1610 results about "Calibration result" patented technology

The invention relates to the technical field of water pollution detection, in particular to a water quality pollution multi-dimensional analysis system which comprises the following steps: synchronously measuring an ultraviolet-visible absorption spectrum of a water sample to be detected and scattered light intensity in an orthogonal direction, and deducting spectrum baseline interference caused by suspended particulate matters in the water sample through a correction algorithm; the interferents in the water sample are selectively converted and degraded by applying a programmed potential to the inflowing water sample to be detected; the reverse pulse is periodically applied, so that the online regeneration function of the electrode is realized; analyzing the spectral data by adopting a multivariate correction algorithm, and calculating the concentration of the target pollutant; the calculation residual error of the multivariate correction algorithm is analyzed, new interference and system performance drift of current measurement are diagnosed, and a corresponding system state code is generated; and responding to the system state code, automatically starting and carrying out state checking and multi-point calibration on the instrument, and using a calibration result to update the analysis model. Through multi-dimensional perception and closed-loop operation, accuracy and reliability of water quality monitoring are guaranteed.

The invention discloses a laboratory analytical instrument automatic calibration system based on artificial intelligence, and belongs to the technical field of instrument automatic calibration. Comprising the following modules: an intelligent hardware interaction module for realizing plug-and-play of different instruments and accurate conveying of standard substances; the instrument digital twinning module automatically identifies the characteristics of the instrument and simulates the behaviors of the instrument; the multi-mode AI calibration module is used for optimizing calibration parameters and adjusting the calibration process in real time; the environment intelligent compensation module calculates and generates a compensation coefficient in real time, and eliminates the influence of environmental factors on a calibration result; the instrument health management module is used for evaluating the health state of the instrument and predicting the service life of a core component, and realizing conversion from passive maintenance to predictive maintenance; the calibration knowledge graph module is used for realizing automatic extraction, reasoning and application of calibration knowledge through a graph neural network and continuously optimizing a calibration strategy; and the intelligent scheduling and management module is used for generating an optimal calibration plan, coordinating the work of each module and realizing reasonable distribution and efficient utilization of calibration resources.

The invention provides a cross-modal adaptive matching online external parameter calibration method and system for a laser radar and a camera, and belongs to the technical field of online external parameter calibration of the laser radar and the camera, initial external parameters are obtained by using a static calibration result, a laser radar point cloud is projected to a visual angle of a virtual camera, an LIP image aligned with a camera image is generated, and a calibration result is obtained. Performing cross-modal segmentation on the LIP image and the RGB image, extracting a semantic mask, generating a cross-modal feature point pair through a strategy, and performing preliminary external parameter calculation in combination with a PnP algorithm; global optimization is carried out through a multi-modal loss function, and an inter-frame smoothing and increment optimization strategy is introduced to ensure accurate estimation of external parameters. Finally, the optimized external parameter matrix is applied to projection and matching of subsequent frames, and can adapt to environment change and data dynamic update in real time. The method has high precision and real-time performance, overcomes the defects that off-line calibration depends on a specific calibration target and cannot cope with dynamic environment changes, and adapts to application requirements in high-speed motion and complex environments.

The invention relates to the technical field of machine vision, in particular to a calibration method and device for an industrial machine vision measurement system, and the method comprises the following steps: collecting error data through a glass linear scale and a circular target, constructing a standardized calibration data set, obtaining a global error gradient field, a residual error trend map and a residual error weight coefficient table, and obtaining a standard calibration data set; and fusing the size compensation value and the directivity correction value, constructing a calibration matrix, and obtaining a system calibration result. According to the method, through fusion modeling of multi-source error data, the recognition precision of the system on error sources is improved, gradient field construction and trend graph extraction are combined, the directionality and spatial continuity of error compensation are enhanced, and a weight coefficient distribution mechanism is utilized, so that differential control on dynamic and static error influence is realized; and a calibration matrix with multi-dimensional parameter fusion is adopted to optimize the consistency and adaptability of the overall measurement precision, so that the system keeps stable error correction capability and calibration accuracy in a complex environment.

