference data to generate deviation data; inputting the eye movement characteristics, the deviation data and the environment data into an evaluation model; the model dynamically adjusts parameters according to environment data, and calculates pilot space orientation capability indexes in combination with eye movement characteristics and deviation data. According to the method, accurate integration of multi-dimensional data can be realized, the analysis comprehensiveness and reliability are improved, a dynamic flight scene is adapted, and real-time accurate evaluation is realized.

The invention relates to a method and system for deflating an oxygen mask. The method for throwing the oxygen mask comprises the steps that the current flight scene S of an aircraft is determined, wherein the flight scene S comprises a ground station-crossing and take-off stage S1, a climbing or cruising stage S2 and a descending and landing stage S3; calculating a cabin height warning value ZCW based on the flight scene S and the cabin height value ZC; judging a jettisoning height threshold value ZD based on the cabin height alarm value ZCW; in any flight scenario, the cabin height value ZC is compared to the jettisoning height threshold ZD, and when the cabin height value ZC is greater than the jettisoning height threshold ZD, the oxygen mask is automatically jettisoned.

The invention discloses an aircraft trajectory prediction method and device and a readable storage medium, and the method comprises the steps: inputting historical flight trajectory data of a to-be-predicted aircraft into a trajectory prediction model, and carrying out the bidirectional gating feature extraction of the historical flight trajectory data, and obtaining historical trajectory features; performing guidance law classification prediction on the historical trajectory features to obtain a prediction guidance law type; determining a corresponding guidance parameter regression branch according to the prediction guidance law type, and carrying out guidance law parameter prediction on the historical trajectory features based on the guidance parameter regression branch to obtain a prediction guidance parameter value; and performing flight path extrapolation on the to-be-predicted aircraft according to the prediction guidance law type and the prediction guidance parameter value to obtain a flight path prediction result. The guidance law type and the guidance parameters are predicted in a data-driven mode, trajectory extrapolation is performed through the physical model, the theoretical completeness of the physical model and the flexibility of the data-driven model are effectively combined, and the prediction precision in a high-dynamic flight scene is improved.

The embodiment of the invention provides a large-scale low-altitude flight safety dynamic calculation parallel scheduling method and device, and is applied to the technical field of low-altitude airspace safety management. The method comprises the following steps of: gridding a low-altitude airspace based on a geographic coordinate system to generate geographic space grids, and performing grid coding on each grid; dividing each grid into a calculation area and a buffer area; the calculation area is a core operation unit and is used for real-time dynamic calculation and parallel scheduling of large-scale low-altitude flight safety, and the buffer area is a data interaction hub and is used for independently loading and caching grid data of adjacent areas; and according to the aircraft position information and the security envelope range, matching the aircraft to the calculation area to which the aircraft belongs, and routing the aircraft data to the corresponding buffer area. On the basis, inter-partition calculation decoupling can be achieved through cooperative work of the calculation area and the buffer area, the low-altitude flight safety dynamic calculation efficiency is remarkably improved, and therefore a real-time and efficient safety calculation solution is provided for a high-density low-altitude flight scene.

The invention provides a flight potential standardization evaluation method based on rapid teaching and flight path assistance, and relates to the technical field of flight simulation evaluation. The method comprises the following steps: firstly, establishing a target capability model including understanding and accepting capability, control capability, attention capability and strain capability, and compiling a simulated flight test according to a cognitive diagnosis theory; constructing a scene library based on the target capability model, configuring track assistance for each flight scene, and marking excitation intensity and discriminability parameters of each flight scene for each capability; short-time rapid pre-teaching is implemented according to a standardized teaching script before evaluation; during evaluation, a multi-capability probe is embedded in a flight scene, evaluation data is collected, a capability estimation value is updated based on a capability-scene matching model, a subsequent flight scene is adaptively selected or scene parameters are adjusted according to the capability estimation value to generate a personalized examination path, a comprehensive score is calculated, and a four-dimensional capability profile map is output. The objectivity of the evaluation result can be improved.

