6429 results about "Gravity center" patented technology

The invention relates to the technical field of container models, in particular to a container model construction method based on three-dimensional software. The method comprises the following steps: obtaining point cloud data of a container through three-dimensional laser scanning, carrying out feature subdivision to generate a container feature set, carrying out space positioning on features to obtain a vertex coordinate set, carrying out geometric constraint modeling based on the vertex coordinate set, forming a container skeleton model, obtaining a target cargo image, extracting a basic contour, and carrying out feature extraction; the method comprises the following steps: carrying out three-dimensional reconstruction to generate a cargo model, carrying out space planning on a container skeleton based on the model, calculating gravity center distribution to generate a cargo balance parameter, then carrying out interference simulation and conflict detection to obtain interference conflict data, positioning a conflict focus area, and finally carrying out variant design on the container skeleton according to the conflict area. And generating an adjusted container model. According to the invention, a more comprehensive and more accurate container model construction method is realized.

The invention provides a humanoid robot falling control method, device and equipment and a storage medium, and relates to the technical field of humanoid robots. The control method comprises the following steps: acquiring state data of the humanoid robot in real time; predicting the current state of the humanoid robot according to the state data; and if the current state is the high-risk tumble state, controlling the humanoid robot to execute tumble protection action. According to the fall control method for the humanoid robot, the accuracy of fall prediction is improved by monitoring the gravity center position, the movement speed and the acceleration in real time. The method can quickly start the protection action under the high-risk condition, reduce the damage risk and protect the safety of surrounding personnel. The adaptability and autonomy of the robot are enhanced, the stability and safety are improved, the maintenance cost is reduced, and the service life is prolonged, so that the practicability and market competitiveness of the robot are enhanced, and the application range is widened.

The invention provides a lower limb and gravity center dynamic balance posture early warning method based on a body measurement all-in-one machine, and the method comprises the steps: obtaining a pelvis forward inclination angle, an arch height and a gravity center position under a standard standing posture, taking the pelvis forward inclination angle, the arch height and the gravity center position as individualized baseline data, and carrying out the statistical analysis of the baseline data, and generating a dynamic balance reference value reflecting the normal balance capability of an individual; on the basis of the dynamic balance reference value, in combination with a gravity center forward trend and a lower limb muscle compensation mode, a balance offset index in standing posture change is calculated through a time sequence analysis algorithm, and a dynamic balance risk assessment result is obtained; and if a dynamic balance risk assessment result exceeds a danger threshold, clustering analysis is carried out on associated parameters of the pelvic forward inclination angle and the arch height, grouping processing is carried out on the associated parameters, and potential reasons causing balance capability degradation are identified.

The invention discloses intelligent suspension conveying equipment for automobile tires, and relates to the technical field of tire conveying, the intelligent suspension conveying equipment comprises a suspension arm which is provided with a hollow cavity, and a sliding seat sliding in the axial direction of the suspension arm and a long-distance air cylinder driving the sliding seat to ascend and descend are arranged in the suspension arm; the telescopic sleeve piece at least comprises an inner sleeve body and an outer sleeve body connected to the outer wall of the inner sleeve body in a sliding and sleeving mode, the inner sleeve body is arranged on the outer wall of the suspension arm in a sliding and sleeving mode, a plurality of receding openings vertically extending are formed in the outer sleeve body, and connecting rods are hinged to the outer sleeve body and the side wall, corresponding to the receding openings, of the inner sleeve body. According to the invention, irregular acting force generated by elastic deformation recovery of the tire can be more uniformly dispersed, the contact points are gradually changed, and the force borne by each contact point can be effectively buffered and redistributed, so that the situation that the center of gravity is instantaneously and greatly shifted due to overlarge local stress is avoided, and the service life of the tire is prolonged. The change of the gravity center of each tire tends to be consistent, and the balance state of the stacked tires is effectively maintained.

