5047 results about "Gyroscope" patented technology

The invention provides a brushless motor attitude detection and balance control method and system based on a gyroscope, and relates to the technical field of control, and the method comprises the steps: collecting angular velocity and acceleration data through a six-axis gyroscope, carrying out the noise reduction through wavelet transform, and carrying out the attitude calculation through the combination of an extended Kalman filter and a quaternion algorithm. A rotor position signal is obtained through a magnetic encoder, nonlinear compensation is carried out, and rotating speed data are calculated. A motor state is modeled by adopting a long-short-term memory network, a double-layer adaptive fuzzy neural network controller is constructed, and attitude error compensation and rotation speed fluctuation suppression are realized. A controller model is optimized through particle swarm optimization and a genetic algorithm, a compensation current vector is corrected in real time, and the control precision and stability of the brushless motor are improved. According to the method, the operation efficiency and the dynamic response capability of the brushless motor are effectively improved.

The invention relates to a dynamic adjust gyroscope life forecasting method based on gray model. By data collection of vibration effective value, random drift and environmental temperature parameter which are preprocessed using radial neural networks, influence of environmental temperature on vibration effective value and random drift is eliminated and random drift and effective value just related to time are obtained by subtracting drift constant value term, then trend term of vibration effective value and random drift are extracted by using wavelet transformation and gray model are built separately for their trend term. The smaller data in two values of life predicted of dynamic adjust gyroscope unless two predicted values exceeding performance parameter limitation when dynamic adjust gyroscope is considered losing effect. The invention uses performance parameter of life probative period of product to predict its life, showing discipline of performance parameter and life of dynamic adjust gyroscope. It is easy and convenient economical and reliable.

The invention relates to the technical field of aviation communication, and discloses a true north calibration system and method for an aviation airborne laser communication equipment alignment system, and the method comprises the steps: synchronously collecting flight data through an IMU sensor and a double-antenna GPS at a preset sampling frequency, and outputting the real-time attitude angle information of an aircraft through an IMU; filtering and de-noising the synchronously acquired IMU and double-antenna GPS data, and carrying out noise suppression and deviation compensation on accelerometer and gyroscope data output by the IMU by adopting a Kalman filtering algorithm; based on the preprocessed sensor data, calculating an initial course angle by measuring relative position change and phase difference between antennas by using a double-antenna GPS (Global Positioning System); the calibration controller transmits the calculated true north direction information to an alignment system of the laser communication equipment in real time through a communication interface; and the attitude change and external environment disturbance of the aircraft are continuously monitored in the whole flight process. The method has the advantage that the alignment performance and the communication stability of the laser communication equipment are improved.

The invention discloses a modular collaborative layout method for gyroscopes and accelerometers, relates to the technical field of inertial sensing, and solves the problem of accumulative errors of gyroscope drift and accelerometer zero offset drift in a complex geological environment under a mine, and by calculating a drift change rate Cpj and a zero offset change rate Azp in real time and executing error compensation, the gyroscope drift rate Cpj and the accelerometer zero offset change rate Azp are calculated in real time, and the accelerometer drift rate Cpj and the accelerometer zero offset change rate Azp are calculated in real time. The positioning and path tracking precision of the equipment under the condition of no GPS is improved; meanwhile, aiming at external interference factors such as vibration, noise and air flow in the mine, a data fusion strategy is adjusted in real time by calculating a dynamic interference adaptation index Xw and comparing the dynamic interference adaptation index Xw with a threshold value, and the influence of interference on attitude estimation is effectively reduced; besides, according to the scheme, sensor data are dynamically adjusted through a temperature compensation and humidity correction mechanism, the influence of temperature and humidity changes on the gyroscope and the accelerometer is compensated, the stability and precision of the system in the extreme environment are ensured, and the adaptability and reliability of the mine environment are enhanced.

