1124 results about "Fixed wing" patented technology

The invention relates to the technical field of flight control, in particular to a fixed-wing unmanned aerial vehicle attitude correction and precise flight control method fused with visual navigation, which comprises the following steps: extracting ORB feature points and constructing a dynamic feature point cloud; simultaneously acquiring angular velocity and acceleration data of the inertial measurement unit; performing tight coupling fusion processing on the dynamic feature point cloud and the inertial measurement data to generate real-time pose data; inputting the real-time pose data into an attitude correction parameter calculation module, and generating an attitude correction parameter through a dynamic weight distribution algorithm in combination with a preset flight path planning model and GPS positioning data; and a control surface deflection instruction and an accelerator control instruction are generated through the multi-constraint optimization model, and unmanned aerial vehicle flight attitude closed-loop correction is completed. According to the method, aerodynamic parameters such as the air speed, the wind field lateral disturbance and the attack angle are introduced to serve as coupling input, the control surface deflection amount and limiting conditions are dynamically adjusted, and self-adaptive modeling and control over the nonlinear flight characteristics are achieved.

The invention relates to the technical field of unmanned aerial vehicles, in particular to an intelligent flight path planning and energy management system and method for a long-endurance fixed-wing unmanned aerial vehicle. Comprising an environment sensing unit; the flight path planning unit is used for planning a flight path meeting task requirements, safety requirements and energy constraints based on the flight environment information of the unmanned aerial vehicle acquired by the environment sensing unit and pre-stored performance parameters of the unmanned aerial vehicle; and the energy management unit realizes energy dynamic management and optimization according to the real-time energy state of the unmanned aerial vehicle, the flight task and the planning result of the flight path planning unit. The flight path planning unit can call working condition energy consumption data such as navigational speed and height output by the energy management unit in real time, and dynamically adjust the weight of the path to avoid high-energy-consumption flight segments; the energy management unit synchronously and intelligently adjusts a main / standby battery charging and discharging strategy to optimize energy distribution according to a task time sequence (such as waypoint priority and track curvature) of a track.

The invention discloses a fixed-wing unmanned aerial vehicle trajectory tracking control system and method based on a disturbance observer. The system acquires various state data of the unmanned aerial vehicle through the data acquisition module, the interference observer module estimates external interference in real time based on a dynamic model, the trajectory planning module generates an optimized trajectory according to tasks and environments, and the controller module realizes accurate control by adopting a model prediction control and sliding mode control composite strategy. And the execution mechanism driving module executes the control instruction. The method comprises the steps of data acquisition, interference estimation, trajectory planning, controller design and calculation, actuating mechanism driving and the like. The method can effectively improve the trajectory tracking accuracy and stability of the fixed-wing unmanned aerial vehicle in a complex environment, and has a wide application prospect.

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.

The invention discloses an adversarial reinforcement learning training method for robust control of a fixed-wing aircraft, and the method comprises the steps: constructing a nonlinear simulation environment and a task set of the fixed-wing aircraft, and constructing a plurality of fixed-wing aircraft agents in parallel in the simulation environment; an adversarial agent module based on a neural network AdvNet is introduced to generate environmental disturbance. A near-end strategy optimized Actor-Critic structure is adopted, an intelligent agent and an adversarial agent module are subjected to joint training through a task set, and a robust control strategy is obtained step by step. In the training process, based on a course learning mechanism, disturbance constraint parameters of the confrontation agency are dynamically adjusted according to the completion condition of a flight task. After training convergence, obtained control strategy parameters are applied to the fixed-wing aircraft, and robust flight control is achieved. According to the method, the robustness and the control precision of the aircraft facing complex environment disturbance can be improved, and the method is suitable for various flight missions with uncertainty.

The utility model relates to a cross-medium aircraft convenient for adjusting flight attitude, which comprises a water-drop-shaped centrosymmetric aircraft body with an aircraft head and an aircraft body, and the aircraft head of the aircraft body is positioned on the front side of the aircraft body. The aircraft body is further provided with an underwater power mechanism used for providing underwater flight power and an air power mechanism used for providing air flight power, the side portion of the aircraft body is connected with four or six fixed wings, slip-flow rudders controlled to rotate are arranged on the rear edges of the fixed wings, and the rotating axes of the slip-flow rudders are parallel to the wing faces of the fixed wings and perpendicular to the long axis of the aircraft body. Each fixed wing is provided with a slipstream rudder, so that the cross-medium aircraft can be conveniently controlled to pitch, roll, yaw and other actions, and the cross-medium aircraft can be conveniently switched between a hovering flight attitude and a level flight attitude.

