54 results about "Flight velocity" patented technology

The invention relates to the technical field of fan blades, in particular to an automatic fan blade coating spraying method and system based on an unmanned aerial vehicle. Comprising the steps that a plurality of blade subareas are set according to the surface structure of the fan blade; according to a preset wear simulation model, an expected wear value of each blade sub-region is generated, and whether a primary spraying strategy is generated or not is judged according to the expected wear values; acquiring a spraying monitoring packet according to a preset feedback time node, and judging whether to correct the primary spraying strategy according to the spraying monitoring packet; the wear degree of each area of the fan blade is remotely predicted according to the wear simulation model in combination with environmental monitoring parameters, each wear point of the protective coating is accurately positioned in combination with image data acquired by the unmanned aerial vehicle, and accurate control of the flight position of the unmanned aerial vehicle is realized by acquiring feature points of each blade sub-area. And meanwhile, the flight speed and the coating flow of the unmanned aerial vehicle are dynamically corrected in time by periodically collecting the thickness of a spraying layer in the spraying process, and the spraying execution efficiency is improved.

The invention relates to a method for vehicle-based control of a drone (60). The method comprises determining a flight route (92) of the drone (60) and a drone speed profile for the flight route (92) of the drone (60) based on a driving route (90) of a vehicle (50), wherein the drone (60) is controlled from the vehicle (50) via a communication link (70) between the vehicle (50) and the drone (60), an exchange of the flight route (92) and the drone speed profile takes place between the vehicle (50) and the drone (60) so that both the vehicle (50) and the drone (60) have the flight route (92) and the drone speed profile stored, and in the event of at least one interruption of the communication link (70), the drone (60) flies the flight route (92) at a drone speed corresponding to the drone speed profile.

The invention provides an unmanned aerial vehicle entering stage air collision risk analysis method, which comprises the steps of modeling unmanned aerial vehicle entering modes, including a horizontal entering-vertical descending entering mode and a waiting circle-waiting point entering mode; establishing a collision risk model, and calculating position errors of the unmanned aerial vehicle in the horizontal direction and the vertical direction according to a horizontal alarm threshold and a vertical alarm threshold of an unmanned aerial vehicle navigation system; calculating a safety interval between adjacent unmanned aerial vehicles based on a collision risk model; the method comprises the following steps: performing Monte Carlo simulation by considering the randomness of speed error, wind shear and flight speed as well as a pitch angle and a course angle to obtain a relative speed, calculating collision risks at different intervals, comparing safety target levels, and calculating the minimum safety interval of the unmanned aerial vehicle in a horizontal approach-vertical descent approach mode; and calculating a minimum route included angle in the approach mode by using the waiting circle and the waiting point, and planning safety intervals in different approach modes.

The invention relates to the technical field of unmanned aerial vehicle obstacle avoidance, in particular to an unmanned aerial vehicle autonomous obstacle avoidance method and system based on visual SLAM, and the method comprises the steps: obtaining multi-source sensor data of an unmanned aerial vehicle, the multi-source sensor data at least comprises load data, visual image data, inertial vibration data and system energy state data; constructing an obstacle environment map according to the visual image data and the inertial vibration data; determining a maneuvering energy index according to the system energy state data and the load data; and determining an obstacle avoidance path based on the current flight speed of the unmanned aerial vehicle, the load data and the maneuvering energy index, and generating an emergency obstacle avoidance instruction based on the obstacle avoidance path and an obstacle environment map, so as to control the unmanned aerial vehicle to realize emergency obstacle avoidance according to the emergency obstacle avoidance instruction. The method has the effect of improving the obstacle avoidance precision and stability of the unmanned aerial vehicle under the high-load condition.

This utility model discloses an adjustable two-dimensional tail nozzle, belonging to the field of two-dimensional tail nozzle technology; it includes a connected engine and an adapter casing. A servo is provided on one side of the adapter casing. The output side of the adapter casing consists of a rectangular opening formed by two oppositely arranged fixed plates and two oppositely arranged adjusting plates. A power arm is provided at the output end of the servo. The right end of the power arm is connected to two parallel first connecting rods by a pin shaft. The other ends of the two first connecting rods are respectively connected to two second connecting rods. It can be applied to small afterburning turbojet engines to improve the flight speed of UAVs. Its structure is simple. The synchronous opening and closing movement of the adjusting plates is achieved through a single servo drive source, reducing the control difficulty, realizing engine thrust adjustment, reducing the number of structures, and making it lightweight, highly reliable, and low in cost. By setting a support rod on the outside of the adjusting plate, the adjusting plate can be limited. The structure is simple and the use effect is good.

