1282 results about "Angular velocity" patented technology

An electric power assisted steering assembly comprises a steering mechanism which operatively connects a steering wheel to the roadwheels of a vehicle, a torque sensing means adapted to produce a first output signal indicative of the torque carried by a portion of the steering mechanism, a means for producing a second output signal indicative from a signal indicative of the angular velocity of the portion of the steering mechanism, an electric motor operatively connected to the steering mechanism, a signal processing unit adapted to receive the two output signals and to produce therefrom an overall torque demand signal representative of a torque to be applied to the steering mechanism by the motor, and a motor drive stage adapted to provide a drive current to the motor responsive to the torque demand signal. The overall torque demand signal includes a damping component that is dependent upon the second output signal. The means for producing the yaw damping component includes a filter having one pole and one zero, and in use the second signal is passed through the filter to produce the damping component, the frequency of the pole and zero being selected such that the filter provides a band between the pole and zero within which the phase of the filtered second signal and the velocity signal are further out of phase or in phase than within the band.

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 camera anti-shake, and discloses a motion camera anti-shake method and system based on inertial prediction, and the method comprises the steps: collecting the three-axis acceleration original data of an IMU sensor in a motion camera, and calculating a first motion intensity value; when the first motion intensity value is smaller than an acceleration change rate threshold value, starting a first anti-shake mode, and extracting angular velocity data of the gyroscope; performing cubic spline interpolation curve fitting and time domain extrapolation prediction on the angular velocity data of the gyroscope to obtain a three-axis angular displacement predicted value and generate a first lens compensation driving signal in a first anti-shake mode; continuously monitoring the motion camera, switching to a second anti-shake mode when a second motion intensity value exceeds the acceleration change rate threshold value, acquiring three-axis acceleration sudden change data, and generating a second lens compensation driving signal in the second anti-shake mode, compared with a traditional single-mode anti-shake method, the method improves the adaptability and compensation precision in a complex motion environment.

The invention relates to the technical field of underwater navigation, and discloses a real-time attitude estimation method of an underwater inertial navigation system. The method comprises the steps that the underwater vehicle collects multi-axis angular velocity and linear acceleration data through an inertial measurement unit and uploads the data to a central processing module, and the central processing module conducts kinematics modeling on the data to generate attitude change initial feature vectors; receiving water flow velocity data of a Doppler velocimeter and pressure data of a depth sensor, and performing flow field interference compensation optimization on the attitude change initial feature vector based on the data to generate an anti-interference attitude feature vector; fusing the anti-interference attitude feature vector and a historical attitude estimation result to generate space-time fusion attitude state representation, and then resolving a real-time Euler angle through a nonlinear filter; and matching a corresponding attitude stability control instruction from the navigation strategy library according to the real-time Euler angle, and issuing the attitude stability control instruction to a propeller execution unit. The method can effectively cope with underwater complex environment interference and guarantee stable operation of the underwater vehicle.

A method for simultaneous localization and mapping underwater. A robot is equipped with an IMU inertial unit and a sonar unit. When the robot submerges underwater, a buoy connected to the robot floats on the water surface, and the buoy moves in coordination with the movement of the robot. The position and observed velocity of the buoy are obtained by a shore-based lidar. During motion estimation in a SLAM algorithm, when an angular velocity is below a preset angular velocity threshold, the observed velocity of the buoy is decomposed into x-axis velocity and y-axis velocity, and updated as the two-dimensional operating velocity of the robot. The polar coordinates of an obstacle in a map under the coordinate system of the robot are associated with the polar coordinates of sonar data of a current frame by using the Mahalanobis distance. The polar coordinates of a new obstacle are converted to the world coordinate system and added to the map. The present invention has the advantages of not relying on underwater visibility, not requiring pre-installed devices, and possessing good generalization and stability.

The invention relates to the technical field of shot action recognition, and discloses a shot throwing action recognition method based on a single attitude sensor. The method comprises the following steps: acquiring a single attitude sensor original data stream in a shot throwing process, and extracting a three-axis acceleration sequence and a three-axis angular velocity sequence from the single attitude sensor original data stream; performing motion event segmentation processing on the two sequences, and generating a key action time period mark set comprising a preparation stage, a sliding step stage, a power generation stage and a release stage; based on the mark set, calling an attitude feature solution algorithm to perform spatial trajectory reconstruction on the original data stream to obtain a key attitude frame set containing a joint angle change curve and a centroid displacement trajectory; and inputting the key attitude frame set into an action recognition model for attitude mode matching, and outputting a shot throwing action classification result which comprises an action deviation parameter generated based on a standard action template library and a key frame correction identifier. According to the method, key attitude information is reconstructed, and support is provided for shot throwing action analysis and improvement.