The invention discloses a flowmeter-oriented embedded multi-parameter fusion calibration control method and system, relates to the technical field of industrial measurement and embedded control, and is used for solving the problem of unstable calibration caused by misalignment of multi-link flow signals, compensation lag and fusion oscillation. The method relates to synchronous acquisition, pretreatment and calibration of differential pressure type, ultrasonic wave and thermal type mass measurement links and environment parameters such as temperature, pressure and density. All-channel unified time scales are established through ternary binding, filtering and denoising, zero snapshot and alignment rules, a stability scoring mechanism is constructed in combination with offset behavior recognition, event classification and feature aggregation, and dynamic switching of a compensation path and a fusion strategy is driven. In a double-path fusion structure, table look-up compensation, model estimation, multi-algorithm parallelism and fusion track recording are adopted, version traceability and calibration result closed-loop control are achieved, and the stability and rechecking performance of mass flow output under complex disturbance are effectively improved.

An adaptive calibration method and system for an electric energy meter, relating to the technical field of electric energy meter calibration. The method comprises: acquiring basic data and additional data of an electric energy meter (S1); performing time series data alignment, and performing period division on an environment data set to generate a time series segmentation result (S2); acquiring device information of the electric energy meter, performing key feature analysis within a period, and establishing an interference weight factor for each feature (S3); building a performance degradation model (S4); acquiring usage environment data of the electric energy meter by means of a monitoring sensor (S5); then generating an adaptive calibration result on the basis of the performance degradation model (S6); and finally performing electric energy meter calibration management (S7). The present invention solves the technical problem in the prior art where the accuracy of electric energy metering is affected due to untimely calibration caused by an inability to monitor performance degradation of an electric energy meter in real time, thereby implementing effective calibration management for the electric energy meter, ensuring the long-term accuracy and reliability of the electric energy meter, and improving the efficiency of calibration work.

The invention provides a pipe thread positioning and measuring method and system based on three-dimensional vision, and belongs to the technical field of industrial automation and three-dimensional vision. According to the method, a measuring system composed of a robot measuring system and a three-dimensional visual locating system is built, and hand-eye calibration is completed; the method comprises the following steps: acquiring a three-dimensional point cloud model of the end part of a pipe thread workpiece, and extracting an end surface normal vector, a tangent vector and a circle center coordinate through preprocessing, cylinder fitting, near-end surface point cloud extraction and end surface circle fitting so as to establish a measurement reference coordinate system; and converting the reference coordinate system to a robot base coordinate system based on a hand-eye calibration result and the tail end pose of the robot, generating a robot moving trajectory, guiding the robot to be positioned to a measurement position, and completing preparation before measurement. According to the invention, automatic high-precision extraction of the pipe thread measurement reference is realized, the problems of non-uniform reference, large error and low efficiency in traditional measurement are solved, the method is suitable for various pipe thread workpieces, and a reliable basis is provided for subsequent high-precision measurement.

The invention relates to the technical field of high-precision pressure sensing, and discloses a pressure response data calibration method and device and computer equipment, and the method comprises the steps: collecting the output response data of a pressure sensor array, and constructing a spatial feature matrix, a time feature matrix and an environment feature matrix based on the output response data; performing trilinear least square separation to obtain dynamic response data and time characteristic data; performing symmetric geometric mode decomposition to obtain linear response component data, periodic fluctuation component data and nonlinear characteristic component data; inputting a multi-branch gating circulation unit network model to carry out dynamic calibration strategy prediction to obtain a first dynamic calibration strategy; performing particle swarm iterative optimization to obtain a second dynamic calibration strategy, and generating a progressive calibration parameter set; static and dynamic pressure sensing calibration is performed on the pressure sensor array to obtain a comprehensive pressure sensing calibration result, so that the accuracy of pressure sensing calibration is improved.

