15403 results about "Airplane" patented technology

An aircraft defining a longitudinal centerline and extending between a forward end and an aft end is provided. The aircraft comprises a fuselage extending between the forward end of the aircraft and the aft end of the aircraft; a wing assembly extending laterally outwardly with respect to the longitudinal centerline from a portion of the fuselage; an unducted turbofan engine including an unducted fan defining a fan diameter; and a pylon fairing that connects the unducted turbofan engine to the wing assembly, the pylon fairing defining a leading edge and including a first inflection point along the leading edge, the first inflection point defining a first radius of curvature that is less than 5 times the fan diameter and greater than 0.1 times the fan diameter.

An attitude display system for use in an aircraft has at least one display unit visible by a pilot within a cockpit. A symbology generator is configured for receiving input from at least one attitude sensor and generating symbology image data representative of a pear-shaped attitude indicator, distorted vertically to represent a pitch of the aircraft and rotated to represent a roll angle of the aircraft. The symbology generator may further be configured for adding a horizontal line that represents a horizon, a regular trapezoid representing a downward gravity vector at a base of the trapezoid, a pitch angle of the aircraft, split wings representing an angle of attack of the aircraft, and a stall warning in a sawtooth crack shape. A tail portion of a T-shape with the curved top edge is itself curved in a direction opposite that of an aircraft spin direction.

A display system of an aircraft includes a display device defining a display area, a vision system for generating an image of an operating environment of the aircraft on the display area, data processors operatively coupled to the display device and the vision system, and non-transitory machine-readable memory operatively coupled to the one or more data processors and storing instructions executable by the one or more processors and configured to cause the one or more processors to, when a condition of the aircraft is met, cause an alteration of a display of flight information on the display area to declutter a cutout region in the image generated by the vision system, the cutout region devoid of imaging generated by the vision system and displaying an Approach Lighting System (ALS) of a runway of intended landing for the aircraft.

Systems and methods are provided for promoting stable aircraft approach conditions. The system comprises a display device that is onboard an aircraft and a controller in communication with the display device. The controller is configured to, by a processor: receive data that includes information relating to an action configured to stabilize an approach of the aircraft during landing thereof and a recommended timing of performing the action relative to a predetermined flight plan of the aircraft, and render a first visual element on the display device that is configured to display the action relative to the flight plan and dynamically indicate the recommended timing of performing the action relative to a geographic position of the aircraft along the flight plan.

Described herein is an electric aircraft comprising a battery pack to power the aircraft. The battery pack comprises a housing, an arrangement of battery cells within the housing and a crumple structure associated with the battery pack. The crumple structure is beneath the arrangement of battery cells and is adapted to compress in the event of an impact from beneath the aircraft. A venting channel is fluidically coupled to the battery cells and arranged to vent gasses away from the battery cells. The venting channel passes through the crumple structure and is adapted to deform with the crumple structure in the event of an impact from beneath the aircraft.

The invention discloses a dynamic path planning and self-adaptive control method and system for a coating robot, and relates to the technical field of coating automation. The method comprises the following steps: acquiring point cloud data through three-dimensional scanning equipment, constructing a dynamically updated workpiece curved surface model, and extracting curvature, edge and high-curvature mutation region features; a spraying path is generated based on a reinforcement learning algorithm, and path density, speed and coating supply are dynamically adjusted for a high-curvature area; distance, force feedback and environment parameters are fused, and mechanical arm and spray gun parameters are dynamically adjusted; dividing operation sub-areas and distributing tasks based on robot capability characteristics to realize multi-machine cooperation; and fault redundancy control and multispectral imaging are added to optimize the coating quality. The system comprises a sensing module, a decision-making module, an execution module, a redundancy control module and a communication module. According to the invention, the uniformity of the complex curved surface coating, the multi-machine cooperation efficiency and the system anti-interference capability are improved, and the method is suitable for spraying large workpieces such as aircraft fuselages and high-speed rail vehicle bodies.

