702 results about "Flight time" patented technology

The invention relates to a low-altitude logistics unmanned aerial vehicle path planning method, which comprises the following steps of 1, discretizing an urban low-altitude region into computable grid units, a dynamic-static obstacle classification modeling technology is combined to endow a static obstacle with a basic risk degree, a height attenuation factor is introduced to quantify the influence of a high-altitude obstacle on a low-altitude path, and a collision risk of a dynamic obstacle is dynamically evaluated through a time dimension risk degree prediction model; 2, based on an improved genetic algorithm, comprehensively considering flight time, height change, risk degree and dynamic risk cost through a multi-objective optimization objective function, and generating a globally optimal task allocation scheme; 3, generating a local optimal three-dimensional path considering meteorological conditions and dynamic obstacle influence by adopting an improved particle swarm algorithm; and 4, performing path planning to feed back actual flight time and energy consumption to task allocation for optimization.

The invention relates to the technical field of unmanned aerial vehicles, and discloses a gas-electric hybrid composite wing unmanned aerial vehicle system, which comprises an intelligent energy management module, a gas-electric hybrid composite wing unmanned aerial vehicle control module and a gas-electric hybrid composite wing unmanned aerial vehicle control module, the self-adaptive flight control module is used for optimizing the flight attitude, dynamically adjusting the flight route and improving the flight safety; the task adaptive scheduling module is used for adaptively adjusting a task execution strategy according to the task category, the load condition and the environmental parameters; the data monitoring and remote control module is used for collecting the operation state of the unmanned aerial vehicle in real time and storing and analyzing flight data; the intelligent safety management module is used for improving the autonomous safety of the unmanned aerial vehicle; and the environment perception optimization module is used for perceiving external environment factors in real time. According to the invention, the intelligent energy management module realizes intelligent scheduling of fuel and electricity power, and dynamically optimizes the power distribution of the battery and fuel oil, so that the flight time of the unmanned aerial vehicle is greatly prolonged.

The invention discloses a civil aircraft PHM modeling method based on cross-modal coupling, a medium and equipment, and belongs to the technical field of aircrafts. The method comprises the steps of S1, multi-modal data preprocessing: performing feature extraction and time-space / event alignment for three modalities of flight time sequence data, text data and image data, and laying a foundation for subsequent fusion modeling; s2, cross-modal feature fusion and holographic data sample construction: constructing a holographic data sample library covering the whole life cycle through cross-domain fusion and dynamic optimization; and S3, PHM physical-knowledge fusion comprehensive modeling: constructing a double-layer collaborative framework combining physical simulation and knowledge reasoning, and realizing controllable fusion of physical simulation and multi-modal knowledge. The problems that in the prior art, multi-source heterogeneous data alignment is difficult, physical mechanism and data driving fusion is insufficient, and model interpretability is poor can be solved.

The invention discloses an unmanned aerial vehicle real-time vegetation classification system and method based on a lightweight AI model, and belongs to the technical field of vegetation monitoring and analysis. On the basis of an existing processor of the unmanned aerial vehicle, vegetation real-time classification is achieved by optimizing the deep learning model, and the flight path is dynamically adjusted according to the classification result. The method comprises the steps of system configuration and initialization, lightweight AI model development and optimization, real-time data acquisition and processing, adaptive flight path adjustment and feedback optimization. The method has the following advantages: (1) real-time classification of vegetation and adaptive flight path adjustment are realized, and the acquisition efficiency is optimized; (2) the sampling density is adaptively adjusted for different value regions, and the precision and coverage efficiency of vegetation classification are improved; (3) the acquisition strategy is optimized in real time in combination with the battery state, and unnecessary flight time and energy consumption are reduced; and (4) the method is suitable for application fields such as agricultural monitoring, forestry management and ecological protection.

The invention discloses a method and a system for processing route planning data for electric power line inspection. The method comprises the following steps: acquiring line distribution and topographic feature data; gridding the power network region, determining the patrol priority, and generating a region priority sequence; the overall patrol task is decomposed, a plurality of task subsets are generated, one task is allocated to each unmanned aerial vehicle, and each task subset comprises an initial position and a target line section; generating an initial route path based on the topographic features; comprehensively analyzing all initial paths, identifying potential airspace intersections and performing conflict prediction, and generating a conflict-free route path set by performing height hierarchical adjustment on related paths; and calculating predicted flight time and energy consumption of each unmanned aerial vehicle, redistributing boundary tasks according to a load balancing principle, and finally generating a balanced multi-unmanned aerial vehicle cooperative route scheme. According to the method, the safe and efficient multi-machine collaborative inspection route can be automatically generated through systematic task decomposition, conflict prediction and load balancing optimization.

