884 results about "Calibration result" patented technology

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 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 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 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 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 forest fire risk prediction method based on multi-source data, and belongs to the technical field of forest fire prevention. Aiming at the problem of low prediction precision caused by one-sided information of a single data source and insufficient multi-source data fusion in the prior art, the method is realized by the following steps: acquiring micrometeorological data including temperature and humidity, wind speed and air pressure, and image data including an infrared image and a visible light image; the data of the mountain fire-prone area comprises historical fire frequency, vegetation type and topographic information; uTC + 8 time synchronization and WGS84 coordinate system space calibration are carried out on the data, and missing values and abnormal values are processed; carrying out feature layer fusion by adopting an attention mechanism, and extracting core features such as a temperature and humidity coupling index and vegetation dryness; spatial correlation features are captured through CNN, a time sequence trend is captured through LSTM, a mountain fire occurrence probability is output by using a Sigmoid function after decision-making layer fusion, and a result is calibrated in combination with sub-region features. Through multi-source data deep fusion and spatial-temporal feature collaborative analysis, the accuracy and timeliness of forest fire risk prediction are improved, a new data source can be expanded and accessed, and the method is suitable for a complex forest fire prevention scene.

The invention discloses a dynamic adaptive black level correction method and device, and relates to the technical field of image processing. According to the dark current space distribution difference, an effective pixel area in each frame of original image is dynamically divided; determining an initial black level calibration coefficient of each space block based on the dark pixel noise level; obtaining the current temperature and the temperature change rate of each space block, and obtaining the level calibration coefficient of each space block after temperature self-adaptive calibration based on the initial black level calibration coefficient corresponding to each space block; fusing the calibration information of the previous frame and the level calibration coefficient of the current frame to obtain a cross-frame stable calibration result; and correcting the effective pixels in each space block based on a cross-frame stable calibration result to obtain a corrected pixel value, and reconstructing the corrected pixel value into an output image. The problems that an existing black level calibration technology is poor in space uniformity, insufficient in temperature change adaptability and unstable in calibration coefficient are solved.

The invention relates to the technical field of model parameter calibration, and provides a hydrodynamic model calibration method and system based on an improved particle swarm optimization, and the method comprises the steps: S1, obtaining the corresponding relation between the section information of a hydrodynamic model and the roughness; s2, defining a roughness parameter range and an allowable error range of each section; s3, initializing a particle swarm; s4, performing parallel scheduling hydrodynamic model calculation according to the matrix number of the particle swarm to obtain a simulation result data set; s5, performing time sequence comparison on a simulation result and an actual measurement result, and calculating an error value; s6, screening a calibration optimal solution, finding out a particle with the minimum error, and recording a corresponding roughness parameter; s7, judging whether the optimal solution is within an error range or not, if yes, directly executing the step S8, and if not, repeatedly executing the steps S4 and S5 until the optimal solution meets the condition; and S8, outputting a calibration optimal solution, and displaying a calibration result, an actual measurement result process line and optimal parameters. According to the invention, the calibration efficiency can be effectively improved.

The invention discloses a distributed hydrological model parameter two-stage calibration method based on remote sensing data and actually measured flow. The method comprises the following steps: collecting and preprocessing basic data required for constructing a distributed hydrological model, and remote sensing data and actually measured flow data for calibrating model parameters; constructing a distributed hydrological model, determining hydrological parameters needing to be calibrated in the model, and setting a value range of each parameter; performing grid-by-grid parameter calibration by utilizing remote sensing data to obtain model parameters with spatial heterogeneity characteristics; performing optimization adjustment on grid-by-grid model parameters based on remote sensing data calibration by utilizing actually measured flow data; and finally selecting a parameter combination with the optimal simulation precision as a finally determined model parameter for researching the drainage basin. Spatial distribution information of remote sensing data and time sequence precision of actually measured flow data are fused, and a multi-target calibration scheme considering parameter spatial heterogeneity and calibration result reliability is constructed.

The invention discloses an electric carbon coupling carbon flow calculation method, system and device and a medium. The method comprises the steps of obtaining a real-time power curve of a power transmission line and corresponding current, resistance and power factor multi-source operation data; segmenting the real-time power curve according to a time window, and extracting a power dynamic feature set in each time period based on a current change trend; calculating the energy loss of the power transmission line in each time period according to the multi-source operation data, and generating a carbon emission factor calibration result in combination with the difference between a reference carbon emission factor and the energy loss; determining a carbon flow attribution result of each power generation node in each time period based on the carbon emission factor calibration result and a power factor curve of the power generation node; and calculating a comprehensive carbon flow value of each power generation node, and summarizing to obtain a carbon flow calculation result of the power system. According to the method, the real-time performance, the accuracy and the physical consistency of carbon flow calculation are remarkably improved.