The invention discloses a warehouse cargo supply chain management method and system based on AI big data, and relates to the technical field of warehouse management, and the method comprises the steps: collecting and preprocessing warehouse multi-source data, and predicting the cargo delivery frequency based on an LSTM neural network; and a multi-target scheduling model combining pickup path time consumption and storage gravity center control is constructed based on a prediction result, a cargo task and AGV path planning are jointly modeled into an open path multi-starting-point asymmetric TSP problem, an FWA-GA hybrid optimization algorithm is used for model solving, and an optimal cargo allocation matrix and an optimal AGV scheduling path table are obtained. Therefore, integrated joint optimization of task allocation, path planning and goods allocation layout is achieved, a supply chain platform is further linked to complete stockout early warning and supplier intelligent selection, and multiple limitations of a traditional method in the aspects of prediction precision, scheduling coupling, structure control, supply collaboration and the like are effectively broken through.

The invention belongs to the technical field of crawler agricultural mechanical equipment, and discloses a posture-adjustable crawler chassis and a control method.The posture-adjustable crawler chassis comprises a chassis frame, a driving transmission assembly, a posture adjusting assembly, a crawler walking wheel assembly and a posture detecting assembly; the output end of the track gauge auxiliary assembly is in universal transmission connection with the track walking wheel assemblies, the posture adjusting assembly is arranged below the chassis frame, one side of the posture adjusting assembly is connected with the track walking wheel assemblies, the posture detecting assembly is arranged on the chassis frame and the track walking wheel assemblies, and the two ends of the track gauge auxiliary assembly are installed on the track walking wheel assemblies on the two sides respectively. When the crawler encounters the situation that the road surface gradient is large or the road surface fluctuation is large, the posture position of the current chassis frame is detected through the posture detection assembly, and the ground clearance or the gravity center position of the chassis frame is adjusted by calculating and controlling the posture adjusting assembly. Meanwhile, the bottoms of the crawler walking wheel assemblies are always attached to the ground by driving the transmission assemblies, and the adhesive force of the crawler to the ground is improved.

The invention discloses a self-adaptive gravity center adjustment method and system for a transfer robot, and relates to the technical field of robot control, and the method comprises the steps: respectively collecting the three-dimensional information and contact force distribution information of an article and the contact force information between the robot and the article through a sensor, integrating the collected information to obtain a multi-modal data set, and carrying out the preprocessing of the multi-modal data set; utilizing a deep learning algorithm to extract visual feature vectors from the three-dimensional image information, and extracting tactile feature vectors from the contact force distribution information and the contact force information; fusing the extracted visual feature vector and the extracted tactile feature vector to obtain a multi-modal feature set; constructing a motion state model based on a deep learning algorithm, inputting the motion state model by using the historical multi-modal feature set, and outputting a control strategy; a control algorithm and a control strategy are optimized by using real-time feedback information; the invention provides a self-adaptive gravity center adjustment method by collecting multi-modal sensor data and combining a deep learning algorithm to perform feature extraction and fusion.

The invention relates to the technical field of sports equipment and rehabilitation, in particular to a split type treadmill control method capable of correcting gaits in a self-adaptive mode and a treadmill. The method comprises the following steps: acquiring air pressure and air pressure variation of each air bag in air-floating treadmills on two sides of the treadmill in a static scene or a dynamic scene to determine a static contact area or a dynamic contact area of the air-floating treadmills and feet, and converting the acquired air pressure variation into foot pressure; calculating a sole load index, a pressure ratio of the inner side to the outer side of a foot and a foot pressure gravity center according to the foot pressure, and adjusting the air pressure of all air bags of the air-floating treadmill to realize that the hardness grade and the inclination angle of the air-floating treadmill adapt to gait characteristics and training requirements of a user; by monitoring the air pressure and the air pressure variation in the air bag of the air floating treadmill in the dynamic scene and adjusting the air pressure of the air bag in the dynamic contact area, the foot pressure gravity center is always located in the gravity center shifting area, and the problems that an existing treadmill cannot adapt to training requirements, is poor in adaptability and is long in gait correction scheme adjusting period are solved.