An autonomous flying device achieving a large payload and a long continuous flight time and also accurately adjust position and orientation while flying. The device includes: a main rotor and the like that provide main thrust; a sub rotor and the like that controls the orientation; an engine that generates energy for rotating the main rotor and the like and the sub rotor and the like; and an arithmetic control device that controls rotation of the sub rotor and the like. Also, the main rotor and the like are rotated by being drivingly connected to the engine, whereas the sub rotor and the like are rotated by motors driven by electric power generated from generator and the like operated by the engine. Further, when orientation control to tilt the fuselage is performed, the arithmetic control device increases the output distribution ratio of the sub rotor to above the output distribution ratio of the sub rotor when hovering is performed.

The invention belongs to the technical field of air traffic management, and relates to a flight time adjustment management method and system in a special scene. According to the method, the flight release priority sequence is constructed, the airport taxiway network topology and the dynamic limitation information are combined, the taxiing path is planned, the space-time conflict is detected, and the dynamic adjustment of flight ground operation and the coordination verification of the runway access time window are realized. The problems of frequent flight ground taxiing path conflicts, low scheduling efficiency and difficulty in accurate take-off time control in special scenes are solved, the safety and efficiency of airport ground operation are effectively improved, the flight taxiing time and the runway waiting time are reduced, the flight release sorting and the runway use plan are optimized, and the flight taxiing efficiency is improved. The flight scheduling cooperation capability in a complex operation environment is enhanced, and the orderliness and stability of flight operation are guaranteed.

The invention relates to the technical field of unmanned aerial vehicle cluster control, in particular to an unmanned aerial vehicle cluster control method and system, and the method comprises the steps: predicting the remaining flight time of an unmanned aerial vehicle cluster for safely arriving at a destination in a current carrying state; calculating a cluster energy consumption deviation degree according to the current energy consumption parameter, predicting the remaining endurance time of each unmanned aerial vehicle, and determining the minimum predicted endurance time; dynamically generating a safe flight time threshold according to the minimum predicted endurance time and a preset safety margin; if the remaining flight time is smaller than the safe flight time threshold value, a cooperative control instruction is generated according to the offset, the offset speed and the cluster energy consumption deviation degree; and distributing the cooperative control instruction to the corresponding unmanned aerial vehicle in the unmanned aerial vehicle cluster. And the flight endurance crisis caused by non-uniform energy consumption in the irregular article carrying process is effectively solved.

The invention provides an anomaly detection method of an ultrasonic gas meter and the ultrasonic gas meter, and relates to the technical field of flow monitoring. The invention provides a more accurate and timely anomaly detection method aiming at the problem that an existing detection method for judging whether an instrument is abnormal or not only by judging flight time of an ultrasonic gas meter is not timely and accurate enough in anomaly response. The method comprises the following steps: exciting a first transducer according to a preset frequency to enable the first transducer to emit an ultrasonic signal; the second transducer receives the ultrasonic signal transmitted by the first transducer and generates an echo signal waveform; and waveform features are extracted from the echo signal waveforms, and if the waveform features do not conform to a preset rule, it is judged that detection of the ultrasonic gas meter is abnormal. In addition, according to different identification results, different processing modes are adopted, the anti-interference capability of the instrument is improved, and the abnormal detection of the instrument is more accurate.

The invention provides an unmanned aerial vehicle flight path dynamic planning method and system, and relates to the technical field of flight path planning, and the method comprises the steps: obtaining the starting and ending points of the flight of an unmanned aerial vehicle, and planning an initial unmanned aerial vehicle flight path based on the starting and ending points of the flight of the unmanned aerial vehicle and a preset constraint; constructing an unmanned aerial vehicle flight environment model based on a preset flight area map, the elevation information and the obstacle information; route optimization is carried out based on the initial unmanned aerial vehicle flight route and a flight environment model, and an unmanned aerial vehicle initial obstacle avoidance route is generated; the unmanned aerial vehicle initial obstacle avoidance route is optimized based on a preset iterative optimization model, and an optimized unmanned aerial vehicle obstacle avoidance route is obtained; and updating the optimized unmanned aerial vehicle obstacle avoidance route to the initial unmanned aerial vehicle flight route to generate a final unmanned aerial vehicle flight route. According to the invention, the flight time and cost are saved, the adaptability to the environment, especially the urban complex environment, is enhanced, and the safety is guaranteed.