The embodiment of the invention discloses a three-dimensional tennis track real-time reconstruction method and system based on multiple cameras, internal and external parameters and calibration results of the multiple cameras are utilized, respective two-dimensional pixel coordinates are converted into three-dimensional rays, and nodes are positioned in combination with a minimum distance algorithm. According to the embodiment of the invention, the real-time reconstruction of the three-dimensional track of the tennis ball is realized by virtue of the synchronous multi-camera two-dimensional image through the steps of camera accurate calibration, two-dimensional to three-dimensional ray conversion, intersection point calculation and screening, data output and the like. Compared with the prior art, the reconstruction precision is improved through accurate calibration and ray intersection screening; by means of multi-camera data synchronization and simple calculation process, data delay is reduced, and real-time performance is prominent; by means of multi-camera data redundancy and a placeholder mechanism, the robustness in a complex environment is enhanced; the output three-dimensional point data can directly support the functions of ball speed calculation and the like, and the expansibility is good.

The invention relates to a calibration method of a binocular camera and a laser radar based on a hollow ellipse calibrator, and belongs to the field of robot vision. Hamming code graticule marks are respectively arranged at four corners of one side face of a square aluminum plate of the hollow elliptical calibrator in the clockwise direction, an elliptical through hole is formed in the middle of the hollow elliptical calibrator, and the center of the elliptical through hole coincides with the center of the square aluminum plate; and the long axis of the elliptical through hole is positioned in the vertical direction. A hardware system of the calibration method comprises a binocular camera, an upper computer, a 16-line laser radar and a hollow ellipse calibrator. An image processing program, a three-dimensional point cloud processing program and a mathematical calculation program are arranged in the upper computer; the calibration method comprises the following operation steps: (1) carrying out image feature recognition on the hollow ellipse calibrator; (2) carrying out point cloud feature recognition on the hollow ellipse calibrator; (3) calculating external parameters of the camera and the 16-line laser radar; and (4) determining a calibration result. According to the calibration method, the calibration accuracy and robustness are improved, and the calibration method is suitable for practical application.

The invention provides a calibration assembly and a four-wheel positioning calibration device.The calibration assembly comprises a calibration base body and a plurality of calibration assemblies, the calibration base body defines at least two calibration directions parallel to the calibration base body, the calibration assemblies are arranged on the calibration base body, and projections of the calibration assemblies in the calibration directions do not coincide with one another; and the heights of the plurality of calibration assemblies on the calibration seat body are different. According to the technical scheme, the calibration seat body is provided with the plurality of calibration assemblies of which the projections in the calibration direction do not coincide, so that the four-wheel positioning measurement device can obtain the images of the plurality of calibration assemblies in the calibration direction, and the images of the plurality of calibration assemblies can provide more coordinate values for mutual calibration; therefore, the accuracy of the calibration result is improved, and the accuracy of the tire positioning information detected by the four-wheel positioning measurement device is further improved.

The invention relates to a double-robot automatic calibration method based on self-adaptive point location planning in a restricted space, and belongs to the technical field of double-robot calibration, and the method comprises the steps: building a three-dimensional simulation model of a double-robot operation space on an Rviz platform based on an ROS architecture; a collision detection module is used for randomly generating a calibration point composed of collision-free double-robot joint angle vectors; when the robot is driven to move, data of the motion capture camera and positive kinematics Cartesian coordinates of the double robots are synchronously collected, a calibration result is obtained through optimization of a least square method by adopting a hand-eye calibration algorithm, and the effectiveness of the calibration result is judged through the average value of data calibration precision until calibration of the double robots is completed. Simulation modeling, collision detection and a hand-eye calibration technology are fused, a complex calibration problem is converted into a virtual environment parameter optimization process through a self-adaptive sampling strategy and a data synchronous acquisition mechanism, calibration robustness and precision are remarkably improved, and guarantee is provided for high-precision cooperative control of double robots.