The invention discloses a non-ideal environment-oriented adaptive closed-loop flight control ICD protocol simulation verification system and method, and belongs to the technical field of software information security analysis, and the non-ideal environment-oriented adaptive closed-loop flight control ICD protocol simulation verification system comprises a basic modeling and simulation module which is used for constructing a flight control system virtual prototype; the non-ideal environment injection module is used for injecting disturbance models of a physical layer, a link layer and a node layer into the virtual bus and the node; the dynamic scene driving module is used for dynamically generating ICD data according to the flight scene data; the intelligent monitoring and analysis module is internally provided with an anomaly detector based on a graph neural network and outputs a structured diagnosis report; and the self-adaptive optimization guide module is internally provided with an optimization strategy engine based on reinforcement learning, generates optimization suggestions and selectively and automatically adjusts configuration to initiate re-verification. The reliability and the research and development efficiency of a flight control system are remarkably improved by simulating a real operation environment in a high-fidelity manner in a design stage.

The invention relates to the technical field of flight models, in particular to a method and device for building a flight scene physical model, and the device comprises a frame, a lower supporting plate, a sand table plate, an elevator, a flight simulation suite, and an upper supporting plate. The flight simulation suite comprises a suspension device, a driver and an aircraft model; the suspension device and the driver are attracted through magnetic force and installed on the lower supporting plate and the upper supporting plate in a clamped mode, the aircraft model is upwards connected to a winding mechanism of the suspension device through a silk thread, the height of the aircraft model in the Z direction is adjusted by controlling the winding mechanism to wind and unwind the suspension silk thread, and the driver drives the suspension device to move in the plane. Therefore, the plane space positions of the aircraft models in the X direction and the Y direction are changed, the lifter is transferred between the upper supporting plate and the lower supporting plate, and the multiple sets of aircraft models can be stored or added into display activities.

The invention discloses an intelligent pilot post competency monitoring device and method. The device comprises a monitoring cloud platform display unit, a display unit, a control unit, a data collecting and processing unit and a post competency system. The pilot post competency assessment method effectively solves the technical problems of discontinuous monitoring, non-objective assessment and non-intercommunication of data in the existing pilot post competency assessment method. According to the method, the strong relevance between training investment and efficient improvement of safety performance is improved, low-cost and efficient pilot post competency evaluation is realized, the method adapts to variable requirements of future flight scenes, and a scientific, accurate and flexible selection and evaluation solution is provided.

The invention discloses a multi-source data fusion positioning monitoring method and system for a low-altitude aircraft. The method comprises the following steps: collecting multi-source data, carrying out abnormal data processing, and then carrying out space-time alignment; dividing the Beidou absolute position data into different scene regions, preliminarily fusing the aligned multi-source data in the scene regions, configuring basic weights of the multi-source data in different flight scenes, and calculating dynamic weights of the multi-source data in real time based on equivalent variances of the multi-source data to obtain real-time comprehensive weights of the multi-source data; and performing state space fusion based on the preliminary fusion positioning information and the real-time comprehensive weight of each piece of multi-source data. According to the method, the pain point that a single data source is easily interfered, drifted or invalid is solved, and meanwhile, the real-time weight of each multi-source data can be intelligently optimized according to a task environment, real-time data quality and a task instruction, so that a fusion positioning result is corrected, and reliable monitoring in dynamic tasks such as emergency search and rescue, logistics transportation and the like is guaranteed.

The invention discloses a predetermined time adaptive control method for a wing-riding separation variant gliding aircraft, and the method specifically comprises the following steps: firstly, constructing a time scale function, and effectively avoiding the problems of unlimited increase of control quantity and singularity; secondly, designing a preset time sliding mode surface based on the time scale function; thirdly, providing a neural network parameter identification strategy, and converting a system identification problem into a parameter estimation problem so as to adapt to a flight scene with uncertain aerodynamic parameters; and finally, designing a preset time self-adaptive sliding mode controller, and realizing convergence in specified time under the condition of ensuring that the system state is not dependent on an initial condition. The adaptive gain of the controller can be dynamically adjusted according to the system environment, jitter can be inhibited, tracking errors can be reduced, and the influence caused by centralized uncertainty can be weakened; in conclusion, the control method not only realizes accurate attitude tracking, but also achieves preset time convergence characteristics irrelevant to initial conditions and control parameters, and has excellent quick responsiveness, stability and robustness.

The invention discloses a moire dynamic rendering method and device for an aircraft simulator instrument, and belongs to the technical field of aircraft simulators, data processing and artificial intelligence. The method comprises the following steps: based on real-time data of an aircraft simulator, utilizing a self-attention mechanism to generate a dynamic weight of each physical quantity during moire rendering; utilizing the dynamic weight of each physical quantity to calculate characteristic parameters of moire; and carrying out moire rendering and display on an instrument of the aircraft simulator by utilizing the characteristic parameters. According to the method, moire rendering can be carried out in an instrument, the moire is used for representing the flight scene state, and the multi-step abstract conversion cost of mapping a numerical value into a physical state and mapping the physical state into a flight situation by a pilot can be eliminated by using visual features; according to the invention, a pilot can instantly sense the change of the flight environment from the instrument, and in an emergency flight state, the pilot can quickly and accurately make a flight decision by using intuitive feeling, so that the user experience can be improved.