The invention discloses a comprehensive performance prediction and structural parameter optimization method for a hemispherical resonator, and belongs to the technical field of aerospace inertia. According to the method, a high-precision finite element simulation model of the ideal hemispherical harmonic oscillator is established based on a multi-region grid uniform division method; aiming at the condition that each structure parameter corresponds to different structure sizes, calculating through a finite element model of a control variable to obtain a data set of different performance parameters of the hemispherical resonator; based on a BP neural network algorithm optimized by a particle swarm optimization algorithm, after the data set is divided into a training set and a test set, a comprehensive performance parameter prediction model of the hemispherical harmonic oscillator is established; and taking the PSO-BP neural network model as the input of a second-generation non-dominated sorting genetic algorithm, and performing multi-objective optimization on the structural parameters of the hemispherical harmonic oscillator by taking higher thermoelastic damping and larger minimum frequency difference between the interference modal and the PSO-BP neural network model as optimization objectives. The use performance of the hemispherical resonator is improved, and the performance requirement of the aerospace technology field on the high precision of the hemispherical resonator gyroscope is met.

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 discloses a transformer substation inspection robot positioning and mapping method based on point-line feature fusion. According to the method, a binocular camera is used for collecting point-line features in an image frame, and high-quality long-line features are quickly obtained based on an adaptive criterion optimized EDLines algorithm; the spatial depth of point-line features is obtained through triangularization of a binocular camera, and redundant line features are filtered based on a length response threshold strategy of the spatial depth of a transformer substation. Based on a point-line pole feature pole plane constraint method, IMU information and visual information are combined, gyroscope zero offset is independently estimated and optimized, IMU pre-integration information is updated, and a more accurate initial posture of the inspection robot is obtained. A point-line feature dictionary based on a transformer substation scene and a large-scale equipment target detection model in a transformer substation are made, closed-loop detection is performed through transformer substation equipment road signs and point-line features, and rapid relocation correction is performed on sliding windows of a current key frame and a previous fixed key frame number. And finally, the pose of the substation inspection robot and a substation scene map are optimized through global BA, and the problem of large-scale scene error drift accumulation is solved.

The invention discloses a ship inclination measurement method and system based on Kalman filtering fusion, and relates to the technical field of ship stability measurement, and the method comprises the steps: multi-sensor synchronous data collection, state space modeling and Kalman filtering fusion, adaptive dynamic adjustment of process noise, drift compensation, and fault tolerance and output. When the method and the system provided by the invention are used for measuring inclination, inclination angle error accumulation caused by gyroscope zero offset integral error, accelerometer dynamic interference, sensor noise and temperature drift, GNSS dependency and the like can be effectively avoided, available precision can still be maintained through multi-sensor depth coupling and an intelligent filtering algorithm, and the accuracy of inclination measurement is improved. The method is simple in operation, independent of satellite data, higher in stability, capable of greatly reducing hardware cost compared with GNSS and IMU schemes, and especially has the advantages of being simple in cost and installation configuration in ship refitting; and the method is also suitable for GNSS rejection or cost sensitive scenes such as inland ships, unmanned ships, offshore buoys and the like.

The invention provides a fiber-optic gyroscope drift compensation method and system fused with LMS self-adaptive filtering, and relates to the technical field of LMS self-adaptive filtering, the method comprises the following steps: synchronously collecting multi-point temperature data, temperature change rate, axial and radial gradient information and original output signals of a gyroscope shell, and calculating the multi-point temperature data, the temperature change rate, the axial and radial gradient information and the original output signals of the gyroscope shell; the original signal is separated into a temperature drift component and a non-temperature noise component through variational mode decomposition, and noise is filtered out; establishing a nonlinear mapping relation by combining the temperature field data and the drift component to generate a drift predicted value, and inputting the predicted value and the residual error of the actual drift component into an LMS adaptive filter for dynamic error compensation; and finally, superposing the compensation result and the predicted value, and outputting a corrected gyro signal. According to the invention, the drift compensation precision and stability of the fiber-optic gyroscope in a complex variable-temperature environment are improved.