The invention relates to the technical field of aircraft structure detection, and discloses an aircraft structure crack intelligent identification method based on deep learning. The method comprises the following steps: acquiring original vibration response signals and electromagnetic field distribution data on the surface and inside of an aircraft structure in parallel through a multi-source sensor network; synchronously processing the data by using a multi-scale convolutional neural network, and extracting time-frequency domain abnormal fluctuation features and space magnetic field distortion features; constructing a cross-modal correlation model, analyzing a topological dependency relationship of the two types of features through a graph attention mechanism, and generating a fused damage sensitive feature vector; inputting the vector into a pre-trained deep belief network to obtain a probability distribution mapping relation for different crack types; and according to the mapping relation, carrying out adaptive weighted fusion on original multi-sensor data, inhibiting environmental noise and structural background interference, and separating and reconstructing an accurate three-dimensional morphology map of the target crack. According to the method, multi-source data information can be effectively fused to improve the accuracy of aircraft structure crack identification.

Systems and methods of the invention generally relate to prolonging viability of bodily tissue, especially an organ such as a lung, by adjusting pressure as needed to maintain a constant pressure within the organ even during external pressure fluctuations due, for example, to transportation of the organ in an airplane. Gas passing into and out of the organ may be conditioned to prolong tissue viability.

Systems and methods herein generally relate to prolonging viability of bodily tissue, especially an organ, by adjusting pressure as needed to maintain a constant pressure within the organ even during external pressure fluctuations due, for example, to transportation of the organ in an airplane. The systems and methods herein can include an electronic pump that pumps gas into an organ and a mechanical pressure regulator to release gas based on organ pressure.

Disclosed in the present invention is a neural network-based defect detection method for gluing quality on aircraft skin. The method includes: data acquisition: taking photos of aircraft skin by using a camera to acquire image data; preprocessing the acquired image data; annotating the data by using annotation software to acquire a data set for network training; establishing a defect detection network model based on feature erasure and boundary refinement, where the defect detection network model includes a feature extraction network, a semantic-guided feature erasure module, a multi-scale feature fusion network, and a defect prediction network based on boundary refinement, which are sequentially connected, the data set is used for training the network model, and trained model parameters are saved; and detecting a directly collected skin gluing image by using the trained network model and outputting detection results.

The invention discloses an extreme climate self-adaptive flight control system for an unmanned aerial vehicle in a complex terrain, and relates to the technical field of unmanned aerial vehicle self-adaptive flight control. The extreme climate adaptive flight control system for the unmanned aerial vehicle in the complex terrain comprises a flight data acquisition and preprocessing module, a climate prediction and risk assessment module, an optimal path and task sequence adjustment module, a real-time flight control and path optimization module and a safety emergency response and recording module. Wherein the flight data acquisition and preprocessing module is used for acquiring flight data; the climate prediction and risk assessment module is used for constructing a neural network model to predict climate; the optimal path and task sequence adjusting module is used for performing path and task security evaluation; the real-time flight control and path optimization module is used for converting a path and a task sequence into an aircraft instruction; and the safety emergency response and recording module is used for executing and recording the emergency strategy. The problem that the unmanned aerial vehicle is difficult to adjust flight in real time due to continuous change of climate states in the prior art is solved.

The embodiment of the invention provides a multi-configuration relay-oriented aircraft electrical box parameter measurement system and method, and belongs to the field of aircraft electrical box test and diagnosis. According to the hardware level, flexible access of a multi-configuration relay electrical box is achieved based on a universal adapter interface, core parameter measurement is completed in combination with an integrated measurement and control circuit, and synchronous acquisition and processing are conducted on multiple paths of signals through a signal acquisition and processing unit; according to the software level, the pull-in / release time, the rebound time and the voltage parameters are accurately calculated through a parameter calculation module on the basis of waveform feature point recognition and dynamic excitation-response theories, and the functions of fault diagnosis, safety protection and data storage are integrated. According to the method, the crossing from on-off judgment to parameterized precise evaluation is realized, the detection efficiency, the measurement precision and the equipment reliability evaluation capability are remarkably improved, and an integrated solution is provided for external field maintenance and state prediction of the aircraft relay.

