1255results about "Angle measurement" patented technology

The invention relates to the technical field of machine vision, and provides a visual inertial mileage pose positioning method based on cross attention and dynamic weight, which performs positioning prediction of visual inertial mileage pose information by means of a visual inertial mileage pose prediction model. In the visual inertial mileage pose prediction model, a cross-modal feature association between a visual optical flow feature and an inertial variable feature is established by using a cross attention mechanism, so that the attention of a space region highly related to inertial variable information in the visual optical flow feature is enhanced; meanwhile, by means of a dynamic weight fusion mechanism, dynamic balance between different modal features is achieved through a learnable weight distribution strategy, the problem of falling into a local optimal solution is helped to be avoided, and the accuracy of visual inertial mileage pose information positioning prediction and the stability and reliability for different scenes are remarkably improved.

The invention discloses a method for measuring an attitude angle of a free throwing object in a wind tunnel test through a binocular system, and belongs to the field of aerodynamics tests based on a photogrammetry technology. Comprising the steps that a binocular system is arranged in a wind tunnel, and internal and external parameters of the binocular system are calibrated through a cross scale; reconstructing the surface mark points of the calibration plate by photogrammetry outside the wind tunnel and establishing a local coordinate system; placing a calibration plate in the wind tunnel, wherein each vector of a local coordinate system is parallel or vertical to an incoming vector, and calibrating a wind tunnel coordinate system by adopting a resection method; carrying out photogrammetry and initial pose installation on mark points on the surface of a thrown object; acquiring each state image of the thrown object and reconstructing the three-dimensional coordinates of the surface mark points; taking the attitude angle of the thrown object as 0 degree as a reference state, and comparing the rigid body transformation relationship between the blowing state point cloud and the reference state point cloud to obtain attitude angle data. Alignment of a wind tunnel coordinate system and a binocular system coordinate system can be achieved, limitation of the appearance of the thrown object is avoided, and attitude angle data of the thrown object are calculated in a non-contact and high-precision mode.

The invention relates to the technical field of data processing, and discloses a VICTS antenna attitude estimation and correction method and system based on satellite pointing feedback, and the method comprises the steps: constructing a tight coupling depth fusion system with extended Kalman filtering as a frame, introducing satellite communication antenna pointing information as a new observation source on the basis of traditional IMU / GNSS fusion, and carrying out the satellite communication antenna attitude estimation and correction. By deducing the Jacobian matrix of the carrier attitude, effective fusion of the observed quantity is realized, so that the attitude estimation precision and robustness of the carrier are reversely corrected and remarkably improved, the three-axis attitude error is estimated and corrected more comprehensively and steadily, and the problem of lack of roll angle observation is fundamentally solved. Observation information of different dimensions is unified into the same state estimation framework through accurate mathematical modeling, and the precision, autonomy and robustness in a complex environment of the system are greatly improved.

The invention relates to pipeline circumferential weld detection, and discloses a pipeline circumferential weld defect detection method and system based on deep learning, multiple sensors are arranged on the surface layer of a pipeline to collect multi-modal signals, an inertial measurement device is combined to carry out pose correction, and a multi-modal time sequence data matrix is constructed; performing preprocessing and segmentation, calculating to obtain a dynamic reference band, and outputting upper and lower bounds; performing broken line fitting on each segment to extract a phase change factor triple, and comparing with a reference band to screen event candidate segments; constructing a multi-segment time domain coupling relation graph based on the candidate segments, and generating a dominant response mode candidate set; inputting a multi-branch time sequence coding network to extract a three-mode feature and generate a time sequence fusion feature; and performing similarity matching with a defect prototype library to obtain a defect category probability sequence, performing single-mode ablation and time sequence playback verification to obtain a high-confidence index, mapping the high-confidence index to a spatial position, and outputting a defect category and severity in combination with a feature index. According to the method, high-precision defect detection and reliable classification under the trenchless condition can be realized.