The invention discloses a lineation robot control system based on a satellite positioning and orientation technology, which relates to the technical field of robot motion control and comprises a satellite positioning and orientation module, an inertial navigation module, a fusion positioning and orientation software module, a motor control software module, a motion control software module and a pattern planning software module. The satellite positioning and orientation module is used for acquiring latitude and longitude coordinates of the current position of the robot by receiving multi-frequency satellite signals; the inertial navigation module is used for collecting posture and motion data of the robot in real time through a gyroscope and an accelerometer. According to the lineation robot control system provided by the invention, through collaborative design of the multi-frequency-point GNSS receiver and the anti-multipath interference antenna array, centimeter-level continuous positioning capability in a complex urban environment is realized, and satellite signal reflection and shielding interference in scenes such as viaducts and avenues are effectively overcome; and satellite positioning and inertial navigation data are deeply fused through a tight coupling Kalman filtering algorithm.

The invention relates to the technical field of robots, and discloses a multi-source data fusion method of a tracked robot, which realizes dynamic environment adaptation and autonomous decision optimization through a multi-source sensing cooperation mechanism, and comprises the following steps: dynamically adjusting exposure parameters of a visual module based on environment illumination intensity, and avoiding overexposure or underexposure of an image through a feedback adjustment mechanism; fusing data of the accelerometer and the gyroscope to generate attitude angle compensation parameters; the heat dissipation system is intelligently regulated and controlled by comparing infrared thermal imaging and temperature sensor data; dynamic task priority distribution is realized; optimizing an advancing route to reduce complex terrain navigation deviation, in addition, establishing a multi-source sensing coordination mechanism, monitoring health indexes such as motor temperature and vibration frequency in real time, and triggering abnormal state judgment; track optimization is implemented in combination with pavement mechanical characteristics and a kinematic model; and executing the staged energy management strategy. According to the method, the environment sensing precision and the motion control reliability of the tracked robot in a complex environment are remarkably improved.

The invention discloses a high-precision attitude sensor dynamic calibration system and a method thereof, and belongs to the technical field of attitude sensors. The invention discloses a dynamic calibration system and method for a high-precision attitude sensor. The dynamic calibration system comprises a data acquisition unit, a dynamic calibration unit and a calibration execution unit. The problem that the calibration effect is limited in the prior art is solved, the state of the sensor can be known more comprehensively by collecting the output data of the high-precision attitude sensor, the environmental data and the multi-source data of the accelerometer, the gyroscope and the magnetometer in real time, so that more accurate error analysis and calibration are carried out, and the calibration accuracy is improved. Modeling and error analysis are carried out by utilizing a machine learning algorithm, parameters are automatically adjusted through a model adaptive updating mechanism, error analysis can be carried out on data collected in real time so as to provide reference for subsequent dynamic calibration, and dynamic calibration operation of the high-precision attitude sensor is accurately executed according to an analysis result of the model. And high precision and high stability of attitude measurement are ensured.

The invention discloses a robot vision inertial navigation method and device and a storage medium, and belongs to the technical field of mobile robot navigation, and the navigation method comprises the following steps: measuring motion information of a mobile robot by using an IMU sensor; collecting image data of the mobile robot by using a camera; inputting the feature points and the descriptors into a LightGlue network model to obtain a local feature point matching relation of the image; calibrating the offset of the gyroscope by optimizing and recovering visual scale information, and estimating the IMU coordinate system speed, the gravitational acceleration and the offset of the IMU; introducing a visual feature re-projection error, an IMU pre-integration error and marginalized residual constraint, and then integrally converting into a target function to obtain a nonlinear optimization result; further repositioning is carried out to obtain a repositioning result; and optimizing the global pose map to obtain a final global pose map optimization result, and carrying out navigation operation according to the global pose map optimization result. The method can improve the positioning precision and operation efficiency under view angle change and illumination change, and is high in practicality.