The invention relates to the field of navigation ship identification, in particular to a ship identity multi-modal verification method and system based on computer vision and deep learning, and the method comprises the steps: obtaining multi-modal data of a ship, the multi-modal data comprising visible light image data, laser radar point cloud data and ship identity information; extracting visual features of the ship according to the visible light image data; performing dynamic space calibration on the laser radar point cloud data; according to a calibration result, extracting three-dimensional structural features of the ship; the visual features, the three-dimensional structure features and the ship identity information are fused and input into a preset verification model, verification results are output through the verification model, and the verification results comprise normal ships and abnormal ships. Different types of data provide multi-dimensional understanding of the ship, and the precision and robustness of ship identification are enhanced.

The invention relates to the technical field of optical detection and calibration, in particular to an optical detection and calibration method based on a laser cross calibration method, which comprises the following steps of: 1, suppressing dynamic ambient light and adjusting laser parameters; step 2, extracting anti-distortion feature points; 3, multi-view error collaborative optimization: inputting the corrected coordinates output in the step 2 and mechanical motion parameters of a rotating shaft encoder into a splicing optimization model, constructing a coordinate transformation matrix with curvature constraint, and obtaining a three-dimensional calibration point cloud under a global coordinate system through iterative optimization; and 4, dynamic closed-loop compensation: dynamically correcting the laser power compensation coefficient in the step 1 and the distortion correction parameter in the step 2. Through close cooperation of multiple steps, high-precision, stable and self-adaptive laser calibration is realized, and reliable optical detection and calibration results can be provided in various environments and working conditions.

The invention relates to wide-range multi-component sensor calibration equipment and a wide-range multi-component sensor calibration method. The method comprises the following steps: firstly, checking equipment parts and setting a target temperature range and a compensation model of each temperature interval; then, dynamic temperature control is started, jig deformation is monitored in real time, a transient temperature gradient suppression technology is applied, multi-physical-quantity calibration is executed, and a compensation measurement value is output; then setting multi-environment coupling calibration test conditions to simulate actual working conditions, and monitoring and recording calibration data of each physical quantity; and finally, calculating a calibration error by combining a calibration result and a reference standard value. According to the process, by precisely setting parameters and combining dynamic control, real-time monitoring and multi-physical-quantity calibration, the transient temperature gradient influence is effectively inhibited, and the measurement precision of the sensor in a complex environment is ensured; the temperature control performance is improved through the micro soaking film and the intelligent temperature control strategy, the actual working condition is simulated through multi-environment coupling testing, the accuracy and reliability of the calibration result are remarkably improved through compensation and error calculation, and guarantee is provided for precise application of the sensor.

The invention relates to the field of intelligent industry, and discloses a visual robot hand-eye calibration method based on a circular hole calibration plate, which takes the circle center of a calibration plate circular hole as a fixed point as a constraint, establishes a hand-eye calibration model combined with robot kinematics parameters, and performs a contrast experiment with a traditional standard ball method under the same experiment platform. After a calibration result is obtained, a certain high-precision plane is scanned with reference to a flatness error evaluation method, a point cloud of the plane is obtained, the distance root-mean-square error between the point cloud and the least square fitting plane is calculated, and the distance root-mean-square error serves as an evaluation parameter of the hand-eye relation calibration precision. According to the method, the position coordinates of the fixed points in the space are collected more accurately under the on-line laser coordinate system, and kinematics parameters of the robot are incorporated into the hand-eye calibration model, so that the root-mean-square error of plane measurement can be reduced, and the superiority of the method is verified.

The invention discloses a heading equipment cutting head position calibration method based on image acquisition, which comprises the following steps: S1, acquiring image data and preprocessing the image data; s2, extracting cutting head feature points, and constructing a two-dimensional feature point set; s3, calculating a three-dimensional coordinate by using perspective transformation, and generating a point cloud set; s4, performing rigid registration on the point cloud set and a standard structure model of the tunneling equipment, and iteratively solving a rotation matrix and a translation vector to obtain pose parameters; s5, simulating change tracks of the feature points in continuous frames, constructing a time consistency constraint, and optimizing pose parameters; s6, the optimized three-dimensional coordinates are converted to a reference coordinate system, space alignment is completed, and a position calibration result is generated; and S7, outputting a calibration result for control instruction generation and path planning. According to the invention, high-precision and non-contact three-dimensional position calibration of the cutting head of the tunneling equipment is realized, and operation automation and control precision are improved.