The invention provides a three-dimensional calibration method using a speckle image as a calibration object and combining weight parameters. The method comprises the following steps: acquiring a standard grid image and the speckle image through a camera; determining angular point positions in the standard grid image through an angular point detection algorithm; calibrating the stereoscopic vision system by using the obtained angular points to obtain an initial calibration result; calculating 3D coordinates of the camera calibration board in the world by using the disparity map; determining a subset of the reference image corresponding to the checkerboard angular points in the target image through a digital image cross-correlation algorithm; calculating a weight parameter of each calibration point based on the re-projection error; solving internal and external parameters of the camera by using the weight parameters, radial alignment constraint and a least square method; optimizing the main point of the camera by using the weight parameters; and if the re-projection error or the number of iterations does not meet the requirement, repeatedly calculating the weight parameter of the calibration point and the subsequent steps, otherwise, obtaining a camera calibration result, and obtaining the distortion curved surface of the camera lens.

System, methods, and computer-readable media for extrinsically calibrating sensors on an autonomous vehicle (AV) by leveraging map data. By leveraging offline data, such as the map data on the AV, the extrinsic calibration of the sensors may be performed on road to update or check previous calibrations. Static objects are determined in the scene by leveraging a map with a semantic map layer and sensors are extrinsically calibrating using a portion of a set of static points associated with the determined static objects by determining relative positions and angles the sensors.

The invention provides a hand-eye calibration joint optimization method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring multi-frame calibration data; a parameterization method is adopted, the pose error of each frame of the end effector is modeled into an independent rigid body transformation, and the pose error of each frame obtained through parameterization modeling, a hand-eye transformation matrix, the pose of a calibration object in a world coordinate system and transformation from the world coordinate system to a base coordinate system serve as target parameters; establishing a parameterized joint model taking object-base pose consistency constraint, frame-by-frame error constraint of end effector pose error and re-projection error constraint as a first objective function; and according to the initialized target parameters, the multi-frame calibration data and the parameterized joint model, optimizing the target parameters by minimizing the first target function, and performing global error estimation of the pose of the end effector through global fusion to obtain a hand-eye calibration result. According to the invention, the hand-eye calibration precision and robustness are improved.

The invention discloses a differential pressure sensor precision calibration method for high-temperature environment monitoring, and relates to the technical field of sensor calibration, and the method comprises the steps: carrying out the high-temperature factor extraction and simulation parameter design of the application scene information of a differential pressure sensor, and obtaining a high-temperature test parameter table of the sensor; a standard differential pressure source is arranged in the high-temperature environment controllable simulation chamber; acquiring a multi-high-temperature parameter differential pressure test data set of the standard differential pressure source; establishing a multi-high-temperature parameter differential pressure compensation model set; obtaining a high-temperature calibration coefficient differential pressure compensation model set; and performing calibration matching calibration on the application scene information of the differential pressure sensor to be calibrated to obtain a differential pressure sensor precision calibration result. The technical problem that the measurement precision and stability of the sensor are poor due to the fact that the measurement precision of the differential pressure sensor is difficult to effectively calibrate in the high-temperature environment in the existing differential pressure sensor precision calibration is solved, and the technical effects of improving the measurement precision of the differential pressure sensor and improving the measurement stability and reliability are achieved.

The invention discloses an optimization method for vibration performance of an automobile lamp. The optimization method comprises the following steps: S101, establishing a finite element model of the lamp and performing modal analysis; and S102, carrying out a modal test by using the lamp. And S103, comparing a modal analysis result in the step S101 with a modal test result in the step S102, confirming a vibration mode and calibrating the finite element model. And S104, submitting modal calculation according to a calibration result, completing boundary condition setting, and performing random vibration simulation. And S105, carrying out a random vibration test on the lamp by using the PSD power spectrum. And S106, comparing a random vibration simulation result in the step S104 with a random vibration test result in the step S105, confirming the reliability of the model and correcting the finite element model. And S107, determining a dangerous area according to a vibration test result and a vibration simulation result, and checking a risk point optimization data structure. And S108, modifying data according to an optimization result, verifying a random vibration simulation result of the new model, and performing vibration test retest after confirming feasibility.