The invention relates to a course axis drift suppression method and device, a holder and a medium, and the method comprises the steps: receiving original data of a current course, the original data comprising an absolute angle outputted by a course encoder, and an acceleration and an angular velocity outputted by an IMU module; the original data are converted into a unified coordinate system through a rotation matrix, and mechanical installation deviation is compensated; performing data fusion on the compensated original data through a preset fusion algorithm; and outputting the fused absolute angle to a servo mechanism of the holder, and by adopting the method, through real-time sensor data alignment, a dynamic compensation algorithm and a fusion algorithm, a course drift suppression mechanism which is resistant to dynamic interference and low in cost is constructed, and static drift lt can be realized; the dynamic tracking error is 1t, 0.01 degree / h and 1t; and the technical index is 0.05 degree.

The invention relates to the technical field of numerical control programming, in particular to a five-axis machining path planning method and system based on data driving, and the method comprises the following steps: obtaining real-time coordinates of each axis of a machine tool, calculating linear velocity and angular velocity components to construct a Jacobian matrix, executing singular value decomposition, and calculating a conditional number ratio by using maximum and minimum singular values; and inputting a nonlinear mapping function to calculate a dynamic penalty factor, generating a rotating shaft weighted item in combination with a rotating shaft identifier, constructing a weighted damping least square objective function, calculating a five-axis motion increment, and accumulating the five-axis motion increment with a real-time coordinate to generate a target absolute position coordinate. According to the method, the pose singularity degree is quantified by monitoring the machine tool pose condition number ratio and converted into the dynamic penalty factor to apply the self-adaptive constraint to the rotating shaft, the severe sudden change of the rotating shaft in the singularity area is inhibited, the tool nose track following error is minimized, and meanwhile smooth distribution of the motion increment is achieved; and the dynamic stability and the surface quality of five-axis linkage machining are improved.

The invention discloses a steering engine accurate control method and system based on an optimization control algorithm, and the system comprises a data collection module which collects key working parameters of a steering engine in real time through a plurality of sensors, and carries out the data processing, thereby forming a state vector; the self-adaptive filtering module is used for carrying out self-adaptive filtering fusion processing on the data acquired by the sensor and dynamically estimating the attitude angle and the corresponding angular velocity of the aircraft; the sliding mode control module constructs a sliding mode surface and a control rate of a steering engine system according to the dynamic error of the system, calculates control input of each axis of the aircraft according to the attitude angle real-time state error, and generates a sliding mode control signal; the driving execution module is used for converting the control signal into a voltage or PWM signal and inputting the voltage or PWM signal into a steering engine, so as to change thrust and realize adjustment and control of a posture or a position; and the real-time feedback module monitors the current state of the steering engine in real time to realize dynamic correction and real-time optimization. The adaptive filtering and sliding mode control method provided by the invention is higher in control precision, quicker in system response and higher in adaptability to complex environments, and can effectively improve the application performance and stability of a steering engine execution system in the fields of industrial automation, aerospace, intelligent manufacturing and the like.

The invention provides an attitude monitoring method and system in navigation of an aircraft, and the method comprises the steps: determining a process noise covariance matrix through a high-frequency energy component of an angular velocity signal measured by a current gyroscope in each filtering period; predicting a prior state vector and a prior covariance matrix at the current moment according to the state vector at the previous moment, the angular velocity measured by the current gyroscope and the process noise covariance matrix; generating an asymmetric Sigma point set and determining a measurement noise covariance matrix; the asymmetric Sigma point set is substituted into a measurement model, and a predicted measurement value and a predicted measurement covariance are obtained through unscented transformation; calculating Kalman gain based on the predicted measurement covariance and the measurement noise covariance matrix, and performing weighted gating test on innovation formed by a real measurement value and a predicted measurement value; and updating a state vector and a covariance matrix on the basis of the adjusted Kalman gain and information so as to obtain attitude information of the aircraft at the current moment.