The invention relates to the technical field of warehouse logistics equipment, and discloses an omni-directional intelligent mobile forklift control system. The system comprises a dynamic path planning module, an omnidirectional motion control module, a load stability monitoring module, an environment adaptive adjustment module and an intelligent obstacle avoidance decision module. The dynamic path planning module collects storage environment multi-dimensional spatial data and constructs a dynamic environment topological map; the omni-directional motion control module analyzes driving wheel parameters based on the map and generates an omni-directional motion composite motion instruction set; the load stability monitoring module collects a fork pressure distribution matrix and a cargo gravity center offset according to an instruction set, and calculates a stability compensation parameter; the environment adaptive adjustment module fuses illumination and slope data to generate a motion control constraint condition; and the intelligent obstacle avoidance decision module predicts a dynamic obstacle trajectory, outputs an obstacle avoidance path re-planning instruction and updates a map. The system can meet the requirements of modern intelligent warehousing.

The invention relates to the technical field of logistics automation, in particular to a full-automatic stacking method and system based on machine vision and path planning, and the method comprises the following steps: based on three-dimensional point cloud data of goods, extracting point cloud coordinates, normal vectors and curvature values of the surface of the goods, calculating the geometric segmentation range of point cloud edge features, and calculating the geometric segmentation range of the point cloud edge features; and calculating a fitting relationship between the boundary size and curvature distribution. According to the method, the surface point cloud coordinates, the normal vector and the curvature value are extracted based on the three-dimensional point cloud data, the accuracy of geometric feature description of the complex cargo surface is enhanced, the geometric center and the variance range are reasonably determined through spatial distribution analysis and feature set classification, the accuracy and stability of shape classification are improved, and the accuracy and stability of shape classification are improved through gravity center and size deviation calculation. The position and pressure distribution of the contact point are optimized, the space priority analysis of the grabbing point and the obstacle point is combined, the path planning and obstacle point elimination strategy is optimized, the path conflict is reduced, and the flexibility and efficiency of logistics operation are improved.

The invention relates to a control system for stabilizing an equipment foundation embedded part mounting device. Comprising the following steps that a dynamic sensing network is arranged on an embedded part mounting device, comprises a tilt angle sensor, a pressure sensor and a displacement sensor and is used for monitoring the dynamic balance state of the embedded part in real time and obtaining monitoring data; the monitoring data are integrated through the central processing unit to form real-time three-dimensional attitude and gravity center position feedback of the equipment foundation; constructing a posture adjustment algorithm based on real-time monitoring data, simulating mechanical changes in the installation process of the embedded part by utilizing a finite element dynamic analysis model, and calculating an adjustment angle and a position deviation; the inclination angle and height of the mounting platform are finely adjusted through an electric servo device, and self-adaptive posture regulation and control of the embedded part are controlled; a partition pressure control technology is adopted, the bottom of the mounting device is divided into a plurality of mechanical unit areas, and the supporting force of each area is adjusted in real time through a distributed pressure regulator; and dynamic balance monitoring data is combined.

The invention discloses an industrial robot based on an automatic production line, and belongs to the technical field of automatic production lines, the industrial robot comprises a grabbing mechanism and a driving mechanism used for driving the grabbing mechanism to move, the grabbing mechanism comprises a mounting seat, a mounting box, a connecting plate, a connecting box, a monitoring mechanism and a clamping mechanism, the mounting seat is connected to the top of the mounting box through a first universal ball, the connecting plate is connected to the bottom of the mounting box through a second universal ball, and the connecting box is slidably connected to the bottom of the connecting plate; the clamping mechanism comprises a driving plate, an air cylinder, two rotating shafts and four clamping plates, and a plurality of clamping wheels are rotationally installed in the clamping plates. Through cooperation of the monitoring mechanism and the clamping mechanism, the gravity center position of a grabbed object can be adjusted while the object is grabbed, so that the balance of the object in the grabbing and carrying process is guaranteed, falling is avoided, and the use stability is guaranteed.

The invention relates to the technical field of dynamic weighing, and discloses an intelligent load prediction and adjustment method in a dynamic weighing system, which comprises the following steps of: separating a weighing signal into a space domain static load characteristic (pressure point distribution sparsity and gravity center geometric vector) and a time domain dynamic inertial interference component (acceleration coupling noise) through space-time double-domain decoupling; the frequency spectrum aliasing problem of a traditional filtering algorithm is eliminated from a signal source; the future interference trend is predicted based on the real-time motion state of the carrier, a feed-forward compensation signal is generated through a pre-training dynamic basis function library, and dynamic errors are actively counteracted; in combination with sensor array space consistency detection and lightweight online learning, decoupling model parameters are dynamically corrected. According to the method, space geometric analysis and kinematics feedforward prediction are combined, a traditional signal processing framework is strided out, error source separation and real-time compensation are achieved, and the dynamic weighing precision of transient working conditions such as sudden stop and speed change is remarkably improved.