An ultra-high-speed helicopter with stowed single-blade coaxial rotors is provided and relates to the technical field of aircrafts. The ultra-high-speed helicopter includes a fuselage. Wings and tails can be arranged on the fuselage, respectively. Tail blades can be arranged at a tail end of the fuselage. A rotor mechanism can be arranged on a top of the fuselage. The rotor mechanism includes rotors. The rotor mechanism can drive the rotors to be stored in a rotor storage cabin of the fuselage. When the helicopter flies at high speed, the rotors stop working, and tail blades provide propulsive force and the wings provide lift force, so that the defects in the aerodynamic characteristics of the rotors are avoided during high-speed flight. In addition, the rotors can be retracted and stowed in a fuselage to further reduce drag and increase the maximum flight speed.

The application discloses a kind of unmanned aerial vehicle autonomous landing method and system based on vision, realize the dynamic landing pad autonomous landing of unmanned aerial vehicle under unknown environment;Adopt the feature extraction and state estimation method of unmanned aerial vehicle vision sequence, according to the center position of the dynamic landing pad, motion direction, motion speed and other features extracted from processed visual information, estimate the relative pose of itself and dynamic landing pad, predict dynamic landing pad space-time state and motion behavior;According to the perception result of unmanned aerial vehicle, directly generate the control instruction of the motion direction, lifting height, flight speed and other of unmanned aerial vehicle, realize the dynamic landing pad landing task of unmanned aerial vehicle under GPS denial unknown environment;The method combines the multi-control network cooperative control based on deep reinforcement learning and target space-time state prediction method, so that unmanned aerial vehicle autonomously completes the dynamic landing pad landing task of unmanned aerial vehicle under unknown environment without human intervention, greatly improves the autonomy and intelligence of unmanned aerial vehicle.

The utility model relates to the technical field of ore blasting, and particularly discloses an ore blasting flying stone prevention device which comprises a top plate and a base, a reinforcing plate is arranged between the top plate and the base, inclined baffles are arranged on the left side and the right side of the reinforcing plate, the upper ends of the inclined baffles are fixedly connected with the top plate, and multiple sets of hanging rod structures are arranged on the sides, away from the reinforcing plate, of the inclined baffles. A plurality of first tires are hung on the hanging rod structure, and the first tires are stacked; the top of the top plate is provided with a plurality of second tires which are stacked, and the top of the top plate is provided with a positioning rod set used for limiting shaking of the second tires. The inclined baffle can block broken stones coming from the front, the top plate can block the broken stones falling from the upper portion, when the inclined baffle is impacted by flying stones, the tires can buffer the flying stones coming from impact, the flying speed and harm of the flying stones are reduced, the reliability of the inclined baffle is improved, and the tires are assembled in a hanging mode, so that replacement and maintenance are convenient for workers.

The embodiment of the invention provides an unmanned aerial vehicle self-adaptive telegraph pole insulating paint spraying method and device, and the method comprises the steps that in the spraying operation process, operation environment parameters are obtained in real time, the operation environment parameters are input into a pre-trained reinforcement learning model, and the operation environment parameters comprise the wind speed, the paint temperature and the telegraph pole surface coating state; the reinforcement learning model generates and outputs a pumping pressure adjusting instruction and a flight control instruction in real time according to the input environmental parameters; and according to the pumping pressure adjusting instruction and the flight control instruction, a spraying mechanism is synchronously controlled to conduct atomization spraying at the target pumping pressure, and the unmanned aerial vehicle is controlled to fly along the spraying object at the target flight speed till the thickness of the coating on the surface of the telegraph pole meets the target thickness. The stability and the consistency of the spraying quality are improved, and the coating thickness error is controlled within a preset range; the coating waste caused by environmental fluctuation is greatly reduced, the working efficiency is improved, manual high-altitude operation is avoided, and corresponding safety risks are thoroughly eliminated.

