15 results about "Flight (process)" patented technology

The invention discloses an aircraft performance monitoring method, device, terminal and system and a storage medium, and the method comprises the steps: obtaining a preprocessed flight data stream from an airborne flight data preprocessing device in the flight process of a target leg, analyzing and processing the flight data meeting the effective leg screening condition in the preprocessed flight data stream to obtain the flight data of the effective leg; based on the flight data of the effective leg, calling an embedded performance factor analysis logic to carry out performance factor analysis so as to obtain a performance factor of the effective leg; and in response to a flight end instruction of the target leg, displaying a performance monitoring result on a display based on the performance factor of each effective leg. According to the invention, while the timeliness of airplane performance monitoring is improved, the interference on airborne system data is avoided, the safety is ensured, and an airplane crew can master the performance condition of an airplane in time.

The application provides an aerodynamic parameter identification method based on an improved physical information neural network, comprising: obtaining a target flight state quantity in a flight process of an aircraft; inputting the target flight state quantity into the improved physical information neural network to obtain an aerodynamic parameter perturbation quantity, the aerodynamic parameter perturbation quantity being a difference quantitative value between a nominal aerodynamic parameter and an actual aerodynamic parameter in flight, a loss function of the improved physical information neural network being an integral loss function, the integral loss function establishing a connection between a dynamic model containing an estimated value and a real dynamic characteristic; and determining the actual aerodynamic parameter according to the aerodynamic parameter perturbation quantity and the corresponding nominal aerodynamic parameter. Through implementation of the application, the dynamic model containing the estimated value is connected with the real dynamic characteristic in an integral manner, correct dynamic information is ensured to be learned by the neural network in a training process, the accuracy of the aerodynamic parameter is improved, and the training difficulty is reduced.

According to the high-rotation transient turbulent flow actuating mechanism control device and the simulated flight test method provided by the invention, the aerodynamic configuration of a flight body and the air flow field around the flight body are changed by accurately controlling the extension and retraction of the spoiler, so that the aerodynamic force and the aerodynamic moment suffered by the flight body are controlled, and the control effect is realized; that is, the spoiler actuating mechanism drives the spoiler to stretch out and retract through the high-frequency response motor so as to realize continuous, repeated and high-frequency super-agile continuous control, and the high-overload resistance of the actuating mechanism is ensured through the high-overload resistance design and the potting process of a mechanical structure; in addition, a simulated flight test device is also established, and the actuation performance of the turbulent flow actuation mechanism is tested in the simulated flight process. According to the invention, continuous, repeated and high-frequency continuous control can be carried out while high overload can be borne, and a control / actuation mechanism implementation way is provided for realizing guided transformation of a high-rotation flight system.

The invention discloses a flight program verification method based on an integrated navigation system, and relates to the technical field of navigation, and the method comprises the steps: simulating a first flight path of an airplane in a preset scene in a simulation system based on a flight program, and setting a plurality of obstacles in the preset scene; the simulation error is injected into a simulation system, corresponding target positions, target postures and target speeds of the aircraft at different moments are calculated through loose integrated navigation, and the target positions, the target postures and the target speeds are fused into a second flight path; calculating a first number of triggered obstacle alarms and a second number of triggered obstacle alarms in a first flight path during operation of the aircraft; and calculating a first average number and a second average number, dividing the second average number by the first average number to obtain a threshold score, and determining that the flight program is qualified when the threshold score is greater than or equal to the target threshold. By means of the technical scheme, the accuracy of verifying the flight program can be improved, and then the safety of the aircraft in the flight process can be improved.

The application discloses a kind of pilot health index real-time monitoring device, belong to monitoring technical field, including: shell, mounting block, rotating mouth, camera, rotating drive mechanism, central processing unit, alarm;The device of the application is installed in the adaptive position of aircraft, will not increase any burden in the flight process of pilot, at the same time, also will not cause the occlusion of the line of sight in the flight process of pilot, improve the use safety of device.