The invention discloses a multi-modal lightweight forest fire detection method suitable for a vertical take-off and landing fixed-wing unmanned aerial vehicle platform, and the method comprises the steps: carrying out the feature alignment and weight fusion of a visible light image and an infrared image, which are synchronously collected by an unmanned aerial vehicle, through a multi-modal early fusion method, and obtaining a fusion feature; carrying out lightweight down-sampling and multi-scale feature extraction on the fusion features to obtain a multi-scale feature set; performing cross-scale feature fusion on the multi-scale feature set by adopting a bidirectional feature pyramid network, and extracting dynamic change information to obtain time sequence features; performing multi-scale context enhancement on the time sequence features by using a spatial pyramid method based on cavity convolution, and performing global context and local texture modeling by using a lightweight Transform module to obtain high-level semantic features; and based on the high-level semantic features, a target detection frame, fire level classification, prediction uncertainty estimation and a pixel-level fire probability graph are generated in parallel through a multi-task output header.

The disclosure relates to hybrid unmanned aerial vehicle (UAV) having vertical take-off and landing (VTOL) capabilities. Specifically, the disclosure relates to a stable hybrid fixed angle rotor arrays UAV having VTOL capabilities with hovering capabilities using rotors and cruising using fixed wing.

The invention discloses a variable-structure water-air amphibious robot and a motion control method. The robot comprises a water-air amphibious robot body, a variable-structure wing system and an electric control system. The robot body comprises a sealed cabin, a propeller fixing assembly, a fluid shell and a variable support tail cover. The variable-structure wing system comprises a driving gear transmission assembly, a two-section folding wing and a wing folding linkage assembly; the electric control system comprises a control core element, a visual module, a power supply module, a GPS module and an underwater depthometer module which are arranged in the cabin body; the motion control method is based on a deep reinforcement learning control method, control generalization ability is enhanced through teacher and student strategies and random domain, and the motion control method has more advantages in scenes such as inaccurate modeling and large external disturbance change. The structure of the variable-structure water-air amphibious robot integrates the structures of a rotorcraft, a fixed-wing aircraft, an underwater robot and the like, the modes of the wings can be switched, and efficient movement operation of the water-air amphibious robot is achieved.

The invention relates to the technical field of aircraft trajectory planning, in particular to a dynamic gliding flight trajectory planning method for a fixed-wing aircraft, and the method comprises the steps: building an optimal control problem model with minimum system energy consumption as a target function; obtaining a nonlinear programming problem model; acquiring a corresponding single-time optimal trajectory and corresponding flight state data when the system energy consumption is minimum in the unpowered gliding flight stage and the powered recovery flight stage; and obtaining a multi-section type dynamic gliding flight path. According to the method, the iteration process of solving a nonlinear equation is avoided, the calculation burden of single iteration is remarkably reduced, the solving efficiency and robustness of the whole optimal control problem are greatly improved, and the optimal control effect is improved by designing the multi-section type dynamic gliding flight strategy of the unpowered gliding flight stage and the powered recovery flight stage. The stable periodic energy-obtaining gliding flight is realized by accurately compensating the flight energy deficit.

The claimed invention discloses a catapult launcher for a fixed-wing unmanned aerial vehicle (UAV), the launcher comprises a starting rail having an I-beam cross-section that comprises two sections that are foldable / unfoldable and mounted on adjustable supports, a carriage that is equipped with wheels that are configured to interact with an internal surface and with an external surface of the starting rail and that is equipped with a UAV interaction mechanism that is represented by fasteners and joint elements that interact with adapters that are fixed to a UAV's fuselage and made in a form of two plates, and a lower edge of the plates is produced with grooves so as to enable interaction with the fasteners and with detents in a form of hooks that are tangent to joint elements. The launcher is equipped with elastic cords that are symmetrically arranged along the starting rail and fixed to the carriage and to the starting rail, and with a release device. A beginning of the starting rail is provided with an inclined section, and the release device joins to the carriage on the inclined section and the carriage to the UAV, their reliable fixation and start of the carriage movement upon activation of the release device. This configuration ensures reliability and portability of the launcher as well as a safe UAV launch at a short acceleration distance.