The invention discloses an automobile hoisting device, and belongs to the technical field of engineering hoisting. The problems that the gravity center of a component is difficult to accurately determine, the position and posture control of a cargo boom is inaccurate, and the load cannot be adaptively adjusted exist in the hoisting process of an existing automobile crane. The device comprises a truck crane body, a cargo boom tail end execution module, a cargo boom body sensing module, an environment sensing module and a control module. The control module is internally provided with a dynamic gravity center correction unit, a multi-sensor fusion unit and a self-adaptive load control unit, processes related sensor data based on Kalman filtering, extended particle filtering and a model prediction control algorithm, and outputs an adjustment instruction. The method is mainly used for improving the accuracy, safety and efficiency of automobile hoisting operation.

The invention belongs to the technical field of aircraft control, relates to an aircraft gravity center real-time balancing method and system based on dynamic parameter fusion, and aims to solve the problems of insufficient real-time performance, accuracy and self-adaptability of a gravity center balancing method under complex flight conditions in the prior art. The method comprises the steps that real-time parameters are obtained, and the real-time gravity center position is calculated; if the real-time gravity center position is not within the preset range, calculating a first inertia moment and a first additional moment caused by fuel density change and a second inertia moment and a second additional moment caused by aeroelastic deformation; performing inertia moment correction based on the first inertia moment and the second inertia moment; additional moment correction is carried out based on the first additional moment, the second additional moment and the real-time pitching inertia moment; when the real-time gravity center position is within the preset range, gravity center balancing is completed. The fuel oil density and aeroelastic parameters are estimated in real time through a self-adaptive control algorithm, rudder deflection and fuel oil distribution are cooperatively adjusted, and the problem of center-of-gravity shift under complex disturbance can be effectively solved.

The invention discloses a ship dangerous goods transportation safety control method and system, and relates to the field of marine transportation, and the method comprises the steps: obtaining dangerous goods parameter data of a dangerous goods monitoring sensor, the dangerous goods parameter data comprising gas concentration, temperature and smoke concentration; under the condition that the sensor parameter data exceeds a preset parameter threshold value, acquiring motion attitude data and inclination angle data of the current ship and pressure distribution data of the cargo on the bottom and the side surface of the cargo hold; calculating the center-of-gravity offset of the current ship based on the motion attitude data, the inclination angle data and the pressure distribution data; calculating a fixed adjustment parameter of the cargo fixing device based on the gravity center offset; and sending a device adjustment instruction containing the fixed adjustment parameter to the target client. By implementing the method, the efficiency of adjusting the cargo fixing device can be improved.

The invention discloses a quadruped inspection robot space positioning method and system based on gravity center sensing, and aims to construct a gravity center potential energy field through foot end contact force and body attitude information, form a gravity center disturbance mode in combination with fluctuation spectrum analysis, and reveal a disturbance propagation mechanism. A reverse compensation technology is adopted to generate an anti-disturbance sequence, a foot end force distribution topology is reconstructed, and active disturbance suppression is achieved; a multi-frequency detection wave beam and coherent superposition technology is introduced, an environment hologram is generated, geometric topology is reconstructed, and a high-precision environment sensing system is established; high and low impedance regions are identified through energy density analysis, and an energy optimal path is constructed in combination with double strategies of potential field bypassing and streamline tracking; establishing an oscillation analysis space for path projection simulation, identifying resonance risk points and determining stabilization parameters; finally, a coordinate reference is generated by adopting a quantum entanglement type multi-anchor-point synchronization mechanism, accurate positioning is realized by fusing environmental geometric information, and a technical closed loop from gravity center dynamics analysis to environmental perception navigation is realized.