The invention discloses a space situation enhancement method and system based on a cortex fusion technology, and relates to the field of aerospace flight attitude perception. In order to solve the problems that an existing space situation perception intervention means cannot take effect in real time, a large number of cognitive resources are occupied and the like, a head tactile stimulation array is adopted in the scheme, flight attitude information is mapped into graded vibration feedback through a cortex tactile fusion technology, and low-delay transmission is achieved through a trigeminal neural pathway. The system comprises a vibration patch helmet, a closed-loop control module and a data transmission unit, stimulation points cover six areas such as the forehead and the top of the head, and single-point and combined vibration prompting is supported. According to the method, secondary cognitive processing of a pilot is not needed, airsickness and flight illusion risks are remarkably reduced, occupation of cognitive resources is minimized, real-time enhancement of space situation awareness in the flight process is achieved, and the method is suitable for flight auxiliary scenes of various aircrafts.

The invention discloses an alarm threshold determination method and a related device, and the method comprises the steps: firstly obtaining historical flight data which is used for identifying the state of flight equipment in a historical flight process, and then obtaining a historical alarm threshold through a rule algorithm based on the historical flight data, wherein the rule algorithm is constructed based on the influence weight of the environment data and the flight parameters on the safe flight state of the flight equipment, the influence weight is determined based on artificial experience, and then a corresponding dynamically changing historical alarm threshold can be obtained based on historical flight data obtained in a real scene according to the rule algorithm. And finally, training the machine learning model according to the historical flight data and the historical alarm threshold to obtain a threshold calculation model, so that the threshold calculation model can be applied to a subsequent real flight process to obtain an alarm threshold which adaptively changes according to a real scene, and dynamic adjustment of the alarm threshold is realized. Therefore, the alarm accuracy is effectively improved.

The invention provides a power battery temperature prediction method and device based on eVTOL typical flight characteristics, and belongs to the technical field of aviation engineering such as an aircraft technology, a power technology, an avionics technology and an electromechanical system technology. The method comprises the following steps: collecting time sequence data of current and temperature in real time after the eVTOL takes off, calculating a time-current curve curvature through a high-precision non-equidistant five-point curvature method, and determining a flight state conversion time point; according to typical characteristics of different flight states, fitting a temperature-time change relationship between the take-off stage and the initial stage of the cruise stage through partial data of the take-off stage and the cruise stage; and predicting the temperature change of the remaining voyage in the flight process by using the obtained fitting parameters in combination with the remaining cruise duration and the landing duration. The method has the characteristics of simplicity, high efficiency and high practicability, can predict the temperature change in the later flight period in the initial flight period, provides effective data support for eVTOL power battery thermal management, and lays a foundation for safe flight.

The application relates to a flight data abnormality detection method and system based on a dual-view enhanced Transformer, and belongs to the technical field of aviation safety. The application extends the flight safety abnormality detection task to beyond the traditional overrun event, and aims at the subtle and often undetected abnormality in the flight process. According to the fact that QAR data is a typical form of time series data, the flight safety problem is re-expressed as an abnormality detection task in time series analysis. In addition, in order to solve the challenge of excessive dependence on expert labeled data in flight safety research, an unsupervised abnormality detection model specially designed for QAR data is designed. Finally, according to the sparse characteristics of QAR data, a time series abnormality detection model architecture based on reconstruction is designed. The application can timely identify the condition deviating from the normal flight mode, provide early warning information for airlines, and effectively assist experts in analyzing abnormal flight behavior, and has a wide application prospect.

The utility model discloses a fire-fighting pod and an aircraft, which belong to the technical field of aircrafts, the fire-fighting pod comprises a pod body and a connecting rod, the connecting rod is provided with a first connecting device used for connecting the top of the pod body and a second connecting device used for connecting an arm connector of the aircraft, the first connecting device is located in the middle of the connecting rod, and the second connecting device is located in the middle of the connecting rod. The second connecting device is located at the end of the connecting rod, in the flight process of the aircraft, the cabin body is hung below the aircraft fuselage through the connecting rod, the connecting rod bears force transmitted by the aircraft fuselage and the cabin body and deforms, the connecting rod provides buffering and damping for the cabin body, and the service life of the cabin body and all parts on the cabin body is prolonged.