The invention relates to the field of cableway transportation safety control, in particular to a cableway lift carriage operation deflection attitude monitoring device and a control method, and the method comprises the steps: collecting the position, speed, attitude angle and local micro deflection disturbance information of a lift carriage in real time by constructing a multi-mode sensing network; the frequency of the sensor is dynamically adjusted by adopting an adaptive sampling mechanism, and space-time alignment and fusion of heterogeneous data are completed in combination with dynamic time warping and minimum mean square estimation; strengthening the key disturbance dimension based on a disturbance-driven attention mechanism, and predicting a future deflection angle sequence; a decoupling torque is generated through spatial deflection vector field modeling, regional coupling tensor analysis and a dynamic direction alignment matrix, and power consumption constraint and a dynamic environment parameter optimization control instruction are fused; and finally, driving the quadrilateral moment gyroscope to execute correction, and constructing a multi-dimensional evaluation index based on the attitude response residual error. According to the method, adaptive closed-loop adjustment of the control strategy is realized, and the robustness under wind speed disturbance and load variation is improved.

The invention discloses a robot unknown environment autonomous exploration navigation method based on CTSAC, and the method combines the powerful sequence perception capability of Transform and a Soft Actor-Critic deep reinforcement learning framework, and introduces curriculum learning of a regular review mechanism, laser radar partition optimization processing, and refined reward setting. The state of the robot is represented by laser radar data and gyroscope data which are subjected to laser radar partition optimization processing, meanwhile, after state information is subjected to refined reward setting, corresponding reward values are obtained, corresponding experience sequences are stored in an experience pool, and data obtained through sampling of the experience pool are supplied to a neural network for training. The method is suitable for the robot to perceive the surrounding environment through the sensor in an unknown environment to perform path planning so as to reach a specified target point or establish an environment map, and is used for complex tasks such as space exploration, search and rescue, reconnaissance and the like.

Disclosed in the present invention are a UWB-based positioning apparatus and positioning method for a point target of a pointing apparatus. The positioning apparatus comprises a pointing apparatus and a receiving apparatus, wherein UWB antennas are respectively arranged on the pointing apparatus and the receiving apparatus, and an accelerometer and a gyroscope are further arranged on the pointing apparatus. By means of the pointing apparatus and the receiving apparatus, UWB-based positioning is performed to obtain coordinates of the pointing apparatus in a coordinate system in which the receiving apparatus is located; then by means of the accelerometer, a motion vector of the pointing apparatus is obtained, such that a linear equation for a corresponding pointing direction of the pointing apparatus is obtained; and by means of solving an intersection point of the linear equation and a pointing area, coordinates of a pointing point are determined, thereby achieving a design purpose.

The invention relates to a split type electro-hydraulic direct-driven non-retractable fin stabilizer hydraulic system which comprises a hydraulic unit and an actuating mechanism which are independently arranged, and the actuating mechanism comprises fin rotating oil cylinders which are symmetrically arranged; a bidirectional hydraulic pump driven by a servo motor forms a closed fin rotating loop; the bidirectional hydraulic pump driven by the servo motor, the hydraulic unit and the actuating mechanism form an electro-hydraulic direct-drive fin stabilizer device; the control loop is composed of a gyroscope, a controller and an executing mechanism, and the gyroscope detects the rolling angular velocity of the ship and generates a fin rotating instruction signal; the controller compares the instruction signal with the fin angle feedback signal and outputs a servo motor rotating speed instruction; the servo driver controls the servo motor to rotate forwards and backwards, the bidirectional hydraulic pump is driven to adjust the displacement of the fin rotating oil cylinder, and therefore the fin is driven to rotate. A valve control or pump control type hydraulic system adopted by a traditional fin stabilizer is replaced, integrated optimization, light weight, high efficiency, high reliability and low noise of the fin stabilizer hydraulic system are achieved, and the occupied space of equipment is reduced.