The invention discloses an unmanned aerial vehicle automatic homeward voyage method based on a global topological map and a graph search algorithm, which comprises a global passable area topological connected graph module, a homeward voyage path search module, a homeward voyage path optimization module and a homeward voyage path error processing module. According to the method, global path searching is carried out in combination with a Dijkstra algorithm, path smoothness, flight time and obstacle avoidance are optimized by using a B spline curve, the precision and speed of path planning are effectively improved, and meanwhile, the system can cope with changes in the environment by updating a topological connected graph and optimizing the path in real time, so that the path planning efficiency is improved. And secondly, the path safety and the flight stability are both considered, and an obstacle distance penalty term is introduced, so that the flight path can avoid the obstacle, and the collision risk is reduced.

The invention relates to a multi-unmanned aerial vehicle maritime cooperative reconnaissance method based on an Archimedes algorithm and hierarchical scheduling, and the method comprises the steps: defining a patrol task region and task targets, and constructing a topological model of an unmanned aerial vehicle cluster for each task target; according to the cooperation characteristic of the unmanned aerial vehicle cluster, Archimedes patrol path planning is carried out on various unmanned aerial vehicles; based on the performance of the unmanned aerial vehicle, factors such as path length, flight time, unmanned aerial vehicle scanning range and search efficiency are comprehensively considered, and the path of the unmanned aerial vehicle is optimized, so that the unmanned aerial vehicle has relatively high execution efficiency and stability; when the leader unmanned aerial vehicle finds a target during patrol, the cluster dispatches the investigation unmanned aerial vehicle to perform a tracking task; and the investigation data is returned to the command center, and next task planning is carried out. The cooperative reconnaissance capability of the unmanned aerial vehicle cluster in complex tasks can be effectively improved.

A modular unmanned aerial vehicle (UAV) system comprises a body module, a rotor module, and a wing module. The body module includes a flight controller and a power distribution device. The body module is releasably attachable to the rotor module or the wing module, and the body module is releasably attachable to the rotor module. The rotor module includes one or more motors and electronic speed controllers (ESCs), while the wing module includes a wing having a flap, elevator, aileron, or rudder. Various UAV configurations can be formed from the body module, the rotor module, and the wing module. Each configuration includes different advantages for flight time, distance, battery life, and payload capacity. A UAV can be configured to a particular configuration to optimize parcel delivery.

The invention discloses a power line anomaly detection method and system based on an unmanned aerial vehicle. The method comprises the steps that a server analyzes a power line detection request to obtain a detection area and a detection time period; planning an initial detection track, generating a power line detection instruction based on the initial detection track, the detection area and the detection time period, and issuing the instruction to the unmanned aerial vehicle; the unmanned aerial vehicle executes an inspection task in the electronic fence, the initial detection track is dynamically corrected in the inspection process, and a flight time sequence image is collected; analyzing the flight time sequence image through a line anomaly detection model, and outputting a line anomaly detection result; an actual detection track is recorded, and abnormity marking is carried out on the actual detection track; and recording, encrypting and uploading an inspection log to the server. The method has the advantages that the detection efficiency, the intelligent level and the safety management capability of power line anomaly detection are greatly improved.

The embodiment of the invention provides a transducer echo line sequence test method and a transducer echo line sequence test device, and the method comprises the steps: enabling a detection surface and a horizontal plane to form a first angle in an echo detection state, comparing waveform data of feedback signals obtained by reflecting the ultrasonic signals emitted by the plurality of test array elements through the detection surface with preset qualified data to determine a performance result of the transducer; in the line sequence detection state, a second angle is formed between the detection surface and the horizontal plane, and the actual flight time difference value of each adjacent test array element in the plurality of test array elements is determined according to waveform data of feedback signals obtained by reflecting ultrasonic signals emitted by the plurality of test array elements through the detection surface, and according to a comparison relation between a difference value between the actual flight time difference value and the theoretical flight time difference value and a preset threshold value, whether welding of each test array element is correct or not is determined. Therefore, an echo performance detection function and a multi-array element line sequence detection function can be integrated.