The application discloses a kind of based on data-driven flight risk assessment method, the method collects the multidimensional flight state parameters in the process of aircraft flight, input flight state depth clustering network obtains the flight state data set of different clustering categories;The entropy weight value and the closeness to ideal solution of each clustering category are calculated using entropy weight approximation ideal solution sequencing algorithm;Based on aviation collision risk model, construct flight risk assessment initial model framework in combination with entropy weight value and closeness;The clustering result and related numerical value are substituted into initial model framework to train and optimize;Real-time flight state parameters are processed using the optimized model, and the risk assessment result of the current flight phase is output.The method classifies flight state by refinement, scientifically determines parameter weight and fuses multiple technologies, improves the evaluation accuracy and reliability, and can effectively guarantee the flight safety of aircraft.

The invention discloses an aircraft testing system, method and device, the system comprises a man-machine interaction device and an anti-skid control box testing device of a target aircraft, the anti-skid control box testing device comprises a virtual model of a brake system of the target aircraft, and the anti-skid control box testing device is in communication connection with the man-machine interaction device; the man-machine interaction device is used for acquiring a user operation instruction and sending the user operation instruction to the anti-skid control box testing device; the anti-skid control box testing device is used for determining a virtual control instruction of the target aircraft based on the user operation instruction and a virtual model; executing the virtual control instruction to obtain an operation feedback result; an operation feedback result is sent to the man-machine interaction device; and the man-machine interaction device is also used for outputting the operation feedback result. Therefore, a real environment in the flight process can be provided for a user, and the performance of the anti-skid control box of the target aircraft can be tested, so that the accuracy of the test result of the anti-skid control box is improved.

The application discloses a landing guidance method suitable for thrust response large lag, which utilizes a polynomial guidance to calculate a reference trajectory, considers engine response characteristics in the calculation process of the polynomial guidance method, solves the technical problem caused by the engine command thrust response large lag in the flight process, and enables the aircraft to complete the flight task according to the trajectory planned by the polynomial guidance. The application obtains the relationship between the command acceleration and the response acceleration through the engine characteristics, compensates the delay characteristics into the acceleration command by using the reference trajectory of the polynomial, obtains the polynomial landing guidance method considering the thrust response large lag, and can guarantee that the output command is the target acceleration calculated by the polynomial, and accurately realizes the target speed position control of landing.

This invention relates to the field of energy regulation and management technology, specifically disclosing a UAV power efficiency regulation and management system and method based on real-time operating condition identification. This invention acquires UAV flight status perception data in real time through airborne sensors, performs preprocessing to obtain flight status perception features, constructs a flight deviation analysis model to obtain flight deviation features, sorts the flight deviation features in chronological order based on a time-series model to obtain a flight deviation time series, builds a UAV control accuracy evaluation strategy based on the flight deviation time series, evaluates the control accuracy of the UAV during flight, establishes a power demand mapping relationship, filters sensitive flight states based on the power demand mapping relationship, extracts flight deviation features of sensitive flight states, and determines the sensitizing factors based on the flight deviation features. This invention can achieve differentiated energy efficiency regulation of the UAV flight process, improving the UAV's adaptability and robustness.

The invention relates to the technical field of low-altitude aircrafts, and discloses a low-altitude aircraft path planning optimization method and system based on big data analysis, and the method comprises the steps: carrying out the preprocessing of original data, and generating standardized low-altitude data; inputting the standardized low-altitude data into a CNN-LSTM-DDPG model, extracting environment features through a CNN network, capturing an environment dynamic change trend in combination with an LSTM network, and outputting a path adjustment action based on a DDPG algorithm; generating an initial path based on the path adjustment action, and introducing a multi-target dynamic optimization cost function to evaluate and screen the initial path to obtain an optimal path; issuing the optimal path to a physical low-altitude aircraft for execution, collecting flight process data, monitoring the deviation between the flight process data and the optimal path in real time, and when the deviation exceeds a preset threshold value, generating a correction instruction and issuing the correction instruction to the low-altitude aircraft; the method improves the precision of path planning, greatly reduces the flight risk, and guarantees the efficient and safe completion of a task.