The invention discloses an AI-based tendering and bidding full-process intelligent generation and review method and system. The method comprises the steps of tendering full-process intelligent generation, bidding full-process intelligent generation and bidding review. An AI scoring model is adopted for review, the technical scheme of each bidding document is deeply analyzed through a natural language processing technology, and real-time cross validation is carried out with a knowledge graph, so that the score of each sub-item is provided with detailed comments and a definite evidence chain, the objectivity, transparency and credibility of review are greatly improved, and the review efficiency is improved. The review quality is improved from experience judgment to a data and knowledge driven level; secondly, potential violation behaviors are identified through a surrounding bidding risk report generated through multi-dimensional correlation analysis, and the risk prevention and control capability is effectively enhanced; and finally, based on comprehensive data analysis, automatically generating a bid-winning candidate sorting and comprehensive review report, and ensuring that the calibration result is optimal.

The invention discloses a laser radar visual joint calibration method based on lane line extraction, and the method comprises the steps: S1, obtaining environment point cloud data from a laser radar sensor, carrying out the plane fitting through an RANSAC algorithm, carrying out the lane line point cloud extraction, and carrying out the clustering of the extracted lane line point cloud, and forming a line feature point cloud; s2, acquiring environment image data from a camera, performing image semantic segmentation on the environment image data, extracting a pixel region of a lane line in the environment image data by using a DeepLab-V3 network, and then performing feature mask binarization processing; s3, finding out line features in the environment point cloud data and the environment image data, then carrying out consistency matching, solving a three-line perspective problem, and obtaining preliminary external parameter estimation by establishing a corresponding relation of three line features; and S4, performing refined calibration on the preliminary matching result by using an optimization algorithm, and outputting external parameter calibration results of the laser radar and the camera through multiple measurements and data fusion, including a rotation matrix and a translation vector.

The invention discloses an electromechanical equipment distributed control system based on the Internet of Things, which belongs to the technical field of distributed control, and specifically comprises the following steps: splitting a control task into task units, registration dependencies, data entries and task levels at an edge gateway, and generating a candidate scheduling range according to registration items; a calibration heartbeat with a reference segment is issued, and a driving node executes and returns a measurement record in an idle window for calibrating hardware fingerprints and link overhead and dynamically updating matching parameters; when computing power saturation is triggered, splitting a low-level task unit into suspensible fragments, setting a de-duplication execution identifier, opening a state interface, and completing migration check; selecting a target control node and a transmission path according to a calibration result, issuing fragment and state interface information, driving a target node to continue fragments according to an execution template, and guiding a source node to release occupied resources in sequence; and checking and comparing the execution result, and when the rule is triggered, recovering to the previous stable state according to the mapping rollback table.

The invention relates to the technical field of agricultural remote sensing measurement, and discloses an unmanned aerial vehicle hyperspectral online calibration measurement method for agricultural remote sensing, which comprises the following steps: acquiring hyperspectral data of a target crop and reference vegetation in the same scene in real time through an unmanned aerial vehicle, and extracting a characteristic wave band reflectivity difference value delta R, according to the comparison result of the time sequence change rate of the delta R and the preset threshold value, crop physiological changes and environmental interference are dynamically distinguished, and online calibration is achieved. A self-consistent calibration mechanism is constructed by means of the time sequence stability of crop spectral characteristics, the illumination mutation influence can be eliminated without depending on an external reference substance, and the accuracy of the calibration result is improved. And meanwhile, a lodging scene is effectively identified through synchronous analysis of a gravity vector and spectrum drift, so that the system can still keep accurate tracking of a real physiological state of a crop under an extreme working condition.