A gas turbine engine for an aircraft. The gas turbine engine comprising: a combustor, comprising a combustion chamber and a plurality of fuel spray nozzles configured to inject fuel into the combustion chamber, wherein the plurality of fuel spray nozzles comprises a first subset of fuel spray nozzles and a second subset of fuel spray nozzles, wherein the combustor is operable in a condition in which each of the fuel spray nozzles of the first subset of fuel spray nozzles is supplied with fuel at a greater fuel flow rate than each of the fuel spray nozzles of the second subset of fuel spray nozzles, wherein a ratio of the number of fuel spray nozzles in the first subset of fuel spray nozzles to the number of fuel spray nozzles in the second subset of fuel spray nozzles is in the range of 1:2 to 1:5. An MTO nvPM emissions index ratio-modified fuel flow is defined as:EImaxTO,SAFEImaxTO,FF×Wf,maxTOwhere: EImaxTO,SAF is the system loss corrected nvPM emissions index in mg / kg of the gas turbine engine when operating at around 100% available thrust for given operating conditions if a fuel provided to the plurality of fuel spray nozzles comprises a sustainable aviation fuel (SAF); EImaxTO,FF is the system loss corrected nvPM emissions index in mg / kg of the gas turbine engine when operating at around 100% available thrust for the given operating conditions if a fuel provided to the plurality of fuel spray nozzles is a fossil-based hydrocarbon fuel; and Wf,maxTO is the mass flow rate of fuel provided to the plurality of fuel spray nozzles in kg / s when the gas turbine engine is operating at around 100% available thrust for the given operating conditions. The MTO nvPM emissions index ratio-modified fuel flow of the gas turbine engine in kg / s is less than 2. The gas turbine engine is configured to provide fuel comprising a SAF to the plurality of fuel spray nozzles. Also disclosed is a method of operating the gas turbine engine.

The invention discloses an aircraft surface crack intelligent detection and measurement method combining an image and a point cloud. The method comprises the following steps: carrying out two-dimensional image and three-dimensional point cloud data acquisition on an aircraft surface; performing crack defect identification on the acquired two-dimensional image based on a target detection model; aligning the two-dimensional image with the three-dimensional point cloud, and acquiring corresponding crack defect three-dimensional point cloud data according to the crack defect position identified from the two-dimensional image; and performing filtering and down-sampling processing on the obtained three-dimensional point cloud data of the crack defects, and performing crack defect size measurement on the processed three-dimensional point cloud data of the crack defects to obtain length, width and depth information of the crack defects. An omnibearing defect detection system is constructed by fusing two-dimensional image processing and three-dimensional point cloud analysis technologies; the texture features of the two-dimensional image and the depth information of the three-dimensional point cloud are organically combined, so that the detection capability of the system is improved, and accurate identification and size measurement of the aircraft surface crack defects are realized.

The utility model relates to a variable-configuration tilting quad-rotor unmanned aerial vehicle which comprises rotors (1), motors (2), main wings (3), a fuselage (4), a vertical fin (7), a power supply unit (8), a control unit (9), tilting steering engines (10), driving rocker arms (11), tilting connecting rods (13), tilting rod supports (16), front tilting rods (17), rear tilting rods, front driven rocker arms (18) and rear driven rocker arms. The tilting mechanism is simple in configuration form, the appearance of the whole tilting mechanism is not greatly changed in the tilting process, and the pneumatic influence in the tilting process is relatively small. When the rotors tilt forwards, a conventional rotor fixed wing aircraft mode is adopted, when the rotors tilt upwards, a conventional four-rotor unmanned aerial vehicle mode is adopted, and various modes and modes such as vertical take-off and landing, hovering and forward flying can be achieved.