The application relates to the technical field of unmanned aerial vehicle control, and discloses an unmanned aerial vehicle endurance prediction method and system, which comprises the following steps: setting a dynamic sensing area based on a flight speed direction and a body, and cooperatively collecting sensing data sets; performing multi-source space-time registration on laser point clouds and millimeter wave echoes based on pose information to obtain a fusion candidate point set; performing state classification identification and effective target condensation on the candidate point set to obtain a current obstacle target; performing space parameter solving and time sequence stabilization processing on the current target to generate a structured obstacle target; judging a safety corridor according to a flight path and a work line direction to obtain a forward passing state; and finally, calculating a risk level by comprehensively considering the forward passing state and motion characteristic parameters, mapping the risk level to a risk action mapping strategy, and outputting corresponding control instructions; the application can improve the efficiency of unmanned aerial vehicle endurance prediction.

The invention provides a catapult kinetic energy measurement method and device, electronic equipment and a storage medium, and the method comprises the steps: inputting a print image generated by the impact of a catapult launched by a catapult and the bullet correlation information of the catapult into an improved target detection model, obtaining an imprint prediction frame and an imprint prediction category in an imprint image output by the improved target detection model; after the target area image in the print prediction frame is optimized, the actual print area is calculated according to the optimized target area image; calculating the kinetic energy of the catapult according to the mass of the catapult and the flight speed after launching, and calculating the unit area kinetic energy of the catapult according to the kinetic energy of the catapult and the actual print area; the improved target detection model is obtained through training by taking an imprint image sample and corresponding bullet correlation information as samples and taking an imprint category labeling result and an imprint frame labeling result in the imprint image sample as labels. According to the invention, rapid and accurate measurement of kinetic energy measurement is realized.

The unmanned aerial vehicle pose joint debugging system and debugging method relate to the unmanned aerial vehicle testing technical field. In order to solve the problem of how to realize multiple flight attitudes of the unmanned aerial vehicle without causing the unmanned aerial vehicle to explode. The present application comprises an unmanned aerial vehicle loading platform, a suspension platform, a pose detection mechanism and a control mechanism, the unmanned aerial vehicle is installed on the unmanned aerial vehicle loading platform and can move; the unmanned aerial vehicle loading platform is on the upper surface of the suspension platform and can be suspended above the suspension platform; the pose detection mechanism is used for acquiring position attitude data, flight path and flight speed of the unmanned aerial vehicle; the control mechanism can acquire the data acquired by the pose detection mechanism, and can control the suspension platform to always hold the unmanned aerial vehicle loading platform floating with the flight of the unmanned aerial vehicle.

The present disclosure provides a fin stabilized projectile which can accommodate subsonic and supersonic flight velocities, wherein flight performance characteristics of the projectile are stabilized. The projectile is configured to be incorporated into a sabot free cartridge, wherein the projectile can be launched from a smooth bore barrel. The projectile includes an elongate body having a diverging ogival nose section extending rearward from a leading end, a converging ogival back section terminating at a trailing end; and a tail segment having a tail fin projecting radially from the back section and extending longitudinally forward of the trailing end of the elongate body and extending longitudinally rearward of the trailing end of the elongate body.

The invention discloses an angle adjusting method and device for shooting hot spots of a photovoltaic power station by using an unmanned aerial vehicle, and belongs to the technical field of image acquisition and analysis, and the method comprises the steps: S1, obtaining basic data; s2, the optimal flight height is calculated according to the focal length of the infrared camera, the flight angle, the installation angle of the photovoltaic cell panel, the illumination intensity, the solar altitude, the wind speed and the environment temperature change; s3, adjusting the pitching angle of the infrared camera according to the optimal flight height, the solar altitude angle, the illumination intensity, the wind speed, the environment temperature change, the focal length of the infrared camera and the linear distance of the starting point; and S4, calculating a shortest flight path according to the optimal flight height, the flight speed of the unmanned aerial vehicle, the shooting task time, the image resolution, the flight angle, the solar altitude angle, the environment temperature value before flight of the unmanned aerial vehicle, the illumination intensity, the wind speed and the environment temperature change. According to the invention, the hot spot detection precision can be improved.

A camera 16 onboard an airborne or spaceborne platform 12, moving in a flight direction 14 around the earth at a flight velocity Vgsat, is pivotable about a roll axis 18 in line with the flight direct

The application discloses an angle adjusting method and device for shooting a hot spot of a photovoltaic power station by using a UAV, and belongs to the technical field of image acquisition and analysis, and comprises the following steps: S1, acquiring basic data; S2, calculating an optimal flight height according to an infrared camera focal length, a flight angle, an installation angle of a photovoltaic cell panel, an illumination intensity, a solar elevation angle, a wind speed and an environmental temperature change; S3, adjusting a pitch angle of the infrared camera according to the optimal flight height, the solar elevation angle, the illumination intensity, the wind speed, the environmental temperature change, the infrared camera focal length and a straight-line distance of a starting point; and S4, calculating a shortest flight path according to the optimal flight height, a UAV flight speed, a shooting task time, an image resolution, the flight angle, the solar elevation angle, an environmental temperature value before the UAV flight, the illumination intensity, the wind speed and the environmental temperature change. The application can improve the precision of hot spot detection.