The invention discloses an alignment method for a vehicle-mounted radar and related equipment, and relates to the technical field of navigation calibration, and the method comprises the following steps: obtaining inertial measurement unit data and horizontal tilt angle sensor data of the vehicle-mounted radar; generating an initial attitude matrix based on the inertial measurement unit data; determining a horizontal attitude data difference based on the horizontal tilt angle sensor data and the initial attitude matrix; and obtaining an alignment result of the vehicle-mounted radar based on the horizontal attitude data difference and a Kalman filtering algorithm. The initial attitude matrix is generated by fusing the inertial measurement unit data and the horizontal tilt angle sensor data, fine alignment is performed by combining the horizontal attitude data difference and the Kalman filtering algorithm, the azimuth angle alignment precision of the vehicle-mounted radar in a dynamic environment is improved, dependence on external satellite signals is not needed, and the accuracy of the azimuth angle alignment is improved. High-precision autonomous alignment can be realized under complex working conditions such as shaking and vibration, meanwhile, the hardware cost and the system complexity are reduced, and the method has wide applicability.

The invention discloses a vertical retaining structure displacement automatic monitoring device and a monitoring method thereof, and relates to the technical field of displacement automatic monitoring, and the device comprises a data acquisition unit which is used for configuring monitoring nodes, obtaining sensor data monitored at the top of a retaining wall, and preprocessing the sensor data to obtain effective inclination angle data; the displacement conversion unit is used for recognizing and optimizing the attitude angle by using a dynamic Kalman filtering algorithm, and calculating a displacement value of the vertical soil retaining structure by combining the vertical distance from the bottom to the top of the soil retaining wall; the monitoring and early warning unit is used for uploading the displacement value of the vertical retaining structure to a remote data platform, constructing a monitoring network, analyzing and predicting the deformation trend of the retaining wall and triggering early warning according to an analysis result; and the battery management unit is used for providing battery state monitoring and management. The displacement of the top of the retaining wall can be accurately sensed and monitored through the inclination angle data, and comprehensive and accurate monitoring is ensured by adopting an attitude solver and a dynamic Kalman filtering algorithm.

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 belongs to the technical field of space remote sensing surveying and mapping, and particularly relates to a monitoring system and method for a front and rear view visual axis included angle and absolute direction of a surveying and mapping camera. The method comprises the following steps: S1, through side sway of a satellite platform, taking a time for sky imaging calibration as a reference time; s2, calculating a rotation matrix from a front and rear view ground camera measurement coordinate system to a star camera coordinate system at a reference moment; s3, calculating respective thermal deformation matrixes of the star camera coordinate system, the front-view camera measurement coordinate system and the rear-view camera measurement coordinate system; s4, obtaining a real-time rotation matrix from the measurement coordinate system of the front-view camera to the coordinate system of the star camera and a real-time rotation matrix from the measurement coordinate system of the rear-view camera to the coordinate system of the star camera at the measurement moment; and S5, carrying out arc cosine calculation on the two absolute pointing vectors to obtain a visual axis included angle between the front-view camera and the rear-view camera at the measurement moment. According to the invention, while the geometric accuracy of the surveying and mapping camera is ensured, the real-time performance of measurement and the comprehensiveness of subsystem monitoring are realized at the same time.

The invention discloses a laser radar attitude measurement positioning method and device for an aviation electromagnetic detection suspension system, and belongs to the technical field of aviation electromagnetic detection, attitude measurement and coordinate positioning. According to the invention, real-time space positioning information and attitude information of the aviation soft suspension flight pod subsystem are accurately obtained by adopting a non-contact laser remote sensing measurement mode, and attitude and positioning devices do not need to be fixedly installed on the suspension flight pod subsystem. Electromagnetic interference or dynamic stability of the attitude and positioning device and related auxiliary electronic equipment on the soft suspension flight pod subsystem is avoided, the accuracy of electromagnetic signals and data reliability in the detection process are ensured, and therefore the precision of aviation electromagnetic detection is improved.

The invention relates to an end-to-end spacecraft pose measurement method based on deep learning, and belongs to the field of spacecraft pose measurement, the method uses a sliding window transformer as a feature extraction backbone network, introduces a multi-layer large kernel convolution module, and is used for enhancing a global receptive field and feature expression ability. A rotating head detection network and a position head detection network are arranged in parallel after the backbone network, a rotating head is used for predicting a 3D key point and a projection weight thereof, a position head is used for predicting a 2D key point, a 2D-3D corresponding relation is sent to a differentiatable EPro-PnP module for pose solving, it is ensured that a gradient can be completely transmitted back to a feature extraction layer, and a feature extraction layer is obtained; therefore, a globally optimal solution is obtained, and integrated network training of feature learning and geometric pose solution is realized. According to the method, a complex loss function is constructed, through multi-angle supervision and complementary optimization, it is ensured that the model can accurately predict the 6D pose of the spacecraft, and robustness and generalization performance in a complex environment are enhanced.