The invention discloses a projection single attitude calibration method, system and device and a medium, and relates to the technical field of computer vision and projection interaction.The method comprises the steps that a plurality of calibration patterns are generated and projected to a calibration plane, gray level images are collected, corner point detection and sub-pixel refinement processing are carried out, and a projection single attitude calibration result is obtained. The method comprises the following steps: acquiring an angular point corresponding relation between a projector image and a camera image, carrying out iterative solution on a projection matrix of a projector and a projection matrix of a camera, separating an internal parameter matrix and an external parameter matrix, calculating a basic matrix and an essential matrix, and decomposing to obtain a rotation matrix and a translation vector of the camera relative to the projector; camera imaging distortion is estimated, a distortion correction coefficient is obtained, and distortion correction is carried out; and counting a re-projection error generated in the correction process, and adjusting parameters of the projector and the camera until the error meets a preset precision requirement. Projector parameter calculation is completed through projection single posture calibration, posture adjustment is not needed in the calibration process, the automation degree is improved, and meanwhile manual intervention is reduced.

The invention discloses a health monitoring management system based on a multi-modal index, and belongs to the technical field of health monitoring, and the system specifically comprises a data collection unit which synchronously collects physiological signals at the same anatomical position of a user through a professional medical device and a wearable device; the calibration model construction unit is used for extracting reference waveform characteristics of professional medical equipment, analyzing a signal offset mode of the wearable equipment, fitting a dynamic correction curve and generating a calibration comparison table; the dynamic correction unit is used for inputting the real-time data of the wearable equipment into a calibration comparison table for correction, generating a reconstructed data stream aligned with the time domain of the reference signal, and ensuring the synchronization of waveform key points; the calibration verification unit is used for calling high-precision data to verify the calibration result in a preset period, and updating the calibration rule base when the matching error of a plurality of continuous calibration windows is lower than a threshold value; according to the method, the wearable device is periodically calibrated through the high-precision professional medical device, and the daily health monitoring precision of the user is improved.

The invention provides a method for automatically calibrating collected data of high-precision measurement and control deformation monitoring equipment, and belongs to the technical field of wind tunnel inner profile measurement. Multi-equipment clock synchronization is realized by establishing a unified time reference system, and measurement data of different frequencies are processed by adopting a CPU-GPU heterogeneous parallel processing architecture, so that the measurement accuracy is improved. The method comprises the following steps: performing three-level alignment on time, space and precision dimensions by using a multi-level clustering algorithm, eliminating clock differences among equipment by using a clock drift correction equation set, establishing a space coordinate system conversion matrix to unify a global coordinate system, and performing adaptive data fusion according to a precision weight by using a Kalman filtering fusion algorithm. And a data quality evaluation system is established to ensure the accuracy of a calibration result, a high-precision calibration data set is finally output, and the technical problem that the measurement precision is reduced due to space-time inconsistency of heterogeneous data of multiple devices is solved.

The invention discloses a calibration method, system and device for a vehicle around-view camera and a computer medium, and relates to the technical field of image processing, and the method comprises the steps: collecting a calibration plate image obtained after a calibration plate is shot by the around-view camera on a vehicle; projecting the calibration plate image to a world coordinate system to obtain a distorted image; selecting an initial angular point in the distorted image according to the calibration plate; projecting the initial angular point to a fisheye image coordinate system of a look-around camera to obtain a target angular point; according to the target angular point, generating an initial external parameter of the look-around camera; in the calibration plate image, extracting overlapped corner point parameters in the overlapped shooting area; and based on the initial external parameter, generating a target external parameter which enables the error between the overlapping angular point parameters to be minimum, and taking the target external parameter as the external parameter of the surround-view camera. According to the method, the extraction precision and robustness of the angular points are improved, the continuity and smoothness of the images shot by the surround view camera are improved, splicing gaps and dislocation phenomena are reduced, and the calibration result of the vehicle surround view camera is more accurate.