A motion state observation method for autonomous navigation of a ship. The method uses a determination method for system matrixes Ad, Bd, Ed and Hd, and a determination method for a related measurement covariance matrix R and noise covariance matrix Q, and uses a discrete Kalman filtering algorithm to perform motion state observation and prediction for autonomous navigation of a smart ship. The method fully uses ship position and heading measurement information of a smart ship during autonomous navigation, uses a ship motion model and the discrete Kalman filtering algorithm, and selects an effective state observation variable, thus calculating reasonable and effective observer parameters. The state observation method can effectively calculate information such as the actual position, heading, speed and angular velocity of a smart ship at each time instant during autonomous navigation, and predict motion information at a next time instant, thus helping to reduce the difficulty of smart ship motion controller design, ensuring effective implementation of navigation control strategies, reducing ineffective thrust output and rotation of propulsion systems, and improving the autonomous navigation capability of smart ships.

The invention relates to the technical field of man-machine interaction, in particular to a multi-user-based ring pairing and left and right hand judgment method and system and a medium, and the method comprises the steps: firstly collecting azimuth angles, distances and historical tracks of a plurality of rings, and clustering the azimuth angles, the distances and the historical tracks into different user clusters; shoulder breadth geometric constraint, posture consistency, micro-motion synchronism and historical prior are fused in the cluster, paired scores are calculated, and paired rings are identified by using a greedy strategy; and then, calculating a judgment score to distinguish the left hand and the right hand by counting the rotation deviation of the angular velocity of the gyroscope on the horizontal plane projection and combining the spatial position score of the ring relative to the human body center line with the historical consistency. A steady-state mode and an event-driven wake-up mechanism are also introduced to balance power consumption. According to the invention, through multi-modal fusion, automatic ring pairing and accurate left and right hand judgment are realized.

The invention provides a real-time calibration method and system for an inertial measurement unit, and a terminal, and the method comprises the steps: carrying out the first correction of an acceleration measurement value and an angular velocity measurement value which are output by a to-be-calibrated inertial measurement unit and are obtained in real time based on a temperature error compensation data table, and carrying out the second correction through employing a multi-sensor fusion filtering algorithm; on one hand, a temperature variable is introduced to carry out a multi-temperature zero offset test and a multi-temperature multi-axis rotation excitation test, a temperature error compensation data table is established, and the influence of temperature on the performance of the to-be-calibrated inertial measurement unit is fully considered; on the other hand, a multi-sensor fusion filtering algorithm is adopted, interference of vibration noise can be suppressed, the attitude calculation precision of the to-be-calibrated inertial measurement unit is improved, and therefore the calibration precision of the to-be-calibrated inertial measurement unit is guaranteed; the technical problems that an existing inertial measurement unit calibration method is low in calibration precision and poor in real-time performance are solved.

The invention provides a low-power-consumption control method of a GPS module. Through data fusion of the gyroscope and the GPS, accurate perception of the motion state of the equipment is realized, and in combination with a dynamic frequency modulation technology and hardware-level power supply control, the power consumption of the system is remarkably reduced on the premise of ensuring the positioning accuracy and the real-time performance. The angular velocity change of the equipment is detected in real time through the gyroscope, and in combination with GPS position information, the equipment is judged to be in a moving, low-speed moving or static state. And dynamically adjusting the GPS sampling period according to the state division result. A sliding window algorithm is adopted to smooth rate fluctuation, a multi-threshold hysteresis mechanism is combined to avoid state misjudgment, a mathematical optimization model is constructed to carry out iterative optimization on control parameters, and balance between power consumption and performance is achieved. Through hardware-level power supply control, zero power consumption in a static state is realized, the average power consumption of the GPS module can be greatly reduced in long-endurance demand scenes such as Internet of Things equipment, wearable equipment, field animal research and the like, and meanwhile, relatively high positioning precision is maintained.

The invention discloses a pipeline robot positioning method, system and device based on an odometer wheel and an IMU and a medium, and relates to the technical field of robot positioning and pipeline detection. The method comprises the following steps: determining an initial attitude angle of the pipeline robot in a static state according to acceleration data and magnetic force data collected by an IMU (Inertial Measurement Unit); based on a compensated angular velocity obtained by denoising angular velocity data collected by an IMU by using a complementary filtering algorithm, updating an initial attitude angle by using an Euler angle method to obtain an attitude angle matrix, and performing optimal estimation by using a nonlinear state estimation algorithm; performing consistency verification on the pulse data of the plurality of odometer wheels, determining corresponding effective pulse data through weighted correction, and then determining a mileage increment; and based on the optimized attitude angle matrix, the mileage increment is projected to a navigation coordinate system so as to solve the real-time position coordinate of the pipeline robot. The problems that the pipeline robot is poor in trafficability and low in positioning precision when facing a complex pipe network can be solved.