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.

The invention discloses an offshore small target radar detection method and system, and relates to the technical field of radio detection. The method comprises the following steps: acquiring radar echo data, a visible light image, an infrared image, an AIS signal and navigation attitude data in real time; performing sea clutter suppression and pre-filtering on the radar echo data, and correcting target plots in combination with a historical radar plot set to obtain a radar single-source target track set; performing target detection on the visible light image and the infrared image to obtain an optical target detection set and an infrared target detection set; the radar single-source target track set, the optical target detection set, the infrared target detection set, the AIS signals and the navigation attitude data are associated and fused, and finally deception feature recognition and consistency verification are performed to obtain an updated fused target track set; according to the method, man-made confrontation and cheating behaviors on the sea can be accurately identified, and reliable support is provided for safety monitoring on the sea, maritime affair supervision and emergency response.

The invention relates to the technical field of automatic control, in particular to a detection equipment attitude real-time correction system which comprises an attitude trajectory extraction module, a trajectory stability evaluation module, an interference area recognition module, a light spot trajectory reconstruction module and an attitude correction control module. According to the invention, through comprehensive extraction of the direction change trend, the angle difference and the trajectory overlapping condition in the light spot image sequence, the trajectory trend of the attitude change between continuous frames is established, so that the identification of the attitude offset evolution process is more detailed, the attitude change stability analysis is realized in the time sequence dimension, and the accuracy of the attitude change is improved. Interference area identification is carried out by means of luminance continuity and spatial distribution consistency of light-emitting pixels, real light spots and lagging residual signals can be effectively distinguished, a light spot track path is reconstructed on the basis of interference removal, and real-time calculation of a track dynamic offset direction and an angle change amplitude is combined with track correction rule setting, so that the accuracy of track correction is improved. And the specific correction action matching of the deviation state is realized.

The invention relates to a sun meridian detection and course angle real-time calculation method based on polarized light field vector characteristics, and aims to solve the problems that a traditional sun meridian detection method is easily interfered in low signal-to-noise ratio scenes such as haze and cloud layer shielding, lens distortion causes polarization angle errors, the false detection rate is high, and the calculation accuracy is high. In order to solve the problems that the real-time performance and robustness of course calculation are affected due to the fact that single polarization angle information is difficult to fully reflect the sun direction, polarization parameter calculation is carried out by utilizing a multi-channel polarization image, and the sun meridian is detected by adopting Hough transform through fisheye lens correction, bilateral filtering and candidate region screening, so that the real-time performance and robustness of course calculation are improved. And a multi-point inversion method is combined to accurately obtain a sun vector and a zenith angle and an azimuth angle thereof, and finally a course angle is calculated in real time. The problems of imaging distortion and insufficient real-time processing in the traditional sun positioning technology can be effectively solved, and a powerful navigation positioning technical guarantee is provided for the fields of unmanned aerial vehicles, autonomous navigation, polarized light navigation and the like.

The present invention relates to a real-time heading angle calculation method based on the vector characteristics of the polarized light field. Aiming at the problems of traditional solar meridian detection methods, such as being easily disturbed in low signal-to-noise ratio scenarios like haze and cloud cover, the occurrence of polarization angle errors and high false detection rates caused by lens distortion, and the difficulty of using single polarization angle information to fully reflect the solar direction, which affects the real-time performance and robustness of heading calculation. This method calculates polarization parameters by using multi-channel polarization images.