The invention discloses an unmanned aerial vehicle electronic fence method based on an artificial potential field method, and the method comprises the following steps: S1, delimiting an electronic fence boundary based on a current flight region of an unmanned aerial vehicle, the interior of the boundary being a flight region, and the exterior of the boundary being a limited / no-fly region; s2, dividing the flight area into a plurality of concentric annular areas according to the distance; s3, based on the current position of the unmanned aerial vehicle, determining the current area of the unmanned aerial vehicle, and obtaining the expected acceleration corresponding to the area; s4, calculating an expected speed based on the expected acceleration; and S5, adjusting the flight speed of the unmanned aerial vehicle according to the calculated expected speed, and returning to the step S1 until the unmanned aerial vehicle lands. According to the method, the motion range of the unmanned aerial vehicle is effectively limited, the risk that the unmanned aerial vehicle rushes out of the fence is reduced, the problem of control failure caused by satellite signal interference and environmental factor influence in a traditional method is avoided, and the method has wide applicability and expandability.

The invention discloses a spraying operation method, device and equipment of an unmanned aerial vehicle and a storage medium, and relates to the technical field of unmanned aerial vehicles. The unmanned aerial vehicle carries a spraying device, the spraying device comprises a water pump and a spraying disc, and the method comprises the steps that the actual flight speed of the unmanned aerial vehicle in the spraying operation process is obtained; determining an expected water pump rotating speed according to the actual flight speed; determining an expected spraying disc rotating speed according to the expected water pump rotating speed; determining an adjusting sequence of a water pump and a spraying disc; adjusting the rotating speed of the water pump to the expected rotating speed of the water pump and adjusting the rotating speed of the spraying disc to the expected rotating speed of the spraying disc based on the adjusting sequence. Through the technical means, the rotating speed of the water pump and the rotating speed of the spraying disc of the spraying device are sequentially adjusted in real time according to the actual flight speed of the unmanned aerial vehicle in the spraying operation process, the problem that atomized particles of sprayed liquid are too fine or cannot be atomized in the prior art is solved, and the spraying effect of the unmanned aerial vehicle is improved.

The application belongs to the field of aircraft design, and particularly relates to a variable angle tail wing configuration for a high Mach number aircraft, comprising a left wing, a right wing, a left tail wing and a right tail wing; the left tail wing and the right tail wing are arranged in mirror symmetry along a fuselage symmetry plane, the root of the left tail wing and the root of the right tail wing are connected to a tail wing rotating shaft, and the tail wing rotating shaft is rotationally connected to a wing trailing edge; the rotation angle of the left tail wing and the right tail wing is 0° to ±90°; a power unit is connected to a flight control system of the aircraft, and the flight control system of the aircraft can control the left tail wing and the right tail wing to rotate by 0° to ±90° along the tail wing rotating shaft. The tail wing serves as a lifting surface at a low speed stage according to the aerodynamic characteristic requirement at different flight speeds, and increases the lift of the aircraft. The tail wing serves as a heading stability and control surface at a high speed stage, and solves the problem of insufficient heading stability at a high Mach number. A dihedral angle of the tail wing is reasonably selected, and the peak value of wing area caused by the requirement of lift and heading stability in traditional design is avoided.

The invention discloses a dual-constraint energy management method of a hybrid propulsion system. The method comprises the following steps: constructing an energy demand prediction method of the hybrid propulsion system; dynamically calculating the lower limit SOElow of the energy state of the super capacitor by combining the current flight speed and the real-time state of the fuel cell based on the energy demand prediction and working condition identification result, and dynamically calculating the upper limit SOEhi of the energy state of the super capacitor by combining the current flight speed and the braking working condition parameters based on the energy demand prediction and working condition identification result; a corresponding real-time power distribution strategy is formulated according to energy state operation, and it is ensured that the hybrid propulsion system works in a safe interval under different conversion working conditions, and a fuel cell operates at high efficiency. According to the hybrid propulsion system, power distribution of the fuel cell and the super capacitor is subjected to dual constraint through energy demand prediction, it is ensured that the hybrid propulsion system operates efficiently and stably under different working conditions, and the energy utilization efficiency and safety of the hybrid propulsion system are improved.