The invention provides an MEMS inertial three-dimensional displacement monitoring method and system, and relates to the technical field of MEMS sensors, and the method comprises the steps: obtaining acceleration and angular velocity signals of an inertial measurement unit, and generating a dynamic acceleration after attitude calculation, error compensation and gravity removal; updating a group of state variables containing position and speed information in real time through integral operation so as to obtain continuous first displacement information with drifting; under a preset condition, measuring the absolute position of the object by using an external acoustic positioning system so as to obtain accurate and drifting-free second displacement information; the state variable is corrected by a fusion process using a deviation between the first and second displacement information, and position information is extracted from the corrected state variable as a final output. The advantages of inertial measurement and external positioning are combined, integral drift is effectively inhibited, and the precision and reliability of long-term monitoring are remarkably improved.

The invention discloses a pouring machine flow control system based on multi-parameter feedback and PID dynamic adjustment, and relates to the technical field of automatic control of mold pouring, the system comprises a tilting parameter module, a liquid level dynamic modeling module, a flow adaptive control module and an execution mechanism module; the tilting parameter module collects the angular velocity and angle data of a casting ladle in real time, the liquid level dynamic modeling module calculates the liquid level height according to the angular velocity, the angle data and the geometrical shape of the casting ladle, and the flow self-adaptive control module dynamically calculates the current flow value. And the preset flow target and the real-time flow difference value are input into a PID controller to generate a tilting adjustment signal to drive an execution mechanism module to adjust the flow of the casting machine. The liquid level height and the flow are calculated through mechanical motion parameters, the problem that the sensor is in direct contact with liquid in the high-temperature and high-pressure environment and fails is solved, and stable operation in the severe environment is guaranteed; and adaptive PID control and a multi-parameter fusion model are used for cooperative work, so that the steady-state error is reduced, and the response speed is increased.

The invention discloses a cylindrical roller trajectory tracking method and device, and the cylindrical roller trajectory tracking method comprises the following steps: obtaining an actual measurement displacement sequence of a key point on the end surface of a roller under a global coordinate system based on a multi-reference matching digital image correlation method; drawing a key point displacement curve about key points and time according to the actually measured displacement sequence; judging the motion state of a roller according to the shape characteristics of the key point displacement curve, dividing a smooth part in the key point displacement curve into a rolling area, and dividing a part with jumping or sharp points into a sliding area; calculating the actual revolution angular velocity and the actual rotation angular velocity of the roller based on the actually measured displacement sequence corresponding to the sliding area; according to the method and the device, the image matching precision can be improved, meanwhile, the rolling and sliding components of the roller are accurately distinguished, the precision of the track of the cylindrical roller is improved, and high-precision and visual experimental data are provided for existing dynamics and tribology models.

The invention discloses an active stabilization device for a floating type platform and a floating type wind power platform. The active stabilization device for the floating type platform comprises a semi-submersible platform; the adjusting assembly comprises a controller and a sensor, the sensor is arranged on the semi-submersible platform to detect angular velocity information, and the sensor is in communication connection with the controller; the counterweight assemblies are arranged in the circumferential direction of the semi-submerged platform and comprise first driving assemblies, guiding assemblies and balancing weights, and the guiding assemblies are located on the same plane and surround the semi-submerged platform; the first driving assembly is in communication connection with the controller and can drive the balancing weight to be adjusted on the guiding assembly. The controller receives the angular velocity information detected by the sensor to obtain the real-time inclination angle of the semi-submerged platform, and the first driving assembly is adjusted to directly drive the balancing weight to move on the guiding assembly, so that the position distribution of the balancing weight on the semi-submerged platform is changed, and the gravity center distribution of the semi-submerged platform is adjusted; therefore, the swinging trend of the semi-submersible platform is resisted, and the effect of quick stabilization is achieved.

A heat balance optimal satellite sun orientation control method comprises the following steps: firstly, determining sun orientation target parameters according to a sun vector direction calculated by an orbit, using preset sun orientation target parameters when regular preset parameters are set, and then calculating a sun orientation target attitude angle and angular velocity by using a formula provided by the method, and finally, the sun orientation of the satellite to the target attitude angle and angular velocity is realized according to the measurement of the terahertz gyroscope and the plane control of the jet phase.