The invention relates to the technical field of bionic navigation orientation and positioning, in particular to a carrier course angle measuring method based on polarized light imaging in a non-Rayleigh atmosphere. Comprising the steps of real-time sky polarized light imaging, atmospheric polarization mode resolving based on Mueller matrix imaging, non-Rayleigh polarization information interference removal, polarization orientation resolving based on Rayleigh scattering, space projection conversion and sun position information resolving. Alignment information of the sun in a carrier coordinate system is obtained by utilizing a Rayleigh scattering model and actual sky polarization imaging, and then a carrier course angle is obtained according to the orientation of the sun in a local geographic coordinate system, so that an orientation function is realized; meanwhile, the error influence caused by image registration and time-sharing rotation measurement of the multi-view-field polarization detector and the interference of environmental factors on a single point are avoided, the method can adapt to sunny and cloudy weather, is also applicable to cloudy and other non-Rayleigh weather, and is wide in application range.

The invention relates to a heading machine pose measurement and control method and system based on visual direction finding and communication distance measurement. The system comprises a base station end measuring system in a roadway, a mobile end measuring system on a heading machine body and a motion control module. The method comprises the following steps: S1, establishing a base station end coordinate system; s2, establishing a mobile terminal coordinate system; s3, the base station side identifies and measures the vector information of the characteristic light source of the mobile terminal through a visual sensor; s4, the base station end and the mobile end measure the distance between the base station end and the mobile end through communication ranging equipment; s5, calculating the three-dimensional position of the mobile terminal in the coordinate system of the base station terminal based on the vector information and the distance information; s6, according to the three-dimensional position and the inertial measurement data of the mobile terminal, carrying out combined navigation calculation based on an EKF algorithm; and S7, performing pose control based on a combined navigation calculation result. According to the invention, a means of combining visual direction finding, communication distance measurement and inertial measurement is adopted, so that the position measurement precision is improved.

The invention relates to the technical field of perception fusion, and discloses a tug fusion enhanced perception method based on target tracking and obstacle recognition, which comprises the following steps: processing an AIS, an optical fiber compass, a Beidou RTK, a laser radar, a millimeter wave radar and a panoramic camera on a tug to establish a ship coordinate system; and collecting message data of the AIS and combining with the MMSI information to screen the target ship to obtain the initial position of the target ship. And predicting the state sequence of the target ship to obtain the position, speed and heading information of the target ship. And carrying out target identification on the image, outputting identification results of semantic levels of the ship, the buoy and the quay wall, and carrying out space projection alignment with radar data. And fusing the processed results to obtain a fusion result, and performing early warning according to the fusion result. According to the method, the target ship relative pose resolving precision and the obstacle recognition reliability are improved, the sensing link time delay is shortened, and the driver blind area risk is reduced.

A method for calibrating position and orientation of a stage light fixture includes acquiring light spot images and light fixture angle information when light beams of the stage light fixture respectively project on at least three different positions, and calculating first coordinates of a light beam center line projection point image in each of the light spot images in a camera coordinate system; deducing second coordinates of a light beam center line projection point on the stage in a stage coordinate system based on the first coordinates and information about internal parameters and a position and an orientation of a camera when the light spot images are acquired, and recording corresponding relationship between the second coordinates and the light fixture angle information; and determining a calibrated position and orientation of the target stage light fixture based on the second coordinates, the light fixture angle information and the corresponding relationship.

The invention discloses a roadside parking space management method and system based on a Beidou positioning system, and relates to the technical field of roadside parking space management, and the method comprises the following steps: collecting the current position coordinates of a vehicle through the Beidou positioning system, and combining a parking space position information database in an urban road parking management platform, identifying the current standard parking space number of the vehicle, and generating an analysis area with the parking space center as the circle center according to the center coordinate of the parking space and a preset analysis radius; and calling the accessed urban three-dimensional geographic information platform, and retrieving and analyzing all building boundary objects in the area. According to the invention, by introducing a building density intelligent prediction and self-adaptive fuzzy buffer mechanism and combining secondary verification of the vehicle body orientation and the inertial navigation trajectory, the positioning drift error of the Beidou in the building dense area is effectively offset, the parking space judgment fault tolerance is improved, the misjudgment and error control risk is significantly reduced, and the accuracy and stability of roadside parking management are enhanced.