A method for monitoring a rotating machine in order to detect a fault in a bearing, the method including acquiring, from the rotating machine, a vibration signal measured by a vibration sensor; determining a first-order spectrogram by first-order cyclostationary analysis of the vibration signal using a delta transform and spectral standardisation; determining a second-order spectrogram by second-order cyclostationary analysis of the vibration signal using averaged cyclic coherence, a delta transform and spectral standardisation; and detecting a vibration signature of the fault in the bearing on the basis of the first-order spectrogram and the second-order spectrogram.

An aircraft includes a flight deck including a flight deck door configured to be moved between an open position and a closed position, a first monument, second monument, and a secondary barrier door moveably secured between the first monument and the second monument. The secondary barrier door is configured to fold into a stowed position in which a path to the flight deck is open, and unfold into a deployed position in which the path to the flight deck is closed.

The invention provides a multi-scale cross-space learning general aviation aircraft landing runway detection method, and relates to the technical field of computer vision. The method comprises the following steps: firstly, collecting a runway image data set when a general aviation aircraft lands, preprocessing the data set, and dividing the data set into a training set and a test set; then, an AES-YOLOv8 network model for detecting a multi-scale runway target is constructed; the model is based on a YOLOv8s network of multi-scale cross-space learning, and a Backbone network comprises a plurality of improved lightweight channel attention convolution modules LA-AKConv; an EMA attention mechanism is introduced after a spatial pyramid pooling module SPPF of the Backbone network; the Neck network comprises a plurality of C2fSCConv modules fused by C2f and a space and channel reconstruction convolution module SCConv; and the AES-YOLOv8 network model is trained based on the preprocessed data set to obtain a multi-scale cross-space learning airport runway detection model, and the runway state of the general aviation aircraft during landing is detected in real time through the multi-scale cross-space learning airport runway detection model.

The invention provides a physical response data analysis method and system based on aircraft catalytic operation, and the method comprises the steps: obtaining three-dimensional cloud particle distribution data sets of a catalytic operation region before and after the catalytic operation through airborne cloud particle detection equipment, the three-dimensional cloud particle distribution data set comprises particle characteristic data before catalysis and particle characteristic data after catalysis; performing morphological feature extraction processing on the pre-catalysis particle feature data and the post-catalysis particle feature data by adopting a cloud particle AI image shape recognition algorithm to generate a pre-catalysis particle morphological difference feature set and a post-catalysis particle morphological difference feature set; constructing a dynamic physical response evaluation model, inputting the particle morphological difference feature set into the dynamic physical response evaluation model to execute multi-dimensional response correlation analysis, and generating a dynamic response feature set of the catalytic operation; and generating a catalytic strategy optimization instruction set according to the dynamic response feature set, and transmitting the catalytic strategy optimization instruction set to the airborne catalytic control system for catalytic parameter adjustment operation.

An assembly for an aircraft includes a wing assembly, a plurality of underwing heat exchangers, and a mounting assembly. The wing assembly includes a wing body. The plurality of underwing heat exchangers are arranged along the wing body in a longitudinal direction. The plurality of underwing heat exchangers includes a first underwing heat exchanger and a second underwing heat exchanger. The first underwing heat exchanger is longitudinally adjacent the second underwing heat exchanger. The mounting assembly includes a first heat exchanger bracket, a second heat exchanger bracket, and a first support bracket. The first heat exchanger bracket is fixedly mounted to the first underwing heat exchanger. The second heat exchanger bracket is fixedly mounted to the second underwing heat exchanger. The first heat exchanger bracket and the second heat exchanger bracket are pivotably mounted to the first support bracket. The first support bracket is fixedly mounted to the wing body.