An ultra-high-speed helicopter with stowed single-blade coaxial rotors is provided and relates to the technical field of aircrafts. The ultra-high-speed helicopter includes a fuselage. Wings and tails can be arranged on the fuselage, respectively. Tail blades can be arranged at a tail end of the fuselage. A rotor mechanism can be arranged on a top of the fuselage. The rotor mechanism includes rotors. The rotor mechanism can drive the rotors to be stored in a rotor storage cabin of the fuselage. When the helicopter flies at high speed, the rotors stop working, and tail blades provide propulsive force and the wings provide lift force, so that the defects in the aerodynamic characteristics of the rotors are avoided during high-speed flight. In addition, the rotors can be retracted and stowed in a fuselage to further reduce drag and increase the maximum flight speed.

The invention discloses an asphalt pavement compaction degree detection method based on an unmanned aerial vehicle-mounted ground penetrating radar. The method comprises the following steps: step 1, obtaining construction section asphalt pavement parameters; 2, designing a detection route; 3, determining the flight height; 4, the amplitude Ap of surface reflection in the metal plate calibration signal is obtained through calibration; 5, the flight speed of the unmanned aerial vehicle on the construction section asphalt pavement is determined; step 6, the unmanned aerial vehicle carrying the ground penetrating radar takes off, the asphalt pavement to be detected is detected, and the position coordinates of each flight moment and the amplitude A0 reflected by the pavement surface in the pavement signal are recorded in real time; and step 7, according to Ap and A0, calculating to obtain the dielectric constant of the asphalt pavement under each position coordinate, and further calculating to obtain the compaction degree of the asphalt pavement under each position coordinate in real time. According to the method, the compaction degree of the asphalt pavement in the compaction process can be rapidly and accurately provided in real time so as to guide on-site pressure supplementing and repairing work, and the compaction quality of the on-site asphalt pavement is guaranteed.

The application discloses a fire-fighting unmanned aerial vehicle autonomous obstacle avoidance flight control method based on visual measurement, relates to the technical field of fire-fighting unmanned aerial vehicle flight control, and comprises the following steps: acquiring a continuous original image frame sequence collected by an on-board visual sensor of an unmanned aerial vehicle, identifying and segmenting dynamic and static obstacle regions through pixel-level visual analysis, and outputting an obstacle region segmentation graph; synchronously solving instant position data of the unmanned aerial vehicle and aligning the instant position data with the segmentation graph in space and time to generate a real-time environment threat field of the unmanned aerial vehicle body coordinate system; constructing a synthetic virtual potential field containing a repulsive potential field and a guide potential field, calculating a theoretical flight speed vector by using a gradient descent method, generating executable flight control instructions through smoothness constraint and dynamic school test, and driving the unmanned aerial vehicle to adjust the attitude and position. The application can improve the obstacle avoidance sensing precision of the fire-fighting unmanned aerial vehicle, optimize the environment threat representation fitting degree, and guarantee the stable execution of autonomous obstacle avoidance flight.

The invention relates to the technical field of unmanned aerial vehicle emergency search and rescue, and discloses an air-ground cooperative emergency search and rescue mobile terminal positioning method and system based on an 8-shaped track of an unmanned aerial vehicle, and the method comprises the steps: controlling the unmanned aerial vehicle to fly above a target search and rescue region according to a preset 8-shaped track, and carrying out the multi-angle geometric observation of a ground target; acquiring flight state data in real time by using an acquisition load carried by the unmanned aerial vehicle; dynamically adjusting a signal acquisition strategy of the radio frequency front end according to the current flight speed; binding position information and a timestamp at a collection moment for each successfully captured international mobile subscriber identity to form a data tuple; and calculating the geographic position of the corresponding ground terminal in real time based on a plurality of data tuples formed by capturing the same international mobile subscriber identity for multiple times and the signal intensity of each point. According to the invention, the multi-angle observation of the 8-shaped track on the ground target and the real-time positioning output of the IMSI are realized.