The invention provides an unmanned aerial vehicle system with symmetrical crossed wings and a control method, and relates to the field of unmanned aerial vehicles. Comprising a fuselage structure, a power module and a flight control module, and the fuselage structure comprises a cylindrical fuselage and four wings which are arranged on the peripheral side of the cylindrical surface of the fuselage and are symmetrically and crosswise distributed; the four wings are distributed in an X-shaped crossing manner or a cross-shaped crossing manner; the power module comprises a motor and a propeller, the motor is arranged at a wingtip of the wing, an output shaft of the motor is in the same direction as the axial direction of the fuselage and faces the tail of the fuselage, and the propeller is connected to the output shaft of the motor; the flight control module is arranged in the fuselage and used for controlling the output rotating speed of the four motors. The four-rotor FPV unmanned aerial vehicle has the advantages of a four-rotor FPV and a fixed-wing unmanned aerial vehicle, lift force can be generated through wings, cruising and sprint can be achieved in a fixed-wing mode, pitching, yawing and rolling postures of the unmanned aerial vehicle can be controlled by changing the rotating speed of a motor, a control plane does not need to be designed for the unmanned aerial vehicle to control the postures, the structure is simplified, and cost is low.

The invention discloses an end-to-end obstacle avoidance method considering flight dynamics of a fixed-wing unmanned aerial vehicle, and the method comprises the steps: constructing a multi-source data synchronous collection module, and obtaining a monocular depth image and inertial navigation state data which are aligned in time sequence; an enhanced visual perception coding module is designed, and spatial position information of a tiny obstacle is reserved at the tail end of feature extraction through an asymmetric convolution strategy and a parallel spatial attention mechanism; constructing a state fusion and time sequence reasoning module, performing long and short time sequence modeling on the multi-modal features by using an encoder with a causal mask mechanism, and outputting potential decision variables; and constructing a kinematics constraint trajectory generation module, and mapping the neural network output into a three-dimensional control trajectory conforming to flight mechanics limitation. The problems that spatial information of a traditional convolutional neural network is seriously lost, an end-to-end model easily generates an illusion trajectory exceeding a physical limit and the like are solved, and the flight safety and robustness of the fixed-wing unmanned aerial vehicle in a complex low-altitude environment are remarkably improved.

The invention discloses an autonomous positioning and obstacle avoidance method for ground-approaching flight of a fixed-wing unmanned aerial vehicle, and the method achieves the high-precision positioning through constructing a stereogram and carrying out the feature point matching with a pre-stored base map, and achieves the safe and efficient obstacle avoidance through employing a dynamic constraint hierarchical progressive trajectory planning method. The problems of navigation and obstacle avoidance under the conditions of limited GPS signals and dynamic change of obstacles in ground-approaching flight are solved, and the survivability and task execution efficiency of the unmanned aerial vehicle in a complex environment are improved.

The invention relates to a foldable tilting four-rotor aircraft concept scheme design method based on task requirements. According to the method, task demand indexes such as voyage, cruising speed, task load, cruising height and hovering height are used as input, and the total design weight, power device parameters, rotor wing geometric parameters and fuselage and wing parameters of the aircraft are determined in sequence; and performance indexes such as hovering lift limit, level flight speed, climbing performance, practical lift limit, voyage and endurance in a helicopter mode and a fixed wing mode are calculated and analyzed respectively. And performing matching judgment on a performance calculation result and a task requirement, and performing iterative adjustment on key parameters such as a paddle disc load when the task requirement is not met, so as to form a closed-loop concept design process driven by the task requirement. According to the method, the vertical take-off and landing capacity and the fixed wing cruising performance can be systematically considered in the conceptual design stage, and systematicness, repeatability and engineering feasibility of scheme design of the folding type tilting four-rotor aircraft are improved.