The invention belongs to the technical field of radar detection, and discloses a bird positioning method of a quantum radar bird detection system, which is characterized in that quantum characteristics such as polarization state and phase of echo photons are accurately analyzed by means of a quantum state demodulation technology, and high-precision measurement of the flight time of the photons is combined, so that the resolution limitation of the traditional radar is broken through from the quantum level; the technical combination not only can capture fine actions such as wing flapping frequency and steering angle of birds, but also can exert remarkable advantages in a dense bird flock scene: by utilizing quantum state differences of echo photons of different birds, overlapping signals are decomposed into independent individual signals through a quantum state separation algorithm; the individual distinguishing problem caused by traditional radar signal aliasing is solved; in high-precision demand scenes such as airports and the like, small bird targets can be accurately locked, flight potential safety hazards caused by misjudgment are greatly reduced, and the system can physically resist copying and deception interference of the outside to quantum signals based on the quantum unclonable principle.

The invention discloses a heterogeneous unmanned aerial vehicle cluster task allocation and region boundary point joint planning method. The method comprises the following steps: constructing an unmanned aerial vehicle motion model; constructing a collaborative detection distribution income measurement index, an estimated detection time difference measurement index and an energy consumption measurement index which take unmanned aerial vehicle task node selection parameters as optimization variables, and taking the weighted sum of the three indexes as a measurement index of collaborative detection task efficiency; establishing a heterogeneous unmanned aerial vehicle cluster task allocation and region boundary point joint planning model by taking given unmanned aerial vehicle voyage, endurance, effective communication distance and inter-vehicle anti-collision distance limitation as constraint conditions and taking minimization of a heterogeneous unmanned aerial vehicle cluster cooperative detection task efficiency cost function as an optimization target; and solving the optimization model by combining an interior point and an improved Hungary algorithm. According to the method, optimal distribution of the heterogeneous unmanned aerial vehicle cluster task area, the base takeoff point and the area boundary entry point is realized, and the heterogeneous unmanned aerial vehicle cluster cooperative detection performance is effectively improved.

The invention relates to the technical field of ultrasonic flow measurement, and discloses a relative flight time estimation method based on an ultrasonic flowmeter, and the method comprises the steps: carrying out the time domain alignment of uplink and downlink echo signals through prior absolute flight time, and preventing phase cycle skipping; carrying out FFT (Fast Fourier Transform) and frequency domain conjugate multiplication on the signal, and extracting amplitude and phase information; and a cost function is constructed by using frequency spectrum amplitude weighting, residual delay is estimated through least square fitting, and finally high-precision relative flight time is obtained. According to the method, correlation operation is realized in the frequency domain, the calculation complexity is remarkably reduced, the estimation precision and the anti-noise capability are improved, and the method is suitable for an embedded low-power-consumption system.

An autonomous flying device achieving a large payload and a long continuous flight time and also accurately adjust position and orientation while flying. The device includes: a main rotor and the like that provide main thrust; a sub rotor and the like that controls the orientation; an engine that generates energy for rotating the main rotor and the like and the sub rotor and the like; and an arithmetic control device that controls rotation of the sub rotor and the like. Also, the main rotor and the like are rotated by being drivingly connected to the engine, whereas the sub rotor and the like are rotated by motors driven by electric power generated from generator and the like operated by the engine. Further, when orientation control to tilt the fuselage is performed, the arithmetic control device increases the output distribution ratio of the sub rotor to above the output distribution ratio of the sub rotor when hovering is performed.