The invention discloses a semiconductor mechanical arm autonomous navigation and positioning method based on AI vision, and relates to the technical field of mechanical arms, and the method comprises the following specific steps: visual perception and multi-modal information fusion: collecting multi-modal data through configured industrial, depth, light field and polarized light cameras, pre-processing the multi-modal data, and carrying out multi-modal information fusion; realizing information fusion by using a deep learning network containing a feature extraction layer and a fusion layer and an attention mechanism, and outputting a unified visual description; according to the method, a deep learning target detection model is utilized, an attention mechanism is introduced to enhance the attention and extraction capability of small target features, the recognition result is optimized in combination with surface feature information recognized by polarized light imaging, the category and position of a target object can be accurately determined, meanwhile, a mechanical arm motion error model is established, and the recognition accuracy is improved. And the fused visual positioning information is fused with sensor data such as a mechanical arm joint encoder and a gyroscope by utilizing a sensor fusion technology, and a positioning result is optimized and compensated.

The invention relates to the technical field of driving, and particularly discloses a mobile phone management and control method and a control system in a driving process. Vehicle running state data and mobile phone multi-mode sensing data are obtained, vehicle CAN bus information and mobile phone sensor data are combined, a motion coupling degree value is calculated on the basis of deviation of a steering wheel angle and mobile phone acceleration, the operation synchronization rate is analyzed through accelerator operation and gyroscope response, hand action coordination is evaluated, and the hand action coordination is evaluated. The method comprises the following steps: calculating a spatial constraint deviation value by combining a magnetometer orientation and a driving position coordinate offset degree; monitoring an abnormal posture of a driver; generating a risk assessment value by fusing three indexes; dynamically controlling a mobile phone function; according to the system, through multi-source data fusion and a hierarchical management and control strategy, emergency communication requirements are balanced on the premise of ensuring driving safety, distracted driving behaviors are accurately identified, and driving potential safety hazards caused by use of a mobile phone are solved.

The invention belongs to the technical field of coupling alignment, and particularly relates to an intelligent auxiliary system for coupling alignment based on dual-laser displacement and an MEMS gyroscope, which adopts a mode of cooperative work of an active stable attitude measurement module and a space reference beacon module to establish a dynamic stable measurement basis which is not influenced by barring operation and environmental disturbance. The micro attitude change of the measuring device can be sensed and actively compensated in real time in the measuring process, it is ensured that laser displacement data at all angles are collected in the same absolute space coordinate system, and the high consistency and accuracy of multi-point measurement data are ensured. And then fusing the attitude feedback signal and the attitude reference signal by using an intelligent resolving module to generate an attitude control instruction, and processing displacement measurement data acquired by a double-laser displacement sensor after the attitude is stable to resolve a centering deviation parameter, thereby being beneficial to improving the efficiency, precision and automation level of coupling alignment work.

The embodiment of the invention provides a construction hoist height measurement method and device based on double correction, and the method comprises the steps: building a pressure height mapping model for initial calibration through fusing the data of a high-precision air pressure sensor and a six-axis gyroscope; the weight of the sensor is dynamically adjusted by adopting a motion state evaluation matrix, and error correction is realized by combining null drift reference point records. And constructing a state transition equation and an observation equation by using an extended Kalman filter, and obtaining a high fusion result through a prediction updating step. Meanwhile, the system has the functions of abnormal state monitoring and sensor mode automatic switching, and double guarantees of measurement precision and reliability are achieved. The method effectively solves the problem that a traditional single sensor measurement scheme is unstable in precision in a complex environment.

The invention discloses a video anti-shake system for eliminating interference of dynamic feature points, and the system comprises a feature point extraction module which is used for extracting a plurality of feature points in an image from a video frame, and generating the motion trails of the feature points; the dynamic feature point filtering module comprises a gyroscope data acquisition unit and a trajectory analysis unit; the gyroscope data acquisition unit is used for acquiring rotation information of the camera in a shooting process; the track analysis unit is used for carrying out clustering analysis on the tracks of the feature points based on the motion tracks and the rotation information of the feature points so as to identify and filter out dynamic feature points; and the image smoothing processing module is used for calculating the conversion between the video frames according to the filtered static feature points and smoothing the video frames so as to reduce picture jitter. According to the method, the video anti-shake effect in a dynamic scene can be remarkably improved, so that a video picture is more stable, and the problems of image distortion and deformation caused by existence of a dynamic object are reduced.