The embodiment of the disclosure provides a large-scale low-altitude flight safety dynamic calculation parallel scheduling method and device, which is applied to the technical field of low-altitude airspace safety management. The method comprises the following steps: generating a geographical space grid by griding a low-altitude airspace based on a geographical coordinate system, and performing grid coding on each grid; dividing each grid into a calculation area and a buffer area; the calculation area is a core operation unit, which is used for real-time dynamic calculation and parallel scheduling of large-scale low-altitude flight safety, and the buffer area is a data interaction hub, which is used for independently loading and caching grid data of adjacent areas; according to the position information and the safety envelope range of the aircraft, the aircraft is matched to the calculation area to which the aircraft belongs, and the aircraft data is routed to the corresponding buffer area. Based on this, the calculation decoupling between the partitions can be realized through the cooperative work of the calculation area and the buffer area, the dynamic calculation efficiency of the low-altitude flight safety is significantly improved, and therefore a real-time and efficient safety calculation solution is provided for a high-density low-altitude flight scene.

An aerodrome maintenance apparatus for monitoring runway and taxiway conditions and remotely reporting the status of the runway or taxiway. The apparatus comprises a drive unit operable to provide self-controlled rolling movement of the apparatus along a surface of a runway or taxiway of the aerodrome, a detection unit comprising one or more sensors configured to detect one or more parameters of the surface, and a communications unit comprising a transceiver arranged to transfer data derived from the detection unit from the apparatus to a remote server. The apparatus is arranged, in use, to move along the surface and transfer data representative of one or more parameters of the surface to a remote server.

The invention provides a cloud detection method and system for a low-altitude aircraft, and relates to the field of meteorological detection of low-altitude aircrafts. The system comprises a laser measurement module and a control assembly, and the laser measurement module can emit laser pulses, receive back scattering light signals reflected by a target cloud layer and transmit the back scattering light signals to the control assembly. The control assembly can determine the distance from the low-altitude aircraft to the target cloud layer and the thickness of the target cloud layer in the sailing direction based on the signal intensity time sequence of the backward scattering light signals. Compared with an image sensor, the influence of illumination on the laser pulse and the back scattering light signal is low, so that the accuracy of detecting the distance from the low-altitude aircraft to the target cloud layer and the thickness of the target cloud layer in the navigation direction is high; and compared with the existing measuring equipment, the low-altitude aircraft is limited in maneuvering flight scene use and is difficult to be suitable for small and medium-sized low-altitude aircrafts. Therefore, the cloud detection system provided by the invention is relatively high in practicability.

The method for designing an autopilot controller for flying objectives (FOs) that adapts to velocity, altitude, and overload consists of two parts: part I focuses on determining the initial controller, and part II focuses on determining the adaptive controller. This method eliminates transfer function zeros, prevents continuous integration, and limits the control signal to ensure the operational conditions of the control loops. The use of a unified control structure allows for a consistent design and tuning process across all three control channels, thereby generalizing the control problem. The solution ensures strong adaptability across a wide range of flight scenarios for FOs, particularly those operating at high velocities, with high overload, and continuously changing altitudes.

The application discloses a kind of cloud stripe dynamic rendering method and device of aircraft simulator instrument, belong to aircraft simulator, data processing and artificial intelligence technical field.The method includes: based on the real-time data of aircraft simulator, utilize self-attention mechanism to generate the dynamic weight of each physical quantity for cloud stripe rendering;Utilize the dynamic weight of each physical quantity, calculate the characteristic parameter of cloud stripe;Utilize characteristic parameter, carry out cloud stripe rendering and display on the instrument of aircraft simulator.The application can carry out cloud stripe rendering in instrument, utilize cloud stripe to characterize flight scene state, utilize intuitive visual feature to eliminate pilot to carry out the multi-step abstract conversion cost of numerical value mapping into physical state, physical state mapping into flight situation, pilot can perceive the change of flight environment from instrument instantaneously, when facing emergency flight state, pilot can utilize intuitive feeling to make flight decision quickly and accurately, so as to improve user experience.