The invention discloses a single-satellite target sight atmospheric refraction correction method and system based on multi-spectral range finding, and relates to the field of atmospheric refraction processing, and the method comprises the steps: determining a target radiation intensity ratio based on two radiation intensities on different wavebands at the same moment; obtaining observation sight lines of the satellite on the measured target on different wave bands at the same moment, and carrying out light trace tracking to obtain a light ray tracking trajectory; determining a target grid through which each ray tracing trajectory passes from the atmosphere gridding model, determining an extinction coefficient of each target grid, and constructing a target function of a radiation intensity ratio with respect to the height of the target from the ground in combination with a radiation intensity calculation formula; determining a target height from the measured target to the ground based on a target function and a target radiation intensity ratio, determining the position of the measured target according to a track point matched with the target height in each light ray tracing track, and determining a sight line vector after atmospheric refraction correction by combining the position of a satellite, therefore, high-precision atmospheric refraction correction under a single-star observation condition is realized.

The invention discloses an autonomous positioning and navigation method and system for a ground mobile robot. The method comprises the following steps: S1, multi-source asynchronous environment perception and initial positioning; s2, carrying out adaptive fusion on multi-source data of time-space association; step S3, global pose optimization under semantic constraint; s4, decision planning driven by the dynamic risk field; and S5, automatically recovering the abnormal state and updating the map. According to the invention, through environmental response type sensor fusion, multi-modal semantic constraint modeling and entropy-driven intelligent decision-making mechanism synergistic effect, industrial pain points of positioning drift, low planning efficiency and insufficient long-term operation reliability in a complex dynamic scene are systematically solved; the centimeter-level positioning precision and the smooth motion trail are kept under the extreme conditions of severe illumination change, dense obstacle disturbance and repeated structure path, the passive operation and maintenance mode that a traditional navigation system depends on manual intervention is thoroughly changed, and a full-autonomous navigation capability closed loop is provided for industrial logistics and commercial service scenes.

The invention discloses a method for measuring the swing angle of a hoisted object of a crane based on multi-sensor information fusion, which realizes high-precision measurement of the swing angle of the hoisted object of the crane in a dynamic environment by fusing data of an inertial measurement unit (IMU) and an industrial camera and combining the advantages of the IMU and the industrial camera. Through an IMU swing angle real-time correction mechanism based on a visual swing angle, the accumulative error of the IMU is eliminated, and the precision of the swing angle measurement of the hanging object is ensured. The mechanism can trigger correction in real time in the dynamic swinging process of the object hoisted by the crane, and the reliability, accuracy and real-time performance of the system are greatly improved. A multi-sensor fusion mechanism is adopted, the problems caused by drifting or failure of a single sensor are effectively reduced, and it is ensured that even if visual data are lost or an IMU drifts, the system can still run reliably and output an accurate swing angle result.

The invention provides a measurement system for the waviness of a neutron conduit. The measurement system comprises a high-precision granite guide rail, a total station, an auto-collimation eyepiece, a computer and a measurement auxiliary assembly. The high-precision granite guide rail provides a stable sliding reference, the total station slides along the high-precision granite guide rail for measurement, the auto-collimation eyepiece is matched with the normal direction of the measurement conduit, and the computer processes data. The system can adapt to measurement requirements of neutron conduits in different geometrical shapes, and the waviness is calculated through a preset formula, and the assembly precision of multiple sections of conduits and the influence on neutron reflection are evaluated; the measurement auxiliary assembly and the jack ensure stable measurement. The system is high in measurement precision, strong in universality, efficient in data processing, good in stability, simple and convenient to operate and capable of guiding design and manufacturing of neutron conduits, reducing production cost and improving neutron flux and experiment accuracy and reliability.

The invention discloses an infrared focal plane array attitude estimation method and device, and belongs to the technical field of rotary carrier attitude estimation, and the method comprises the steps: extracting the features of infrared focal plane array data through a sliding window, and obtaining the feature vectors of a plurality of windows; selecting a blocking mode by using an MLP decision network, and dividing the infrared focal plane array data in the window into a plurality of sub-blocks; calling a corresponding distributed LSTM model from a distributed LSTM model pool to estimate the attitude angle sine and cosine values of each sub-block according to the infrared focal plane array data of each sub-block and the blocking mode; and fusing the attitude angle sine and cosine values of the sub-blocks based on a self-attention mechanism, and converting the fused attitude angle sine and cosine values into an attitude angle under an angle system to obtain an infrared focal plane array attitude estimation result. The method improves the precision and real-time performance of attitude angle estimation, and can be widely applied to attitude estimation of a high-speed rotating carrier.