The invention belongs to the technical field of mechanical arm control, relates to a bionic mechanical arm elbow joint adjusting angular velocity control method, and solves the problem that an existing method is difficult to meet the collaborative requirements of smooth starting, smooth transition and quick response in bionic actions. Acquiring starting and target positions to generate a motion trail; deducing an expected angle sequence based on forward and reverse kinematics, calculating a target angular velocity, and collecting current angle and angular velocity information in real time; an angle error signal is constructed, an angular velocity control instruction is generated by using a position type PID controller, and PID parameters are dynamically set through an improved algorithm based on state optimization; and a control instruction is input into the elbow joint driving unit, and dynamic adjustment and closed-loop control of the angular speed are achieved. The effect of the method is verified through experiments, and the experiments prove that the precision, robustness and dynamic response capability of angular velocity control of the bionic mechanical arm can be remarkably improved through the method.

The invention discloses a forking operation track generation method and device for a forklift, and the method comprises the steps: determining the pose of a target tray when the distance between the forklift and the target tray reaches a first distance; according to the target tray pose, the current fork tooth pose and the forking environment illumination intensity, the first pose deviation between the target tray and fork teeth is determined, and a first forklift linear speed and angular speed instruction is obtained through calculation; in the process that the forklift travels to the second distance, the ground friction coefficient and the vibration compensation amount are determined according to the friction-vibration joint estimation model and the first forklift linear speed and the first forklift angular speed; when the second distance is reached, determining a second pose deviation between the target tray and the prongs; and simulating the obtained parameters to obtain a second linear velocity and angular velocity instruction so as to complete the forking operation. Through rough adjustment and fine adjustment of the two distances, high-precision track planning of the forklift is achieved, and through calculation of the ground friction coefficient and the vibration compensation amount, the curve insertion precision of the tray is further improved.

The invention belongs to the technical field of wind driven generator state monitoring, and discloses a millimeter wave and vision fused fan blade clearance monitoring system, which comprises a central processing unit, a wind driven generator, a millimeter wave radar sensor, a millimeter wave radar sensor and a millimeter wave radar sensor, and is characterized in that the central processing unit establishes a reference time difference according to blade transit timestamps acquired by the vision and millimeter wave radar sensor; during operation, a blade instantaneous angular velocity is determined by using visual data so as to correct a real-time timestamp, a comparison result of a dynamic time difference and a reference is calculated and is used as an initial diagnosis signal, and risk levels are discriminated by analyzing Doppler spectrum width characteristics of radar echoes in case of abnormality. According to the method, the fan master control system has the capability of distinguishing and recognizing the individual state abnormity of the single blade for the first time, the monitoring granularity is lowered to the component level from the complete machine level, and the improvement from passive response type control to predictive adaptability control is achieved.

An attitude control method for a spin detection satellite, which method belongs to the field of satellite attitude control. The method comprises: S10, establishing a satellite dynamic equation and converting same into a state-space equation; S20, designing a two-layer linear extended state observer, wherein the first-layer linear state observer is used for observing and acquiring a current angular velocity estimate and a current disturbance estimate of a satellite, and the second-layer state observer observes a tracking error of the first-layer linear state observer on the basis of the observation result of the first-layer linear state observer; and S30, then performing calculation on the basis of the current disturbance estimate and the tracking error thereof, so as to obtain the total internal and external disturbance torque estimate of the satellite, using attitude parameters representing the direction of a spin axis to design a PD control law, and compensating for the total internal and external disturbance torque estimate of the satellite, so as to calculate a control torque, which is used for satellite attitude control within a current cycle. The method has the advantages of fewer tuning parameters, ease of adjustment and stable performance, thereby greatly improving the observation precision.

The invention belongs to the technical field of ship course control, and discloses an unmanned sailboat sail-rudder cooperative active-disturbance-rejection course control method based on ESO, and the method comprises the following steps: building a nonlinear course motion mathematical model; designing a self-adaptive tracking differentiator to smooth the expected course; the course, the yawing angular velocity, the sail aerodynamic moment and the comprehensive disturbance are observed in real time through ESO; based on a nonlinear state error feedback control law, in combination with the output of the tracking differentiator and the observed value of the ESO, generating a rudder torque control quantity, performing constraint processing on the rudder torque control quantity, and outputting a rudder angle instruction; and a dynamic optimal sail angle is decided according to the lift-drag ratio parameter, the apparent wind speed and the relative wind angle of the sail aerodynamic model corrected in real time, and a sail angle instruction is generated after the dynamic optimal sail angle is compensated and constrained by combining the course deviation. The adaptive capacity to the time-varying wind field and the model uncertainty is enhanced, and the anti-interference performance and the energy efficiency of the system are improved through dynamic optimization and compensation of the sail angle.