The invention provides a flight navigation map element display method and device based on cognitive behavior optimization. The method comprises the following steps: firstly, constructing an eye movement stimulation material library covering a full flight scene of takeoff, cruising and approaching landing; collecting eye movement data and subjective importance evaluation data of a pilot by systematically presenting the sub-scene stimulation material to the pilot; calculating a visual importance index of each element based on the eye movement data; fusing subjective and objective data to obtain a comprehensive importance index; calculating a display priority by combining a preset scene weight and a proportional scale-load mapping relation of each flight stage; and dynamically controlling the elements to be implicit according to the priority. Through standardized scene cognitive behavior data acquisition and quantitative analysis, personalized and adaptive display of flight navigation map elements is realized, the cognitive load of a pilot is effectively reduced, and the navigation efficiency and the flight safety are improved.

The application relates to the technical field of aviation ground support equipment, in particular to an airport mobile weeding machine structure, which comprises a collecting structure for crushing and collecting impurities and a fixing structure for replacing an auxiliary rod, one side of the fixing structure is fixedly connected with a rotating rod, and the top of the rotating rod is rotationally connected with a pushing rod. The application can realize convenient replacement and stable fixing of the auxiliary rod through the fixing structure, solves the technical problems of inconvenient replacement and unstable fixing of the auxiliary rod, and can improve work efficiency and equipment stability.

The invention belongs to the technical field of comprehensive avionics, and discloses a multi-flight-scene avionics service dynamic scheduling method and system, and the method comprises the steps: constructing a flight scene library which comprises four flight stages of sliding, takeoff, cruising and landing and three flight conditions of extreme severe weather, conventional complex weather and clear sky standard weather; the avionics function is divided into strong real-time sub-services, medium real-time sub-services and weak real-time sub-services according to real-time requirements, and the sub-services are registered to a distributed service center; according to the method, sub-services are matched for each scene, a service-resource quantitative mapping rule is defined, a resource utilization rate, key service response delay and fault recovery time are taken as constraint targets, a reinforcement learning reward function under a multi-flight scene condition is designed, operation indexes are collected in real time, the weight of the reward function is dynamically adjusted, and closed-loop scheduling is formed. The problem that dynamic resource scheduling of the avionics system in multiple scenes is difficult is solved.

The invention provides an intelligent flight decision-making auxiliary system and method based on multi-modal flight data, and relates to the technical field of aviation flight, and the method comprises the steps: firstly obtaining multi-source flight data which comprises multiple monitoring dimensions such as a flight attitude, an external environment, a dynamic parameter and the like and has a time correlation attribute; extracting performance characteristics and collaborative change characteristics of data of different monitoring dimensions in each flight scene, establishing a dynamic association model, determining influence weights based on the dynamic association model, generating scene decision factors, establishing association rules of influence transfer characteristics and flight operation response logic, and constructing a decision response link; finally, logic in the decision response link is converted into natural language expression, an intelligent flight decision auxiliary instruction containing flight operation suggestions and data monitoring key points is output, and the flight safety and efficiency can be effectively improved.

The invention relates to a target sensing method and device for a low-altitude flight scene, equipment and a medium. The method comprises the following steps: acquiring real-time detection data of a to-be-identified target by a plurality of heterogeneous sensors preset on an aircraft; based on the real-time detection data, determining a cooperation state of the to-be-identified target; determining an initial fusion weight for each heterogeneous sensor based on the current distance between the to-be-identified target and the aircraft and the cooperation state; calculating a dynamic confidence score in real time aiming at each observation of each heterogeneous sensor on the to-be-identified target; for each heterogeneous sensor, adjusting the initial fusion weight of the heterogeneous sensor according to the dynamic confidence score of the heterogeneous sensor in each observation to obtain a target fusion weight; and performing weighted fusion according to the real-time detection data of each heterogeneous sensor in each observation and the target fusion weight to obtain state estimation of the to-be-identified target after fusion in each observation. And the environment perception capability and the navigation safety level of the flying platform are improved.

A flight auxiliary decision-making method based on multi-source aviation information priority calculation, comprising the following steps: step 1, constructing a three-layer aviation information model; step 2, defining a typical flight scene and dividing a standard flight stage; step 3, constructing a structured flight stage-data element information priority matrix and a flight scene-data element information priority matrix; step 4, judging the current flight stage according to real-time data of multi-source aviation information; step 5, identifying the current flight scene according to real-time data of multi-source aviation information and logical rules of the typical flight scene; step 6, calculating the comprehensive priority of information according to the current flight stage and the flight scene; and step 7, generating flight decision information according to the comprehensive priority and controlling the information content and display form of the onboard display. The application controls the information content of air-ground link transmission and onboard device display in the typical scene, generates a flight decision information demand model, and assists the pilot in making flight decisions.