The invention relates to a control method for improving the anti-interference performance of an aircraft based on jet flow, belongs to the technical field of anti-interference of fixed-wing aircrafts, and solves the technical problems that a passive flow control method in the prior art cannot adjust the control effect according to the current situation in actual use and is poor in control effect under non-design working conditions. According to the control method, the requirement for safe and stable operation of the aircraft in complex environments such as water surface take-off and landing and gust disturbance is considered, and the active flow control lift-augmentation and drag-reduction method for jet wing circular rector control is used; the lift coefficient of the aircraft can be improved to the maximum extent, and meanwhile, the wave resistance or wind resistance of the aircraft is improved in a stable maneuverability mode.

The invention relates to a fixed-wing unmanned aerial vehicle track anomaly detection method and device and a medium, and the method comprises the steps: building a radar detection noise model based on a radar equation and a signal-to-noise ratio formula; on the basis of the motion equation, simulating the motion process in normal and abnormal states to generate a real track, and adding noise to the real track by using a radar detection noise model to obtain noise-containing simulation track data; constructing a dynamic graph based on the simulated track data; inputting the dynamic graph into a space-time diagram neural network model; the time-space diagram neural network model comprises a diagram attention network layer, a long-short term memory network layer and a linear layer which are connected in sequence; and performing feature extraction and classification on the dynamic graph through a time-space diagram neural network model, and outputting a track anomaly detection result. Therefore, precise detection of tiny track abnormalities of the fixed-wing unmanned aerial vehicle, especially gliding faults and the like, is realized.

The invention relates to the technical field of unmanned aerial vehicles, in particular to an inflatable wing type variable wingspan unmanned aerial vehicle. The unmanned aerial vehicle comprises a vehicle body, variable inflatable wings are arranged on the two sides of the vehicle body, the variable inflatable wings are connected with an inflation and deflation mechanism arranged in the vehicle body, each variable inflatable wing comprises a hollow fixed inflatable wing body and an extended inflatable wing body, and an inflatable part of each extended inflatable wing body is arranged outside a hollow cavity of the corresponding hollow fixed wing body; the uninflated part of the extended inflatable wing body is arranged in the hollow cavity, and the extended inflatable wing body is connected with the telescopic part of the extended driving mechanism. According to the inflatable wing type variable wingspan unmanned aerial vehicle, the variable inflatable wings are adopted, the wingspans of the whole wings are adjusted by lengthening the inflatable wing bodies, the unmanned aerial vehicle adapts to different flight states, and the unmanned aerial vehicle is of a relative folding structure, so that multi-stage adjustment is achieved.

The invention provides a fixed-wing aircraft fuselage equal straight section assembly deformation prediction method, which comprises the following steps: establishing a three-dimensional simplified structure model of a skin assembly, a fuselage frame assembly and a bottom plate beam assembly according to geometric features; the skin assembly, the fuselage frame assembly and the bottom plate beam assembly are assembled, a constraint relation is applied, and a three-dimensional simplified structure model of the straight section of the middle fuselage is formed; grid division is carried out on the three-dimensional simplified structure model of the straight section of the middle fuselage; setting material attributes and mechanical boundary conditions for the three-dimensional simplified structure model of the straight section of the middle fuselage; solving a deformation result of the three-dimensional simplified structure model for the straight section of the middle fuselage; and evaluating and optimizing a calculation result. According to the method, the influence of the skin size of the middle fuselage straight section, the fuselage frame assembly size, the bottom plate beam size, the material attribute and the connection mode can be considered, and the deformation of the middle fuselage straight section of the fixed-wing aircraft can be rapidly calculated.

The invention belongs to the technical field of wind tunnel tests, and discloses a spiral flutter wind tunnel test method using a motor to control the rotating speed of a rotor, and the method comprises the following steps: constructing a spiral flutter wind tunnel test device using the motor to control the rotating speed; a comprehensive regulation and control method of motor rotation speed and wind tunnel incoming flow speed; and officially entering the spiral flutter wind tunnel test, and providing the spiral flutter wind tunnel test method for controlling the rotating speed of the rotor wing by the motor. According to the wind tunnel test speed regulation method provided by the invention, the motor can work within a load safety range while the comprehensive control of the rotating speed and the incoming flow speed can be ensured, and the safety and success of the test are ensured. The provided spiral flutter wind tunnel test method for controlling the rotating speed of the rotor wings through the motors provides technical support for spiral flutter wind tunnel tests of tilt-rotor aircrafts and fixed-wing propeller aircrafts.