The invention discloses a tunnel monitoring method and system based on a vibrating wire sensor, and relates to the technical field of tunnel engineering construction safety monitoring, and the method comprises the steps: collecting the vibration frequency data and spatial position coordinates of the vibrating wire sensor in a monitoring region; the method comprises the following steps: calculating a time difference and an energy attenuation ratio between adjacent sensors by extracting spectrum energy density distribution, and constructing a stress wave propagation field; dividing grids in the propagation field to calculate node stress values, generating a stress field distribution cloud picture and extracting a stress concentration area; calculating a gravity center position coordinate change rate and a stress time sequence curve of the stress concentration area, and determining fracture extension parameters; and calculating a surrounding rock bearing capacity attenuation curve based on the parameters, and outputting an early warning signal when the slope exceeds a threshold value. According to the invention, real-time monitoring and early warning of the tunnel surrounding rock instability risk are realized.

The invention discloses a real-time precise balance mechanism of a numerical control cradle rotary table, which comprises a base, the base is rotatably connected with the cradle rotary table, the end part of a rotating shaft of the cradle rotary table is fixedly provided with a connecting plate, the base is detachably provided with a track close to the connecting plate, the track is slidably connected with a telescopic piece, and the telescopic piece is fixedly connected with the rotating shaft of the cradle rotary table. The output end of the telescopic piece is rotationally connected with the connecting plate, a control valve is further arranged on the base, and the control valve is electrically connected with the telescopic piece and the system control end. When the balancing mechanism is used, the balancing mechanism can change along with the change of the gravity center of the rotating part of the rotary table, the cutting force and the weight of a machined workpiece, and the torque borne by the rotating part of the numerical control cradle rotary table is accurately balanced in real time. When the device is used, the expansibility is high, the precision of the numerical control cradle rotary table can be improved or the bearing capacity of the numerical control cradle rotary table can be improved by replacing configurations, and effective technical support is provided for the numerical control cradle rotary table in the aspect of product serialization type spectrum expansion.

The invention provides a coffee machine mechanical arm acceleration compensation control method and device based on toppling spill prevention, and relates to the technical field of mechanical arm control. A coffee machine calls a real-time acceleration sequence from an acceleration control library after receiving a real-time order, and a pipetting mechanical arm moves along a pipetting collision-free track in the process of clamping an order coffee cup to move along the pipetting collision-free track; the liquid gravity center offset is measured in real time through a six-axis force sensor integrated on a clamping jaw, and lagging shake offset of a real-time acceleration sequence is carried out according to the real-time gravity center offset. The technical problem that in the prior art, when a mechanical arm of a coffee machine transports coffee drinks containing heterogeneous liquid, the displacement control stability is insufficient, and pouring and scattering are likely to happen is solved. The technical effects that the coffee liquid is effectively prevented from spilling and leaking in the transportation process, the transportation stability of complex coffee drinks containing ice blocks, foam and the like is remarkably improved, safety and high efficiency of collaborative operation of the multiple mechanical arms are ensured, and the delay or overflow risk caused by liquid shaking is greatly reduced are achieved.

The invention provides an AGV control method, an AGV control device and an AGV, and the AGV control method comprises the steps: obtaining the stability parameters of the AGV during working, the stability parameters including but not limited to the gravity center position parameter, the inclination angle parameter and the vibration frequency parameter of the AGV; sequentially carrying out gravity center stability analysis, inclination stability analysis and vibration stability analysis according to the stability parameters, and generating corresponding analysis results; and the stability state of the AGV is determined according to the analysis result, and the response action of the AGV is determined according to the stability state of the AGV. The stability parameter of the AGV during working is obtained, the stability state of the AGV is judged according to the stability parameter, and when it is determined that the stability of the AGV is poor according to the stability state of the AGV, the stability parameter corresponding to the AGV is intelligently adjusted, so that the stability parameter of the AGV is adjusted to be within the normal range, normal operation of the AGV is ensured, and the working efficiency of the AGV is improved. And the stability, the reliability and the safety of the AGV are improved.

