44 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 relates to a visual feature adaptation method based on flight scene category driving, and belongs to the technical field of image processing. The method comprises the following steps: establishing a scene classification data set with labels; constructing an image feature extraction algorithm set; performing feature extraction on the images of the various flight scenes in the scene classification data set by using algorithms in the algorithm set one by one, and performing feature merging and dimension reduction to obtain representative features corresponding to the various scene images; then image clustering is carried out, and representative features of all images under each algorithm are clustered into clusters with the same number of scene categories through clustering; and according to the clustering result and the actual scene classification label of the image, calculating the index of the feature adaptation degree, which is used for representing the adaptation degree of the image feature extraction algorithm for processing a certain scene image. According to the method, accurate comparison of feature adaptation degrees of different feature extraction algorithms under various flight scene categories is realized, and a scientific basis is provided for feature selection in an aircraft visual task.

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.

A system for global auto-configuration of at least one airport signaling device (11) of an aerodrome, said system comprising: a central control unit (14) and signaling devices (11), wherein the central control unit (14) is capable of communicating with the airport signaling devices (11) via the communication module (119) once a communication channel has been initiated; wherein the system is configured to communicate configuration data of at least one signaling device (11) to an Internet of Things (loT) hub (210), namely the identity code and the estimated location of the at least one signaling device; wherein the Internet of Things (loT) hub is capable of data communication with plurality of servers (220) configured to store inventory data related to a set of registered airport aeronautical signaling devices for at least one aerodrome for a predefined geographical area.

The invention provides an unmanned aerial vehicle mode switching control method and system, and relates to the technical field of mode switching control, and the method comprises the steps: constructing a flight scene vector, and carrying out the fitness evaluation; if the flight mode adaptation coefficient is smaller than or equal to the flight mode adaptation threshold value, generating a mode switching decision; switching accident suppression compensation adjustment is carried out on the mode switching decision according to the flight scene vector; loss constraint optimization is carried out on the switching adjustment first group according to the switching loss evaluation model; and a switching propagation constraint condition is introduced, propagation optimization is carried out, a switching optimization strategy is obtained, and mode switching control is carried out on the unmanned aerial vehicle. According to the method and the device, the technical problem that the flight safety of the unmanned aerial vehicle is affected due to the fact that the unmanned aerial vehicle mode switching lacks fine control and is easy to cause instability at the switching moment in the prior art is solved, the flight scene vector is constructed and the mode switching decision is made based on the fitness evaluation, the stability of the unmanned aerial vehicle mode switching is improved, and the flight safety of the unmanned aerial vehicle is improved. Therefore, the flight safety is improved.

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 provides an anti-vibration and anti-airflow inertial sensor module suitable for a flight scene, and relates to the technical field of inertial measurement. The inertial sensor module comprises a rectangular core body, twelve sensor chips, a digital circuit and a damping structure, wherein each sensor chip comprises an accelerometer and a gyroscope; the rectangular core body, the twelve sensor chips and the digital circuit are nested in the damping structure and are not in contact with the interior of the damping structure; the rectangular core body comprises six outer side surfaces, and for each outer side surface of the rectangular core body, two sensor chips are arranged on the outer side surface to obtain X-axis data and Y-axis data of the position of the outer side surface; the digital circuit is arranged in a preset area on the outer side face of the rectangular core body and used for determining acceleration data and rotation acceleration data of the position where the inertial sensor module is located in a three-dimensional space according to the X-axis data and the Y-axis data obtained by the twelve sensor chips. The anti-vibration performance and the measurement precision of the inertial sensor module 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 stealth aircraft maneuvering avoidance method and system under a quasi six-degree-of-freedom assumption, and the method comprises the steps: S100: obtaining an azimuth angle theta corresponding to an RCS peak in an RCS curve, and determining a high RCS region of an azimuth angle domain as [theta-w / 2, theta + w / 2], where w is the width of the RCS peak; s200, determining a high RCS flight path segment on the initial flight path; s300, setting a first turning point, a second turning point and a third turning point, and taking the first turning point, the second turning point and the third turning point as sequentially adjacent track control points to generate a maneuvering track; and S400, the aircraft flies along the initial flight path, flies along the maneuvering flight path when reaching the first turning point, and returns to the initial flight path and continues to fly along the initial flight path when reaching the third turning point. According to the invention, the exposure risk of the aircraft in a real three-dimensional flight scene can be reduced.

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.

This invention relates to the field of flight training assessment technology and discloses a flight training assessment system that integrates electroencephalogram (EEG) characteristics and physiological indicators. The system includes a physiological signal acquisition module that simultaneously captures multi-channel raw EEG signals and surface physiological indicator data, including ECG R-R interval sequences, respiratory wave frequency and amplitude, and skin conductance response amplitude; a multimodal fusion module that analyzes the ECG R-R interval sequences to generate a heart rate variability feature vector and establishes a dynamic correlation mapping between EEG entropy values ​​and physiological feature vectors; a cognitive state modeling module that generates a cognitive load index based on the dynamic correlation mapping and constructs a cognitive stability quantification matrix; an adaptive feedback module that receives relevant data and dynamically adjusts simulated flight scenario parameters; and an assessment output module that integrates data to generate a comprehensive training assessment report including neurophysiological coordination scores and operational accuracy ratings. This system enables comprehensive assessment and dynamic training adjustment of the pilot's cognitive state.

The application discloses a flight behavior recognition method based on aircraft intention in an autonomous operation mode. Firstly, aircraft behavior features are extracted from the time and space levels; secondly, an aircraft flight intention model in a typical flight scene is constructed; thirdly, the aircraft behavior features are analyzed by clustering based on a BIRCH clustering model, and the typical behaviors of the aircraft in flight are divided; and finally, the real-time behavior feature values are calculated based on the flight intention model, and online behavior recognition of the aircraft flight is realized. The aircraft behavior features are constructed from the time and space angles, so that the aircraft behavior is more visualized. In addition, the aircraft flight intention model can adapt to dynamic change scenes and is more flexible. Finally, the BIRCH model can adapt to the process of incremental clustering and meet the real-time performance of online behavior recognition.

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 utility model relates to a remote control aircraft model which comprises a helicopter main fuselage, a main rotor wing, a tail rotor wing, a battery and a flight controller, the main rotor wing is rotatably installed above the helicopter main fuselage, the tail rotor wing is rotatably installed at the tail of the helicopter main fuselage, and the battery and the flight controller are installed in the helicopter main fuselage. A GPS module, an obstacle avoidance sensor, an electronic speed regulator, a main motor and a tail motor are further installed in the helicopter main body, the battery provides electric energy for the whole helicopter, the remote control aircraft model integrates the GPS module and the obstacle avoidance sensor, obstacles can be accurately positioned and avoided, the safety of the aircraft is greatly improved, and the unmanned aerial vehicle is suitable for being popularized and used. And the flight controller is provided with a GPS positioning mode, an automatic return flight mode and a 3D flight mode, and can automatically return to a take-off point when signals are lost or the electric quantity is insufficient, so that the flight risk is further reduced, and multiple flight modes meet the requirements of users in different flight scenes.

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.