The invention discloses an aircraft pose vision measurement method based on key points, and relates to the field of vision measurement, and the method comprises the steps: obtaining an aircraft image through machine vision; on the basis of the YOLO-v7 network, constructing an attention-enhanced target detection network; inputting the aircraft image into the attention-enhanced target detection network to obtain bounding box information; cutting the aircraft image by using the bounding box information to obtain an aircraft target image; constructing a key point extraction network; inputting the aircraft target image into the key point extraction network to obtain a key point coordinate; constructing a pose measurement network; and inputting the key point coordinates into the pose measurement network to obtain an aircraft pose measurement result. According to the invention, geometric modeling and end-to-end characteristics can be unified, the measurement precision is improved, and the ideal effect of balance between precision and robustness can be achieved.

The invention relates to the technical field of digital data processing, and discloses an aircraft safety data multi-source heterogeneous data acquisition method, which comprises the following steps of: synchronously controlling multiple types of sensors to concurrently execute physical obstacle three-dimensional investigation, micro-meteorological wind field construction and space electromagnetic spectrum surveying and mapping operation through a single unmanned aerial vehicle platform; and integrating the acquired three types of heterogeneous data into a three-dimensional spatio-temporal data base with a unified timestamp in real time. According to the method, endogenous space-time consistency of multi-source safety data at a collection source is ensured, information dislocation during traditional data fusion is avoided, a data base can truly reflect the instant coupling state of multiple risks, meanwhile, the exploration positioning capacity of the dynamic risks is arranged at a collection end in advance, and the data collection efficiency is improved. And an accurate and reliable decision basis is provided for flight safety assessment.

The invention provides an aircraft landing stage short-time abnormal risk early warning and visual simulation adaptive method based on deep learning, and the method comprises the following steps: synchronizing a multi-source sensor signal, separating the multi-source sensor signal into an impact channel, a wind shear channel and a residual channel, and mapping the multi-source sensor signal into aircraft-runway-wind field graph node features; features are extracted through a space-time diagram convolutional network, and a future trajectory is predicted in combination with a dual-channel attention decoder under physical constraints such as an energy attenuation template; high-risk actions are rapidly inhibited on the basis of real-time risks, the risk probability is calculated through weighted submerged space sampling, graded alarms are output, meanwhile, the alarms drive visual simulation to be adaptively updated, and model online safety iteration is achieved through hard sample mining after landing. According to the method, physical driving modeling, space-time fusion perception and probabilistic risk assessment are adopted, the dependence of a traditional method on an empirical threshold value is overcome, and the early warning precision, the confidence coefficient and the landing safety are remarkably improved.

The invention discloses a data-real fusion civil aircraft environment control system fault positioning test method, and belongs to the field of civil aircraft system fault digital positioning test, and the method comprises the steps: S1, real: carrying out fault positioning based on a physical test; s2, performing digital twinning-driven fault location deduction based on the physical test data obtained in the S1; s3, number-real fusion: based on the physical test result in S1 and the digital twinborn deduction result in S2, performing Bayesian-based fusion analysis and iterative optimization: calculating the deviation between the physical test and the digital twinborn simulation result; if the deviation exceeds a threshold value, optimizing parameters of the digital twinborn model by using a Bayesian method, adjusting a physical test scheme, and iteratively executing S1-S2 until the deviation meets the requirement; and outputting a final fused fault positioning result. According to the method, the precision of civil aircraft environment control system fault positioning is improved, and reliable technical support is provided for fault positioning and maintenance decision making.

The invention relates to the technical field of industrial visual inspection and intelligent assembly, solves the technical problem that the assembly task cannot be completed while the defect and quality of a blade are detected in the prior art, and particularly relates to an aircraft engine blade detection method, system and equipment. Carrying out multi-dimensional data acquisition to obtain leaf data; analyzing the key size, the surface damage and the coating integrity of the blade according to the collected blade data, and identifying the size error and the surface defect of the blade; and after the weighing equipment is calibrated, the static weight is read, and compensation calculation is carried out in combination with environmental factors, so that whether the quality of the blade is within a qualified range or not is judged. According to the method, multiple processes and multiple numerical parameters are comprehensively considered, full-process and multi-numerical-parameter engine blade detection is achieved, and assembly accuracy is guaranteed. And meanwhile, an efficient and reliable solution is provided for the aeronautical manufacturing industry, and the overall assembly quality and efficiency are remarkably improved.