The invention belongs to the technical field of inspection equipment control systems, and discloses an inspection equipment control system, method and device, and the system comprises a difficulty recognition module, a path density adjustment module, a state monitoring module, a boundary compensation module and a control linkage module. According to the method, a trend included angle is obtained through numerical value change analysis of a track section structure, an angle matching ratio is introduced to realize dynamic adjustment of a path section interval, a three-period sequence is constructed in cooperation with gyroscope data to extract main direction change, disturbance rhythm change is accurately captured, disturbance amplitude is extracted through a minimum interval distance trend, and the disturbance accuracy is improved. A time axis turning position is reconstructed by combining data of a path trigger, a boundary offset reference is positioned, linkage control of the distance between path points and an average path is realized, a processing logic establishes a multi-dimensional linkage relation of path adjustment, disturbance identification and boundary compensation, and path response flexibility and equipment operation stability under environment change are enhanced. And the inspection precision and adaptability in a high-disturbance scene are improved.

The invention discloses a self-growing robot and an environment exploration method thereof. The self-growing robot comprises a driving storage mechanism, a plastic film body, a flexible sensing unit, a signal receiving module, pneumatic artificial muscles arranged on the inner wall of the plastic film body and a tail end guiding sensing mechanism. The flexible sensing units are attached to the surface of the plastic film body, the sensing units are designed in an array mode, detection of obstacles in the environment is achieved while flexibility is guaranteed, the tail end guiding sensing mechanism is used for sensing the posture of the robot, information of a proximity sensor, an encoder and a gyroscope is combined, and the detection accuracy of the robot is improved. Navigation in an unknown environment can be realized; besides, pre-bending is set according to environment obstacle information, the environment obstacle is used for guiding the robot to grow, a larger area can be covered by combining pneumatic artificial muscles, a proximity sensor is used for detecting angular points in the environment according to the method, and the environment is explored by adopting a depth-first strategy; and a relatively high environment exploration rate can be realized within relatively few exploration times.

The invention relates to a method for testing and compensating a gyroscope installation error angle of a fiber-optic gyroscope inertial platform, which is used for testing the installation error angle of a fiber-optic gyroscope platform relative to a hexahedral coordinate system after the fiber-optic gyroscope is installed on a platform body. The gyroscope installation error and the ground velocity are coupled in gyroscope output during error coefficient calibration, so that the true value of the calibration result of the instrument error coefficient is influenced, calibration is carried out in different orientations, the ground velocities coupled with the gyroscope installation error are different, and therefore, the calibration results of four orthogonal orientations are combined, and the gyroscope installation error angle calculation is realized in an analytic mode. And compensating the obtained gyroscope installation error angle into the error model, thereby solving the problem of testing the precision of the gyroscope of the high-precision fiber-optic gyroscope platform.

The invention discloses a GNSS (Global Navigation Satellite System) / inertial navigation tightly integrated navigation method and system based on robust auto-velocity constraint factor graph optimization, and the method specifically comprises the following steps: extracting pseudo-range and Doppler observation data from original observation information of a GNSS satellite, and obtaining accelerometer and gyroscope data from an INS (Inertial Navigation System); constructing a pseudo-range residual block, a Doppler residual block, an inertial navigation pre-integration residual block and a speed constraint factor, and integrating into a sliding window estimator based on factor graph optimization; according to the size of a set sliding window, adding all residual blocks in the window to form an optimized objective function; performing a first round of factor graph optimization to obtain a preliminary state estimation result, and endowing the observed quantity containing gross error with a relatively low weight; and updating the prior weight matrix, and carrying out second round of optimization to obtain a joint optimal estimation result of a plurality of moment states in the current time window. According to the method, the influence of gross error-containing observation information on weight estimation and state estimation is suppressed, the positioning precision is high, the robustness is strong, and the reliability is high.