The invention relates to an AR (Augmented Reality) space true north calibration method, device and equipment and a medium. The method comprises the following steps: acquiring fixed solution positioning data in a moving process by utilizing RTK (Real-Time Kinematic) equipment; based on the fixed solution positioning data, selecting a first positioning point and a second positioning point, calculating a coordinate azimuth angle between the two positioning points by using Gaussian positive and negative calculation, and calculating a meridian convergence angle at the first positioning point; calculating an included angle between a connecting line of the first positioning point and the second positioning point and the true north direction based on the coordinate azimuth angle and the meridian convergence angle to obtain a geographic true north direction angle; and continuously monitoring data of a gyroscope of the RTK equipment and a gyroscope on the AR running equipment, and dynamically adjusting the true north direction angle in the AR space by adopting a double-loop control structure based on the geographic true north direction angle, so as to ensure that the AR space is consistent with the true geographic direction. Compared with the prior art, the method has the advantages that the AR space direction precision is improved from + / -5 degrees to + / -0.1 degrees, and the surveying and mapping standard is achieved.

The invention discloses a system and a method for automatically measuring pipe network parameters based on three-dimensional scanning of a wellhead of an inspection well, and belongs to the technical field of municipal engineering measurement. The system comprises a wellhead fixing assembly, a three-dimensional laser scanning assembly, a posture sensing assembly, a distance measuring assembly, a coordinate input assembly, a control processing assembly and a telescopic rod assembly. According to the method, through system deployment leveling, coordinate reference establishment, working condition judgment, point cloud acquisition, data processing and result output, automatic measurement of inspection well depth, pipe network pipe diameter, pipeline trend and pipe orifice center coordinates is realized. The system is fixed at a wellhead, does not need to descend, and adapts to scenes such as shallow wells / deep wells and good / weak signal areas; based on a high-density point cloud and an automatic algorithm, the measurement precision is high, the efficiency is improved, and output data can be directly used for pipe network modeling. The method solves the problems of low efficiency, strong manual dependence and poor safety of traditional measurement, and is suitable for parameter measurement of various inspection wells and pipe networks.

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

The invention discloses a battery pack special-shaped part accurate positioning method and system fusing a disassembly topological relation, and belongs to the technical field of power battery disassembly positioning. The method comprises the following steps: acquiring a global point cloud of a battery pack by using a global camera, and registering with a preset CAD model to obtain a transformation matrix; a graph neural network assembly relation scene graph is constructed based on the matrix and a CAD model analysis result, and semantic association recognition of the parts is achieved; performing difference detection by comparing the registered CAD model with the global point cloud, and marking the state of the part; and planning an optimal recognition view angle of the local camera according to a sheltered or uncertain state, controlling the local camera to obtain a local point cloud and performing fine positioning, and updating pose information in the scene graph. The method is mainly used for accurate positioning of special-shaped parts in the power battery disassembling process, data support is provided for robot disassembling operation, the positioning robustness under the severe working condition is improved, and meanwhile the positioning problem caused by shielding is effectively solved.

The invention relates to the technical field of automobile fault detection, and discloses a self-adaptive optimization method and system of an automobile fault detection system and a storage medium. The method comprises the following steps: performing real-time detection on attitude data based on a preset inclination angle threshold value and steering signal delay, and generating angular velocity sensing data and a vibration interference identification result; performing characteristic decomposition on the attitude data stream, identifying abnormal fluctuation, judging whether a potential fault signal exists or not, updating the calibration frequency of the vehicle-mounted sensor, and obtaining adjusted parameter configuration information; a fusion result of the attitude data is analyzed, an evaluation index of deviation correction precision is calculated, a real-time feedback mechanism is constructed based on the evaluation index, and a fault signal correction scheme is generated; and constructing a continuous detection cycle, analyzing the matching effect of the calibration frequency and the steering signal delay, and if the deviation correction precision does not reach a first preset standard, iteratively processing the attitude data. According to the invention, the precision and response speed of adaptive optimization of the automobile fault detection system are improved.