The invention discloses a power transmission line fault positioning method and system based on ground potential end transient information perception, and relates to the technical field of line fault positioning, and the method comprises the steps: obtaining a voltage traveling wave signal and a current abrupt change rate signal detected by a trunk line and branch node sensor array in a power transmission line; processing the voltage traveling wave signal and the current abrupt change rate signal to obtain traveling wave components and polarity-amplitude calibration results of different modes; according to traveling wave components and polarity-amplitude calibration results of different modes, in combination with topological parameters of the power transmission line and spatial distribution of a ground potential end sensor, adjusting edge weights or connection relationships in the graph structure to obtain a composite feature matrix and an edge weight matrix of each node; and inputting the composite feature matrix and the edge weight matrix of each node into a graph neural network positioning model, and outputting a power transmission line fault positioning result. According to the invention, through ground potential end information fusion and the dynamic graph neural network, accurate fault positioning under a complex power transmission topology is realized.

The invention discloses a distributed flood forecasting scheduling model construction method based on sub-basins, particularly relates to the technical field of flood forecasting model optimization, and is used for solving the problem of local prediction failure due to spatio-temporal differences caused by neglecting parameter sensitivity of an existing flood forecasting model. A target drainage basin is divided into sub-drainage basins, hydrological and geographic feature parameters are extracted, and a cross-drainage-basin water conservancy facility topology network is constructed to dynamically correct river channel evolution boundary conditions; quantifying parameter sensitivity spatial diversity based on a Sobo index method, identifying a sensitive abnormal response region in combination with historical flood event distribution, and applying spatial lag correction through a river topology network to generate parameter sensitivity grade classification; constructing a dynamic weight matrix, and performing partition parameter calibration by adopting global optimization and local adjustment strategies respectively; and the hydraulic equilibrium constraint of the calibration result is verified based on the river topological relation, and a partition and grading flood discharge scheduling scheme is generated after iterative correction, so that the forecasting capability in a sudden flood scene is remarkably improved.

The invention relates to a CFD-based in-situ 3D printing shield secondary lining constructability optimization method, and belongs to the technical field of tunnel construction. The method comprises the following steps: constructing a joint simulation platform, calibrating the size of a single-layer secondary lining, establishing a CFD simulation geometric model, setting boundary conditions of a physical field, simulating a printing process, and optimizing a construction process based on a simulation result. According to the method, the quality source items of concrete layer-by-layer stacking in the in-situ 3D printing secondary lining process are loaded and simulated by configuring the UDF, and the single-layer secondary lining size calibration result is synthesized, so that the function relationship between the quality source items and absolute coordinates in a closed calculation domain is established; according to the in-situ 3D printing shield secondary lining construction method, the effect of multi-layer printing of fresh concrete along with movement of a spray head is simulated, the overall efficiency of modeling simulation is improved, good universality is achieved, and an in-situ 3D printing shield secondary lining construction scheme with higher constructability can be planned according to different tunnels.

The invention relates to the field of microscopic imaging, and discloses a miniature microscopic system optical precision improvement and image calibration error optimization method, which comprises the following steps: establishing an optical distortion model and a mechanical disturbance model, and respectively describing a static error and a dynamic error; constructing a joint dynamic error model, and uniformly expressing a coupling relationship between optical distortion and mechanical disturbance; decoupling and separating the joint error through a space-time separation method to obtain a static error component and a dynamic error component; performing iterative optimization on the optical distortion parameter and the mechanical disturbance parameter based on an optimization algorithm to minimize a system calibration error; a real-time sensor is utilized to obtain dynamic disturbance data, and real-time dynamic compensation is performed on an image calibration error in combination with an optimization result, so that a high-precision calibration result is obtained. The method can effectively improve the calibration precision of the microscopic system in a dynamic environment, remarkably improves the imaging quality of the system, and has a wide application prospect.

The invention discloses memory calibration with tolerance check. A memory subsystem includes a memory and a memory controller coupled to the memory. The memory controller includes a calibration circuit configured to: perform a horizontal memory calibration for some of a plurality of performance states during an initialization process; and determining information indicative of a set of differences between calibration results for pairs of performance states of the plurality of performance states and storing the information in a storage circuit. The memory controller is further configured to, after the initialization process and in response to a change from a first performance state of the plurality of performance states to a second performance state of the plurality of performance states, set an initial memory parameter for the second performance state based on the set of differences. Thereafter, operation begins in the second performance state without performing the initial level calibration.