The invention provides an unmanned aerial vehicle three-degree-of-freedom attitude measurement device, and relates to the technical field of unmanned aerial vehicle attitude measurement, and the unmanned aerial vehicle three-degree-of-freedom attitude measurement device comprises a yaw measurement device, a pitching measurement device and a rolling measurement device; the yaw measuring device is arranged at the bottom of the overall measuring device and used for fixing the overall device and measuring the yaw angle of the unmanned aerial vehicle. The pitching measuring device is arranged above the yaw measuring device and is used for measuring the pitching angle of the unmanned aerial vehicle; the rolling measuring device is located in the middle of the yaw measuring device and used for measuring the rolling angle of the unmanned aerial vehicle and connecting the measuring device with the measured unmanned aerial vehicle model. The three-degree-of-freedom attitude angle measuring and limiting device has the three-degree-of-freedom attitude angle measuring and limiting functions, and the limiting position can be adjusted according to actual application requirements. The device is adaptive to various small and medium-sized unmanned aerial vehicles with fixed wings, rotors, fan wings and the like, is simple and compact in structure and convenient and efficient to mount, has practicability and economy, and can effectively guarantee the accuracy and reliability of attitude measurement.

The invention discloses a fixed-wing aircraft super-maneuvering flight control method and system, relates to the technical field of aircraft control, and is used for solving the technical problem that the control precision of an aircraft is low due to the fact that an existing control mode shows obvious insufficiency when facing strong nonlinearity and coupling characteristics of the aircraft. The fixed-wing aircraft super-maneuvering flight control method comprises the steps that a fixed-wing aircraft simulation environment is established, and the initial state of fixed-wing flight is set as the current state; inputting the current state into a strategy network, and outputting a continuous control instruction by the strategy network; obtaining a reward function value according to the next moment state and the control effect; according to the strategy model, storing the state information, the action information and the reward information of the aircraft into an experience playback pool; optimizing network parameters of the strategy network by adopting a gradient descent algorithm; the optimized strategy network acts on a simulation model for training; and implementing real-time hyper-maneuver flight control on the aircraft by using the obtained strategy network.

The invention discloses a fixed-wing unmanned aerial vehicle distributed formation and obstacle avoidance method based on diffusion reinforcement learning, and the method comprises the steps: processing single observation data through a graph attention network, and enabling the single observation data to serve as a condition for generating an optimal action in a reverse denoising process; the method is suitable for distributed cluster control of a fixed-wing unmanned aerial vehicle cluster in an unknown and disordered environment, treats huge challenges brought by complex dynamics and non-integral constraints in the cluster, and effectively solves a series of problems that an existing method is difficult to capture multi-modal action distribution necessary for robust obstacle avoidance under an uncertain condition. A large number of numerical simulation results show that the method is obviously superior to an existing baseline method in the aspects of flight stability and collision rate, the potential of a diffusion model in the aspect of extensible and robust unmanned aerial vehicle flight control is highlighted, and the method has good theoretical popularization value and engineering application prospects.

An aircraft wing having a fixed wing and a moveably mounted wing tip device is disclosed. A first cable harness and a second cable harness which are received in a protective sleeve extend between the fixed wing and the wing tip device. The protective sleeve is in a secured configuration in which at least two opposing parts of the protective sleeve are secured together between the first cable harness and the second cable harness to provide the sleeve with a first channel in which the first cable harness is received a second channel in which the second cable harness is received, and a webbing region extending between the first channel and the second channel such that the first and second cable harnesses are held apart by the webbing region.

The invention discloses a shipborne fixed-wing aircraft landing guidance law design method and system, and belongs to the field of aircraft guidance law design. The problems that the multi-coordinate system coupling effect of ship motion and aircraft dynamics is not fully decoupled and an existing method is weak in adaptability to non-stable sea conditions are solved. The method comprises the following steps: defining related coordinate systems including a world coordinate system, a landing coordinate system and a ship body coordinate system; calculating an ideal landing point height change value caused by ship deck movement in real time according to the position of the ideal position in the ship body coordinate system; utilizing a KOA-LSTM hybrid forecasting model to predict a motion heave value of a ship deck at a future critical moment; designing a compensation value for the longitudinal position deviation based on the predicted motion heave value, and carrying out dynamic compensation correction on the longitudinal guide instruction; and according to the compensated guide instruction and the real-time position of the aircraft, calculating the transverse and longitudinal deviation of the aircraft relative to the expected landing trajectory to form closed-loop control. The device is mainly used for offshore operation.