The invention relates to the technical field of unmanned aerial vehicle control, and discloses an unmanned aerial vehicle control method, device and equipment and a storage medium, and the method comprises the steps: obtaining a target flight scene, and carrying out the scene data collection of the target flight scene, so as to obtain a scene data set; performing three-dimensional modeling based on the scene data set to obtain a three-dimensional scene model; generating a preliminary flight path based on the three-dimensional scene model and a preset obstacle avoidance constraint condition; performing paragraph division on the initial flight path to obtain paragraph feature parameters; generating a preliminary control parameter based on the paragraph feature parameter; integrating the preliminary flight path and the preliminary control parameters into a flight control instruction; according to the invention, based on the complete process of scene perception, three-dimensional modeling, path generation, paragraph feature extraction, parameter matching and instruction integration, the flight control instruction adaptive to the actual flight demand is generated, the problem of poor adaptability of the flight path and the control parameter in the prior art is solved, and the flight stability and accuracy of the unmanned aerial vehicle are improved.

The invention discloses a supersonic aircraft noise audible visualization method and device, and relates to the field of aviation acoustics. Firstly, supersonic aircraft engine parameters are obtained; and calculating noise data generated by different parts of the supersonic aircraft engine through a data prediction algorithm. Secondly, carrying out superposition and dynamic correction on noise data of different parts; and constructing a three-dimensional model of the aircraft and the flight scene. And finally, superposing the noise test virtual scene with a real scene, testing the supersonic aircraft engine, and displaying a test result. According to the method, on the basis of the mixed reality technology, an approval person and a designer are allowed to experience personally and evaluate the noise influence in a virtual environment, so that whether the design meets regulatory requirements or not is more effectively verified, abstract noise data are converted into audible and visual immersive experience, complex noise prediction data are displayed in a real-time and three-dimensional mode, and the method is more practical. And a designer can intuitively find the noise problem.

The present application relates to the field of flight environment simulation visualization, in particular to a flight environment simulation multi-source data dynamic effect three-dimensional visualization generation method, comprising: obtaining real-time state parameters of an aircraft, flow field disturbance, meteorological particles and dynamic environment parameters of terrain shielding through a sensor network and a meteorological server, synchronizing time stamps and aligning spatial coordinates of the data, and forming a unified space-time reference original flight scene data set; generating a dynamic three-dimensional effect field containing time evolution characteristics by using an improved adaptive fusion algorithm, including three-dimensional morphology of flow field disturbance, three-dimensional distribution of meteorological particles and three-dimensional gradient of terrain shielding; and outputting a three-dimensional flight environment simulation image with fused dynamic environment visual effects by real-time drawing in a graphics rendering pipeline according to the effect field and a basic three-dimensional geographic model. The present application realizes integrated rendering of multi-source data space-time fusion and environment dynamic effects, and is suitable for flight simulation, avionics simulation and airspace visualization scenes.

The application provides an intelligent flight decision assistance system and method based on multi-modal flight data, and relates to the technical field of aviation flight. First, multi-source flight data containing multiple monitoring dimensions such as flight attitude, external environment and power parameters and having time correlation attributes are acquired. Then, the performance characteristics and cooperative change characteristics of different monitoring dimension data in each flight scene are extracted, a dynamic correlation model is established, the influence weight is determined based on the dynamic correlation model, the scene decision factor is generated, the association rules of the influence transmission characteristics and the flight operation response logic are established, the decision response link is constructed, and finally the logic in the decision response link is converted into natural language expression. The intelligent flight decision assistance instruction containing flight operation suggestions and data monitoring priorities is output, and the flight safety and efficiency can be effectively improved.

An aircraft assistance system measuring a wind speed and direction in a vicinity of an aerodrome and calculating a wind speed and direction in a path, along which the aircraft approaches or departs, and predict wind data representing a wind speed and direction in the path for a predetermined future time period. Also an aircraft that receives the predicted wind data transmitted by the aircraft assistance system and determines the predicted wind speed and direction along the path, and displays a visualization about the predicted wind speed and direction or provides an autopilot system adapting a flight path accordingly.