The invention relates to the technical field of airport safety guarantee, and particularly discloses an airport bird situation monitoring and early warning bird repelling equipment linkage control method comprising the following steps: obtaining bird situation data vectors collected by sensors, calculating fused bird situation data vectors, and obtaining bird flock information; constructing a bird situation risk assessment model based on machine learning, combining the fused bird situation data with an aircraft take-off and landing plan, a runway use state and airport surrounding environment information to form an input feature vector, calculating a risk value through a risk assessment function, and dividing risk levels according to the risk value; according to a risk grade result of the risk assessment module, corresponding bird repelling equipment is controlled to work according to a hierarchical linkage bird repelling strategy; and in the bird repelling process, the risk level is re-evaluated according to the new bird situation data, the parameters of the bird repelling equipment are adjusted, and the bird repelling strategy is optimized by using a reinforcement learning algorithm. According to the invention, the defects of monitoring range and precision of a single sensor are effectively overcome, and the reliability of bird monitoring is greatly improved.

The invention is suitable for the technical field of unmanned aerial vehicles, and provides an unmanned aerial vehicle cruise detection method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the global path planning through employing an improved fast extension random tree algorithm; when a conflict risk is detected, a dynamic reward function is designed with returning to a global flight path after obstacle avoidance as a target, and a deep reinforcement learning model is adopted to realize control of actions of the unmanned aerial vehicle; and controlling the unmanned aerial vehicle to fly along the global aircraft path and the local obstacle avoidance path, and executing a target detection task based on the target detection model in the flight process until the task is completed and / or a target position is reached. According to the invention, global path planning is carried out by adopting the improved fast extended random tree algorithm, a local obstacle avoidance path is obtained in combination with the deep reinforcement learning model when facing an emergent obstacle, the autonomous cruising ability of the unmanned aerial vehicle is improved, real-time target detection is realized based on the target detection model in the flight process, and the task execution efficiency of the unmanned aerial vehicle is improved.

A computer-implemented method for simulating an aircraft system in a closed-loop functional simulation environment is disclosed. The computer-implemented method may include: receiving, at a computer system, one or more control inputs from an interface; processing, by a control system model, the one or more control inputs to generate one or more system command signals; applying the one or more system command signals to one or more virtual system models; simulating a physical response of the aircraft based on output generated by the one or more virtual system models in response to application of the one or more system command signals; generating, responsive to monitoring the output generated by the one or more virtual system models, sensor data; transmitting the sensor data to the control system model; and outputting simulation results, wherein the simulation results at least comprise an indication of the physical response of the aircraft.

The invention relates to the technical field of aircraft part processing, testing or inspection and the like, and provides an aircraft aluminum alloy plate aging evaluation method based on an equivalent circuit model, and the method comprises the following steps: collecting electrochemical impedance spectrums of samples with different exposure age limits, and extracting electrochemical impedance spectrum characteristics of the samples; establishing an equivalent circuit model comprising solution resistance, coating resistance, coating capacitance, Warburg impedance, anodic oxide film charge transfer resistance, interface capacitance, aluminum alloy matrix charge transfer resistance, interface electric double-layer capacitance, inductance and corresponding resistance of the inductance based on the characteristics, wherein the equivalent circuit model comprises the solution resistance, the coating resistance, the coating capacitance, the Warburg impedance, the anodic oxide film charge transfer resistance, the interface capacitance, the aluminum alloy matrix charge transfer resistance and the interface electric double-layer capacitance; and analyzing a resistance curve and a capacitance curve obtained by fitting the model to complete the evaluation of the corrosion and aging degree. According to the method, systematicness and accuracy of aging evaluation are improved, an electrochemical mechanism in the corrosion process can be disclosed, time correlation modeling of the aging process can be achieved, and the method is suitable for long-term service performance monitoring and service life prediction of the aviation aluminum alloy structure.