The invention relates to the technical field of aviation safety, in particular to a fixed-wing aircraft natural icing prediction system based on a prediction model and big data analysis. Comprising a multi-source data acquisition module, a data processing module, a feature extraction module, an icing case database, a prediction model module, a prediction analysis module and an early warning result output module. The data processing module is used for preprocessing and cleaning the collected original data; the feature extraction module is used for extracting key feature variables having significant influence on natural icing of the aircraft from the processed data; the prediction model module is used for taking the extracted key feature variables as input and combining big data analysis to construct a prediction model; and the prediction analysis module is used for inputting the currently collected multi-source data into the trained prediction model for analysis, and by adopting the mode, the icing risk is predicted in advance, the operation fault-tolerant space is greatly increased, and the accurate prediction requirement in the flight scene can be met.

The invention discloses a hydrogen fuel cell-based extended-range vertical take-off and landing fixed-wing unmanned aerial vehicle, which comprises an unmanned aerial vehicle body and an extended-range power supply system arranged in the unmanned aerial vehicle body, the range-extended power supply system comprises a high-gas-state hydrogen cylinder, a pressure valve, a lithium battery, a hydrogen fuel cell, a DC-DC voltage stabilization module, an electric brushless turbofan and an FCU system control module, the high-gas-state hydrogen cylinder is connected with a hydrogen inlet of the hydrogen fuel cell through the pressure valve, and the electric brushless turbofan is connected with an oxygen inlet of the hydrogen fuel cell. The DC-DC voltage stabilizing module is connected with the hydrogen fuel cell, the lithium battery is used for providing peak power for the vertical take-off and landing stage of the unmanned aerial vehicle and providing basic circuit power supply for starting of the whole machine, and the FCU system control module is in communication connection with the pressure valve, the hydrogen fuel cell, the DC-DC voltage stabilizing module and the electric brushless turbofan. The problems that an existing unmanned aerial vehicle is short in endurance, slow in charging, high in pollution, high in maintenance cost, prominent in endurance and load contradiction and the like can be effectively solved.

The invention discloses a large fixed-wing unmanned aerial vehicle fire extinguishing performance evaluation test method, and relates to the field of aviation equipment. The method solves the problem that quantitative evaluation of fire extinguishing agent throwing precision and effective coverage range of a large fixed-wing unmanned aerial vehicle in a complex wind field environment is difficult, scale test parameter design is carried out based on similarity criteria and reference wind tunnel size, and then test model (unmanned aerial vehicle and fire extinguishing agent water tank) and adjustable cabin door structure design are carried out. The unmanned aerial vehicle model is installed on the upper tunnel wall of a wind tunnel through a lifting supporting rod in a back supporting mode, the fire extinguishing agent measuring system is installed on the central axis of a wind tunnel test section and is vertically aligned with a water tank, finally a large fixed-wing unmanned aerial vehicle fire extinguishing performance evaluation wind tunnel test is carried out, the effective range of a fire extinguishing agent is quantitatively treated, and the fire extinguishing performance is evaluated. The test method can effectively research the fire extinguishing performance of the large unmanned aerial vehicle under the influence of the flight speed, the launching angle, the height and the like of the unmanned aerial vehicle.

An aircraft including an aircraft wing wherein the aircraft wing includes a fixed wing, a wing tip device at an end of the fixed wing, and a wing tip device actuator configured to move the wing tip device between a flight configuration and a ground configuration. The wing tip device actuator includes a shaft which is rotatable about a shaft axis to selectively displace respective first and second elbows of the wing tip device actuator towards or away from the shaft. The first elbow is connected to the wing tip device and the second elbow is connected to the fixed wing such that movement of the respective elbows away from the shaft causes the wing tip device to move away from the flight configuration and such that movement of the respective elbows towards the shaft causes the wing tip device to move towards the flight configuration.

A wing assembly for an aircraft, the wing assembly having a fixed wing and a wing tip device moveably mounted at the end of the fixed wing. A wiring harness extends between the fixed wing and the wing tip device, a length of the wiring harness being encased in a length of protective sleeve. The protective sleeve is pre-shaped, for example pre-molded, to follow a path along a helical curve.