The invention discloses a tray forking method and system, a storage medium and a program product, and relates to the field of general control or adjustment systems.The method comprises the steps that tray area images are collected, and tray position coordinates and cargo distribution data are obtained; carrying out gravity center calculation to obtain a cargo plane gravity center predicted value, calculating a stress compensation coefficient of a scissor fork module, and determining an initial stress value; determining motion track parameters of the robot, and generating a motion control instruction for controlling a pallet fork of the robot to move to a preset position; an initial lifting instruction is generated and used for controlling a scissor fork module of the robot to conduct lifting motion; acquiring real-time stress data of the scissor fork module, determining a horizontal attitude deviation value of the tray, and generating a lifting compensation instruction for adjusting the real-time stress data so that the target tray is adjusted to a horizontal state; and generating a truck body forward moving instruction and a module homing instruction, and controlling the target tray to be placed on the truck body. According to the invention, the tray forking and moving stability of the robot can be improved.

The invention relates to the technical field of Internet of Things perception, in particular to an intelligent storage digital visual management system and method based on the Internet of Things. The method comprises the following steps: acquiring intelligent storage structure data; constructing a storage three-dimensional model according to the intelligent storage structure data; carrying out material carrying simulation based on the storage three-dimensional model to obtain material carrying data; identifying a high-frequency congestion area based on the material handling data; carrying out cargo placement analysis according to the high-frequency congestion area to obtain cargo placement data; identifying a cargo spatial form based on the cargo placement data to obtain cargo spatial form data; carrying out cargo gravity center shift detection according to the cargo spatial form data to obtain cargo gravity center shift data; and according to the cargo gravity center shift data, acquiring a cargo unique label to obtain cargo label data. The goods stacking safety rate and the goods shelf structure operation stability rate in intelligent storage are improved based on the Internet of Things sensing technology.

The invention relates to the field of electric power engineering construction safety management, and particularly discloses an electric power engineering construction safety management system based on multiple sensors. By monitoring the relative deviation distance and direction of the gravity center point, the transfer speed and direction of the gravity center point, the inclination angle and direction of the body and the number and the supporting area of supporting framework joint points corresponding to various postures of the overhead working personnel in the electric power engineering construction process, the falling risk of the overhead working personnel is recognized; monitoring the distance between each easily-impacted part of the body of the aerial working personnel and an object adjacent to the part and the activity coefficient of the object adjacent to each easily-impacted part in the electric power engineering construction process, and identifying the collision risk of the aerial working personnel; the distance between high-altitude operation personnel and all surrounding electrified bodies in the electric power engineering construction process is monitored, the electric shock risk of the high-altitude operation personnel is recognized, recognition and evaluation of various safety risks of the high-altitude operation personnel in the electric power engineering construction process are achieved, and personnel safety is guaranteed.

The invention relates to the technical field of intelligent logistics and unmanned shipping, in particular to an unmanned shipping system based on intelligent weighing, which comprises a multi-modal data acquisition module, a distributed weighing and dynamic optimization module, a loading execution module, a detection and verification module and an electronic shipping order generation module. The system calculates the loading sequence and path of goods through a dynamic loading optimization model, and monitors the gravity center change and load distribution of the vehicle by using an inertial sensor and a piezoelectric sensor to realize real-time adjustment and optimization; through the combination of an electronic shipping order and a digital twin entity, the system supports whole-process state tracking and abnormal early warning, and the transportation safety and the management efficiency are ensured; according to the invention, the intelligence and efficiency of logistics operation are obviously improved, and comprehensive technical support is provided for modern logistics and factory dispatching.

The invention discloses a high-speed turntable variable load adaptive control method, which is based on a closed-loop control mode, realizes adaptive regulation and control of a microprocessor on the rotating speed and the position of a servo motor by combining a fuzzy PID (Proportion Integration Differentiation) control algorithm, reduces the regulation response time and errors of a high-speed turntable, and improves the operation stability of a turntable system. The rotation angle of the high-speed rotary table is fed back to a microprocessor by a displacement sensor to form a closed-loop control system, and an improved gravity center Lagrange interpolation-Fourier harmonic synthesis displacement sensor error compensation model is established, so that the high-speed rotary table can still obtain a high-precision displacement measurement result in a variable-load processing working environment; a software operating system is designed to control and realize multi-task operation such as start-stop, initialization, instruction import and the like of the turntable, and the real-time performance and the detectability of the high-speed turntable system are improved. The method can be used for self-adaptive control under the condition of a variable-load high-speed turntable, and has the characteristics of high precision, fast response and good robustness.