The invention relates to a pan-tilt angle calculation method and device, an electronic device and a storage medium, and the method comprises the steps: obtaining initial gravitational acceleration data and initial angular velocity data, determining reconstructed gravitational acceleration data according to the initial gravitational acceleration data and the initial angular velocity data, and calculating the angle of a pan-tilt according to the reconstructed gravitational acceleration data; and determining an observation model according to the initial gravitational acceleration data, determining real gravitational acceleration data according to the reconstructed gravitational acceleration data and the observation model, obtaining a carrier coordinate gravitational acceleration, and determining a cradle head attitude angle according to the carrier coordinate gravitational acceleration and the real gravitational acceleration data. According to the method and the device, the problem of how to accurately calculate the attitude angle of the unmanned aerial vehicle holder is solved, noise interference is reduced, the real gravitational acceleration is restored, and the stability augmentation control capability of the holder is effectively improved.

This invention discloses a deep reinforcement learning guidance method based on the TD3 algorithm. It includes the following steps: (1) establishing a relative motion model between the missile and the target; (2) designing a Markov decision process; (3) constructing a network model for the deep reinforcement learning guidance method; training the constructed model offline, and then using the trained network model to output the normal acceleration; designing a Markov decision process, using the line-of-sight angular velocity as the state space and the normal acceleration as the action space, and then using the deterministic policy gradient principle to find the optimal neural network parameters, and then using the trained neural parameters to achieve a direct mapping from the line-of-sight angular velocity to the normal acceleration.

The invention relates to the technical field of trajectory measurement, discloses an underwater riprap particle motion trajectory measurement device and method, and aims to realize high-precision response tracking of stress and motion trajectory of riprap particles around a foundation under dynamic water scouring based on an underwater positioning unit sensing array and a high-frequency sampling particle motion and attitude detection technology. The technical problem that the motion characteristics of a single riprap particle cannot be observed in previous riprap protection research is solved. Through combined measurement of acceleration and angular velocity data collected by the inertial measurement unit and absolute position measured by the radio frequency unit, the three-dimensional motion condition, track and attitude process of a unit space as well as two-dimensional displacement images of a riprap surface and a vertical flow section are accurately reconstructed; and a centimeter-level-precision visual data support and a low-cost research means are provided for foundation scouring and coastal slope protection and riprap protection research, so that the engineering cost is saved.

The invention belongs to the field of wind tunnel experiments in a hypersonic flow field environment, and discloses a multi-degree-of-freedom high-frequency motion simulation device for an aircraft dynamic stability test and a calculation method for realizing an actuation angle. According to the technical method, calculation is carried out on the basis of an electromechanical coupling equation, determined by electrical parameters and mechanical parameters, of a piezoelectric material. Modeling can be carried out according to a piezoelectric equation to obtain a calculation method between the voltage applied by the piezoelectric actuator and the pitching and yawing actuation angles of the device, so that the excitation effect of the device in the ground test process can be accurately controlled and predicted. The method is not only suitable for pitching and yawing two-degree-of-freedom actuation calculation, but also can be used for calculating the actuation angle of a three-axis degree-of-freedom experimental device added with rolling drive through coordinate transformation under the condition of adding parameters such as rolling angular velocity and the like in the face of the three-axis degree-of-freedom experimental device added with rolling drive. At present, according to a calculation method based on the device, calculation is carried out only by considering the degree of freedom of the pitching axis and the yawing axis.

The invention discloses a high-voltage vacuum circuit breaker contact motion detection method and system based on an inversion model, and the method comprises the steps: firstly designing a dual-position speed sensor collection unit for collecting speed signals of different positions and different characteristics, and achieving the mutual triggering; based on an inversion model, a programmable logic component and a CPU are adopted for result operation and logic inversion and correction, a rotation angular velocity curve is obtained, and the accurate motion state is obtained through comparison; according to the method, the stroke characteristic curve in the arc extinguish chamber of the high-voltage vacuum circuit breaker can be accurately reflected, mutual conversion of angular velocity and linear velocity at different positions can be realized based on the thought of an inversion model, and finally effective data which can be analyzed and judged can be output for system application.