The invention relates to the technical field of power system relay protection, and discloses a relay protection device mutual inductor adjustment system and method, and the system comprises a system connection initialization module, a data collection reference data generation module, a power frequency background signal offset module, a pilot frequency current injection error calibration module, and a calibration result verification output module. The method comprises the following steps: initializing sampling frequency of a to-be-calibrated mutual inductor and calibration source output precision of a calibration system, collecting amplitude and phase data of real-time power frequency current of the mutual inductor, generating offset current with equal amplitude and opposite directions through power electronic compensation based on reference data, optimizing offset current parameters through a closed-loop adjustment algorithm, and adjusting the offset current parameters through a closed-loop adjustment algorithm. Power frequency background signal offset is completed, pilot frequency calibration parameters are set, a difference value between a mutual inductor pilot frequency output signal and a calibration source standard signal is extracted by adopting a zero pointing technology, an optimal calibration coefficient is automatically calculated, verification of a calibration result is completed, and accuracy and reliability of the calibration result are ensured.

The invention provides an ultrasonic detection method and system for inverting residual stress by using sound wave phase velocity, and belongs to the field of air coupling ultrasonic guided wave detection. The method is based on an air coupling ultrasonic guided wave sound field propagation finite element model, and guides optimization design of air coupling ultrasonic transducer parameters. The air coupling ultrasonic guided wave detection technology is adopted for conducting non-contact excitation and receiving of guided wave signals on the composite material component with the preset stress through the stretcher. And calculating the phase velocity of the air-coupled ultrasonic guided wave in the composite material component based on a geometric positioning and time difference cooperative gradual difference method. And calibrating the phase velocity in the target composite material and preset stress to obtain a corresponding relational expression, performing phase velocity detection on a composite material component with unknown stress based on a calibration result of the target composite material, and performing inversion to obtain composite material construction residual stress. By adopting the method and the system, the residual stress detection of the composite material component is realized.

The invention discloses a calibration method, device and equipment for an external actuator of a robot, and the method comprises the steps: enabling the tail end of a mechanical arm with a calibration plate to be in contact with the actuator in different poses, and obtaining two different circular mark points and a preset transformation matrix; calculating a three-dimensional point cloud coordinate of the circular mark point based on a mapping relation between a pixel coordinate and a point cloud coordinate in the structured light system; calculating a pose transformation matrix between two poses at the tail end of the mechanical arm according to a preset transformation matrix; according to the three-dimensional point cloud coordinates, the pose transformation matrix and a preset hand-eye matrix, the actuator coordinates of the tail end of the actuator under the mechanical arm base coordinate system are calculated; direction vectors of the tail ends of the actuators are calculated through the coordinates of the two different actuators; and calculating a homogeneous transformation matrix calibrated and aligned at the tail end of the actuator according to the direction vector to obtain a calibration result. The technical problem that the actual calibration scene requirement is difficult to meet due to the problems of low precision, complex measurement process, high cost and the like in the prior art can be solved.

The invention belongs to the technical field of clock synchronization, and discloses a synchronous clock precision optimization method and device and electronic equipment, and the method comprises the steps: obtaining a first crystal oscillator frequency and environment parameters of a clock source; inputting the environmental parameters into a preset deviation prediction model to obtain a first deviation value output by the deviation prediction model; and performing compensation calibration on the first crystal oscillator frequency according to the first deviation value, and tracking time according to a compensation calibration result. By monitoring and compensating the influence of environmental parameters on the frequency of the crystal oscillator in real time, the precision and stability of the clock are remarkably improved. The dynamic compensation mechanism can adapt to environmental changes, the influence of external factors on clock precision is reduced, meanwhile, the dependence on expensive hardware is reduced, and the development and maintenance cost of the whole system is reduced. In addition, the method is realized through software design, can be easily integrated into an existing clock synchronization system, is simple in maintenance and updating process, and does not need complex hardware replacement or adjustment.