The invention discloses an airship type unmanned aerial vehicle inspection system and inspection method, and belongs to the field of inspection unmanned aerial vehicles. The system comprises a laser radar, an image acquisition device, an airship capsule filled with helium, a standby safety airbag, a communication module and a ground control center, in the method, the ground control center sets an inspection path and issues the inspection path, and the unmanned aerial vehicle flies according to a preset path. During fault detection, the high-definition camera collects images to recognize line cracks and broken strands, the thermal infrared imager monitors the joint temperature, the gas sensor detects abnormal gas, and multi-source data fusion assists in defect positioning. The routing inspection takes a starting point-terminal point connecting line of a power transmission line as a reference, identifies main obstacles and surrounding nodes to perform global planning, performs key routing inspection on a risk area in combination with historical data, and initializes and guides a flight direction through a Q value to reduce invalid exploration. The four-rotor unmanned aerial vehicle solves the problems of short flight time and poor stability of a four-rotor unmanned aerial vehicle, improves the inspection stability and cruising ability, and improves the inspection efficiency of a power transmission line and the reliability of a power system.

The invention relates to a multi-domain collaborative ocean emergency rescue method, which solves the technical problems of short endurance, small operation range and low recognition accuracy of persons in distress when an unmanned aerial vehicle or an unmanned ship or an underwater robot is adopted to carry out a search and rescue task in the prior art, and combines the unmanned aerial vehicle, the unmanned ship and the underwater robot for mutual cooperation. The unmanned aerial vehicle carries out investigation traversal in the air to find a search and rescue target, the unmanned aerial vehicle gets close to the search and rescue target and sends the position information of the target to the control center, the unmanned ship sails to the position of the target, the at least two underwater robots are transferred along with the unmanned ship, and the unmanned ship controls the at least two underwater robots to work cooperatively. The method can be widely applied to deep ocean emergency rescue, and an'air-sea-submerged 'multi-domain cooperative new normal form is formed.

The invention discloses a laser radar ranging system based on direct flight time, and the system comprises a laser transmitting module which is used for transmitting a laser pulse signal; the laser receiving module is used for receiving echoes reflected by the target; the data processing module is connected with the output end of the laser receiving module and is used for processing the laser pulse signal and calculating a time difference according to the laser pulse signal; the time sequence control module is connected with the laser emission module and is used for recording a first timestamp of laser pulse signal emission; the recording module is connected with the laser receiving module and is used for starting the laser receiving module and recording a second timestamp for receiving echoes when the first timestamp is recorded; the time calibration module is connected with the data processing module and is used for providing a time calibration signal for the data processing module; and the distance measuring module is used for measuring and calculating the distance according to the time difference. According to the invention, the laser radar ranging of the target can be realized by using the direct time-of-flight method.

The invention discloses a communication and inductance integration method for a communication waveform in a high mobile environment. The method comprises the following steps: constructing a UAV-ISAC system based on AFDM; constructing a model of a communication signal sent by the UAV to the base station and a model of an echo signal received by the UAV and perceived by a ground user; determining the signal-to-noise ratio of each time slot communication part link and the signal-to-noise ratio of a sensing part echo based on a communication signal model and an echo signal model, thereby determining the capacity of each time slot communication link and the sensing mutual information amount of each user, and determining the total sensing mutual information amount, the total communication capacity of the UAV in the whole flight time, and the total consumed energy; constructing a total optimization problem by using the total communication capacity and the total consumed energy, and decomposing the optimization problem into three sub-problems of user scheduling optimization, transmitting power optimization and UAV trajectory optimization; and by constructing different constraint conditions and solving the three sub-problems, an optimization result is obtained. According to the invention, the energy efficiency of the UAV-ISAC system based on AFDM can be maximized.

In a method of determining position information of a client device, reference devices include a master device and target devices. Target device clocks are synchronized with the master device clock based on one-way message information. For each of the target devices a first time correction is determined based on a two-way ranging message. A first message transmitted from / to the respective target device is timestamped by several target devices corrected for the first time correction. Position information of the client device is determined based on time-of-flight information of the first messages in which the first timestamp is corrected for the first time correction. As a result, the timestamps of the first messages applied by the target devices will experience a same offset error. Consequently, the corresponding pseudo-ranges will all have the same error. Typically, positioning algorithms are insensitive to constant errors in the pseudo-ranges or can easily deal with them.

A single-pass method for identifying peaks in a time of flight histogram, the single-pass method including conducting an ordered comparison of each bin with an adaptive threshold until finding a bin that exceeds the adaptive threshold; enabling peak tracking in response to finding the bin that exceeds the adaptive threshold; in response to enabling peak tracking, continuing the ordered comparison of each bin with the adaptive threshold until finding a bin that falls below the adaptive threshold; and in response to finding the bin that falls below the adaptive threshold, marking a peak location between the bin exceeding the adaptive threshold and the bin that falls below the adaptive threshold.