The invention discloses a gas extraction pipeline tiny leakage positioning method based on multi-sensor fusion, which belongs to the technical field of positioning, is used for gas extraction pipeline leakage positioning, and comprises the following steps: establishing a state equation and an observation equation of a motion process of an inspection robot, and realizing inspection robot positioning under a navigation system based on Kalman filtering. And realizing coal mine gas extraction pipeline leakage source positioning under a microphone array coordinate system based on a beam forming algorithm, and obtaining coal mine gas extraction pipeline leakage source positioning under a navigation system through coordinate conversion. According to the method, the leakage source position of the gas extraction pipeline under the navigation system is directly given, maintainers can conveniently and quickly reach the leakage source position, and the first-aid repair time is greatly shortened; the positioning error of the inspection robot can be effectively reduced, and the phenomenon that the positioning error is accumulated along with time when the inspection robot only uses an accelerometer and a gyroscope for positioning is avoided; the influence of background noise on a positioning result can be greatly reduced, and the spatial resolution of a leakage positioning result is improved.

The invention provides a femtosecond laser-based hemispherical harmonic oscillator precision trimming device and method. The femtosecond laser-based hemispherical harmonic oscillator precision trimming device comprises a vacuum system, a femtosecond laser trimming system, a clamp, a workpiece movement system and a mass imbalance test system, the femtosecond laser trimming system comprises a focusing module, a laser light path, a femtosecond laser, a femtosecond laser energy continuous regulation and control module and a femtosecond laser patterning and control system; the workpiece movement system comprises a workpiece autorotation mechanism and a workpiece translation mechanism; the workpiece autorotation mechanism is used for realizing autorotation movement of the clamp and the hemispherical harmonic oscillator; the workpiece translation mechanism is connected with the workpiece autorotation mechanism and is used for realizing three-direction translation motion of the hemispherical harmonic oscillator and the workpiece autorotation mechanism; the mass imbalance test system comprises a harmonic oscillator excitation module and a test module. The harmonic oscillator excitation module is used for exciting the hemispherical harmonic oscillator; and the test module is used for detecting the vibration of the excited hemispherical harmonic oscillator. According to the invention, the influence on the stability of the standing wave of the harmonic oscillator and the precision of the gyroscope caused by an overhaul pit is effectively reduced.

The invention relates to a method for controlling the stability of a transport vehicle. Comprising the following steps that dynamic parameters of the speed, the acceleration, the steering angle and the sideslip angle of a vehicle are collected through a vehicle sensor comprising an accelerometer, a gyroscope and a wheel speed sensor; in combination with various sensors such as a vehicle-mounted radar, a laser radar and a camera, conditions of wet, slippery, rugged and uneven road surfaces are monitored in real time, and road surface friction coefficient parameters are generated through a data fusion algorithm; according to the dynamic state of the vehicle and the real-time road surface state, the stability of the vehicle is evaluated through a mathematical model, and the potential risk of current instability is calculated; a plurality of stability control modes are preset according to different driving scenes including expressways, mountain roads and wet and slippery roads, and different control parameters and algorithms are adopted in each mode; a sensor including a driver state monitoring system inside a vehicle and external environment data including meteorological data and traffic information are utilized to predict operation behaviors including sudden acceleration and sudden braking of a driver.

A hybrid electric aircraft equipped with gyroscopic stabilization control is provided. In one aspect, a hybrid electric aircraft includes a turbo-generator having a gas turbine engine and an electric generator operatively coupled thereto for generating electrical power. The turbo-generator defines a rotation axis. The aircraft also includes one or more electrically-driven propulsors for producing thrust for the aircraft. In addition, the aircraft includes a pivot mount operatively coupled with the turbo-generator. To provide gyroscopic stabilization control of the aircraft, the pivot mount is controlled to adjust the rotation axis of the turbo-generator relative to a prime stability axis of the aircraft. Additionally or alternatively, a rotational speed of the turbo-generator can be changed to provide gyroscopic stabilization control of the aircraft.