The disclosure relates to the technical field of anti-icing and de-icing of an overhead transmission line or a railway contact system, and provides a mechanical anti-icing and de-icing device fixedly installed on the overhead transmission line or the railway contact system. The device comprises a base, an electric driving assembly, a weight block and a potential energy module comprising an elastic element. The electric driving assembly comprises a clutch mechanism and a motor. When the clutch mechanism is in an engaging state, the electric driving assembly drives the weight block to generate displacement relative to the base, and when the clutch mechanism is in a separation state, the electric driving assembly cuts off driving to the weight block. When the clutch mechanism is engaged, the potential energy module is used for accumulating potential energy when the weight block generates displacement relative to the base; and when the clutch mechanism is separated, a driving force of the electric driving assembly on the weight block is cut off, the potential energy contained in the potential energy module is rapidly released, so that the weight block moves quickly, thus causing the whole gravity center of the device to suddenly change, forming vibration to be transmitted to the overhead transmission line, so that the icing is removed.

The invention discloses a GPU-based parallel tetrahedral mesh generation method and an aircraft profile design method. At present, rapid generation of a large-scale tetrahedral mesh with reliable quality is still an open problem. The invention designs a block-based GPU tetrahedral mesh data structure, and realizes an efficient parallel tetrahedral mesh generation method based on the data structure. The method comprises the following steps: firstly, calculating the gravity center of a tetrahedron and carrying out size inspection, if the size requirement is not met, carrying out multi-round iterative cavity growth by taking the tetrahedron as a starting point, then selecting independent cavities of which the boundaries are not overlapped through a dyeing algorithm, and repairing the cavities through multi-round iteration. And finally, cavity reconnection is carried out, and topological information and neighbor information of the grid are updated. And the steps are repeatedly executed until all tetrahedrons meet the size requirements, so that the large-scale tetrahedral mesh with reliable quality is quickly generated, and the time required for optimizing the shape design of the aircraft is greatly shortened.

The invention relates to an amphibious vehicle path planning method and system based on fuzzy logic rules and reinforcement learning. The planning method comprises the following steps: collecting scene parameters by using a sensor according to an application scene of the amphibious vehicle, and taking the scene parameters as input parameters; performing fuzzification processing on the input parameters, performing reasoning by using a fuzzy rule base to obtain fuzzy output, and performing output defuzzification on the fuzzy output by using a gravity center method; defining a state space and an action space, resetting an environment, executing an action and calculating a reward, and finishing the step when a turn ending condition is met; an Actor-Critic neural network is initialized, and stable learning of a strategy is realized through experience playback and an updating mechanism of a target network; and training and optimizing the Actor-Critic neural network to obtain an optimal path planning strategy. According to the amphibious vehicle path planning method based on the fuzzy logic rule in combination with reinforcement learning, efficient solution of a path planning problem in a complex environment is realized through combination of a fuzzy logic system and a reinforcement learning algorithm, and the amphibious vehicle path planning method has a wide application prospect.

The invention discloses a superconductive synchronous phase modifier rotor adaptive dynamic balance compensation device and method, and relates to the technical field of superconductive synchronous phase modifiers, the superconductive synchronous phase modifier rotor adaptive dynamic balance compensation device comprises a rotor, the rotor is fixedly connected with a rotating shaft, and a plurality of vibration signal capture sensors are uniformly distributed on the side surface of the rotor and used for monitoring the vibration condition of each point in the circumferential direction of the rotor in real time; a gravity center compensation mechanism is further installed on the side face of the rotor and used for correcting the dynamic unbalance situation generated in the rotating process of the rotor in real time. When a certain vibration signal capture sensor on a rotor monitors that a dynamic unbalance condition occurs at a corresponding point, a sealing push plate in a balance box body at a corresponding position pushes out balance liquid stored in the balance box body through a communicating pipe, and the sealing push plates in the oppositely arranged balance box bodies move to a position far away from the communicating pipe; and the spaces, communicated with the communicating pipes, in the opposite balancing box bodies are filled with the pushed balancing liquid, so that the adjustment and compensation of the gravity center distribution of the rotor are completed.