The invention discloses a terminal course angle and time constraint iterative reentry guidance method, and belongs to the technical field of hypersonic flight vehicle gliding section trajectory planing.The method comprises the steps that firstly, a resistance acceleration profile is planned according to a reentry corridor, and the size of a heeling angle is obtained; a heeling angle symbol is obtained through a heeling reversal strategy based on an SA-SQP optimization method; and finally, on-line correction is carried out on the basis of the standard attack angle profile, the interference error of longitudinal and lateral guidance is weakened, the guidance precision is improved, and a three-dimensional trajectory considering time and terminal course angle constraints is finally obtained. According to the method, the three core modules of two-parameter resistance acceleration profile design, heeling inversion search based on the SA-SQP optimization method and attack angle profile online correction are combined, the coupling interference error between longitudinal guidance and lateral guidance is weakened, and therefore high-precision reentry guidance under multiple constraints is achieved. According to the method, the reentry guidance precision can be effectively improved, the task adaptability is high, and flight time and terminal course angle constraints can be strictly met.

A time of flight (TOF) ranging system includes multiple emitters, each emitting a signal whose intensity, amplitude or polarization is modulated by a corresponding delayed modulation signal. Each delayed modulation signal is a delayed version of a time varying multi-valued modulation signal, the amount of delay being determined by a spatial position of the emitter and direction of a target point on the target. The signal reflected by the target is correlated with the original modulation signal to generate an output having a peak representing the TOF to the target point. The same process is performed to detect other target points. Another TOF ranging system includes one emitter and multiple detectors; the signal from each detector is delayed in a similar manner and their sum is correlated with the original modulation signal to generate an output representing TOF. Yet another TOF ranging system includes multiple emitters and multiple detectors.

The invention discloses an AI-based unmanned aerial vehicle automatic positioning and navigation system, and the system comprises an unmanned aerial vehicle body which obtains a starting point coordinate through a navigation module by manually inputting a terminal point coordinate and a planned flight time length value t, flies to the terminal point coordinate at a flight speed value V1 and a flight height value H1 from the starting point coordinate, automatically completes a flight task, and automatically judges a return flight; and the monitoring unit is used for acquiring an initial electric quantity value Q of the unmanned aerial vehicle body, transmitting the initial electric quantity value to the coordinate unit, monitoring the output power of the storage battery in real time during flight, and generating a feedback signal and transmitting the feedback signal to the correction unit when abnormal output power is generated during flight. The problems that when an existing unmanned aerial vehicle automatic positioning navigation system is used, the endurance problem of the unmanned aerial vehicle is not considered, and the unmanned aerial vehicle cannot return or even falls in the flight process in the actual flight process are solved.

The invention relates to the technical field of urban low-altitude flight control, in particular to a low-altitude aircraft path planning and dynamic adjustment method for urban low-altitude logistics. Constructing a dynamic evaluation model of the flight risk factor R based on the urban three-dimensional environmental parameters; planning the path of the aircraft by adopting a multi-objective optimization algorithm, and determining an optimal path; dynamically adjusting paths by using an environment prediction model and a reinforcement learning algorithm: constructing a conflict graph between paths of each aircraft, and constructing a path collaborative optimization model according to path cost, energy consumption, flight time, path conflict and formation collaborative income; and outputting an optimized path set through the path collaborative optimization model, and generating a formal deployment scheme of multi-aircraft path collaborative scheduling. Compared with an existing static optimization and single path scheduling method, the method has the advantages that the path planning precision, the dynamic response capability, the multi-aircraft cooperation efficiency and the complex airspace adaptability are remarkably improved.

The invention relates to the technical field of aviation data, in particular to an airport transit level measurement method and system.The built transit service index system covers the flight time transit connection level, passenger transit waiting and transit air flight; influences of airport operation, passenger service and flight operation on the transfer service are comprehensively considered, and multi-source description of the airport transfer service level is effectively realized. According to the airport transfer level fusion method fusing the multi-flight transfer service, measurement of flight transfer service priorities is achieved based on flight operation characteristics such as airline company attributes, peak periods and the number of transfer passengers, and the comprehensive service level of a plurality of transfer connectable flight pairs is effectively fused.