The application discloses a smoke screen jamming bomb launching optimization method and system based on a 0-1 dynamic programming model, relates to the technical field of jamming bomb launching, and comprises the following steps: constructing different launching scenes of a UAV carrying a smoke screen jamming bomb to interfere with an incoming missile; in view of the different launching scenes, discretizing time, constructing a motion trajectory model of the UAV, the missile, free fall of the smoke screen jamming bomb and a smoke cloud cluster, constructing an equation of a line connecting the missile and a target point at each time point, determining the distance from the center point of the smoke cloud cluster to the line, establishing a shielding model according to the relationship between the distance and the radius of the cloud cluster; defining whether the shielding condition is met at the discretized time as a decision variable, taking the maximum of the accumulated discrete shielding effective time as the target, combining the constraint conditions of the flight angle and the flight speed of the UAV, the launching time and the detonation time of the smoke screen jamming bomb and the shielding model, constructing a 0-1 dynamic programming model at the discretized time, and obtaining the optimal launching strategy through solving.

The application discloses a single unmanned aerial vehicle autonomous path planning method in a network-free environment, which comprises the following steps: 1) according to the distance between the unmanned aerial vehicle and surrounding obstacles, obstacles on a flight road are divided to obtain the state level of the surrounding environment of the unmanned aerial vehicle; 2) a targeted flight method is formulated according to the state level of the surrounding environment of the unmanned aerial vehicle; 3) multi-target optimization is introduced into the path planning method, and the flight method of the unmanned aerial vehicle is comprehensively controlled through three different factors, i.e., average flight speed, flight decision number and flight energy consumption; and 4) according to the multi-target optimization, a reward function in a DDPG method is further optimized. The method can effectively cope with different flight environments, and the path planning capability of the unmanned aerial vehicle is greatly improved.

The invention discloses a multi-rotor unmanned aerial vehicle inclined lifting force device, and relates to the technical field of aircrafts, the device comprises a lifting force wing device and an unmanned aerial vehicle fixing device, the lifting force wing device comprises a frame connecting structure and a lifting force wing structure, the frame connecting structure is of a hollow design, and is used for connecting the unmanned aerial vehicle fixing device and the lifting force wing structure; through dynamic optimization of aerodynamic lift assistance and an intelligent regulation and control algorithm of a lift wing structure, rotor energy consumption is reduced, battery film auxiliary power supply is matched, the cruising ability is improved, environment airflow changes are captured in real time through a sensing data acquisition assembly, lift distribution and rotor rotating speed are rapidly adjusted through the algorithm, and the reliability of the system is improved. The stability of the fuselage is enhanced by combining the aerodynamic characteristics of the lift wings, the flight speed is increased, the wind resistance performance is optimized, rotor wing faults are detected through the fault response sub-module, emergency lift force distribution is triggered, the fuselage balance is maintained by means of the emergency lift force of the lift wings, and the air crash risk caused by the rotor wing faults is avoided.

The invention discloses an obstacle avoidance inspection method and device for an unmanned aerial vehicle, equipment and a storage medium. The method comprises the following steps: firstly, acquiring configuration parameters, point cloud environment data and motion data; an environment model is constructed through multi-source data fusion processing, the terrain of an inspection area and the position of a static obstacle are accurately represented, and then a static obstacle avoidance route is determined. And continuously fusing environment and motion data to obtain an effective data set, dynamically delimiting a coverage range in combination with an obstacle avoidance early warning distance and a flight speed, generating a real-time local environment map, extracting features to construct an obstacle model, and accurately identifying static and dynamic obstacles. Calculating the distance between the path and the obstacle in real time, when the distance is lower than a safety threshold, generating a dynamic obstacle avoidance track based on the current state and the static route of the unmanned aerial vehicle, and performing smooth regression after obstacle avoidance; and when the unmanned aerial vehicle arrives at a preset waypoint, stably hovering at a preset height to collect inspection data. The method can optimize the route, remarkably improves the flight safety, guarantees the data reliability, and is suitable for complex scenes such as bridges and tunnels.

A method for simulating a failure of a combustion engine of a single-engine rotorcraft, the rotorcraft comprising a controller controlling the combustion engine. The method comprises: i) arming a training mode by operating an arming button in communication with the controller, the training mode not being able to be activated in the absence of the arming of the training mode; ii) subject to the arming, activating the training mode by operating an activation button that is in communication with the controller, the controller consequently controlling a deceleration of the combustion engine to reach the idling speed; iii) deactivating the training mode by operating the activation button again, the controller consequently controlling an acceleration of the combustion engine to reach a flight speed, the training mode being able to be reset only during a new simulation phase.