The invention discloses an aerated building block geometric dimension intelligent detection method based on three-dimensional point cloud reconstruction, and the method comprises the steps: collecting and processing multi-view point cloud data, and generating a complete point cloud data set covering six surfaces; executing self-reference calibration based on hexahedron features, and generating a standardized point cloud data set; inputting the multi-modal input into an improved SegFormer model, extracting geometric features and calculating a variance; executing weighted segmentation and topological optimization based on the geometric features, and outputting geometric parameter data; calculating the geometric dimension of the aerated building block, and combining the spatial covariance to generate a precision calibration result; and fusing variance information to establish a space-time coupling judgment mechanism, and outputting a detection report and a detection result. According to the method, through fusion of improved SegFormer dynamic geometric semantic modeling, geometric entropy driving topology correction and a space-time coupling tolerance judgment mechanism, high-precision three-dimensional point cloud reconstruction and intelligent geometric dimension detection of the complex surface of the aerated building block are realized.

The invention relates to the field of hydrological forecasting, and discloses a distributed hydrological model construction method, system and equipment based on feature units, and the method comprises the steps: building a session flood historical data set according to the collected topographic data, soil data, hydrological data and meteorological data, dividing the topographic data in the session flood historical data set into feature units, the other soil data, hydrological data and meteorological data are matched to each feature unit, and a spatial topological relation is constructed based on the feature units; constructing a distributed hydrological model based on the spatial topological relation to calibrate runoff production model parameters, and calibrating confluence model parameters according to a runoff production model parameter calibration result; and according to a parameter calibration result, various monitoring and forecasting information and different levels of flood early warning release standards, manufacturing and releasing flood early warning information. According to the method, the distributed hydrological model is constructed based on the feature units, and real-time flood operation forecasting can be carried out.

The invention relates to the technical field of electronic measurement, and discloses a software instrument system-based short-wave broadcast equipment power automatic calibration system, which comprises a main control unit, a signal excitation unit and a measurement feedback unit. According to the method, an iterative adjustment process is controlled through a main control unit; a measurement feedback unit measures the actual output power of a measured device; and the main control unit directly takes the power difference value as the adjustment amount of the excitation level according to the power difference value between the actual output power and the preset target power, adds the adjustment amount with the current excitation level to obtain the next excitation level, and controls the output of the signal excitation unit until the preset precision is met. According to the method, test link loss calibration is executed before iterative adjustment so as to compensate system errors, a calibration lookup table can be automatically generated after calibration is completed, the problems that a traditional calibration method is low in efficiency and insufficient in precision are solved through an adaptive adjustment strategy and system error compensation, and the calibration accuracy is improved. The method has the beneficial effects of high convergence speed, accurate calibration result and high automation degree.

The invention relates to the technical field of sound correction, and discloses a room sound calibration method based on listening tendency control and related equipment, which are used for improving the matching degree of a calibration result and listening preference of a user. The room sound calibration method based on listening tendency control comprises the following steps: obtaining a listening tendency parameter selected by a user through an interactive interface and a room pulse response of a current room; determining a group of frequency-related window control parameters according to the hearing tendency parameter and the room pulse response; determining a windowing strategy with the window length changing along with the frequency based on the window control parameters; windowing the room impulse response by using a windowing strategy to extract an effective frequency response curve for acoustic calibration; calculating according to the difference between the effective frequency response curve and the target frequency response curve to obtain a correction filter coefficient; and calibrating the audio signal of the audio playing system based on the correction filter coefficient.

According to the metering detection calibration method and system, the dynamic waiting time is determined on the basis of the characteristic relaxation time of the instrument to be calibrated, and data is recorded after output is stable, so that the problems that the traditional fixed waiting time cannot adapt to the relaxation characteristic of the instrument, and data instability or low efficiency is easily caused are solved; the instrument is ensured to be fully stable so as to improve data reliability, and waiting time redundancy is avoided; and meanwhile, the equivalent effective times are calculated by combining the actual retention time after the output value is stabilized and the characteristic relaxation time of the instrument to be calibrated, and a final calibration result is obtained by adopting a statistical method for dynamically quantifying the data contribution degree, so that the problems that the existing equal weighting or manual weighting mode is strong in subjectivity and is difficult to reflect the real reliability of the data are solved. And the accuracy and objectivity of the calibration result are improved.

The invention discloses a calibration method and system based on multi-scale feature fusion and an adaptive optimization algorithm, and belongs to the technical field of computer vision. The method comprises the following steps: collecting a plurality of images containing calibration modes; detecting and positioning feature points by adopting a multi-scale feature fusion technology, and distributing a confidence score for each feature point; carrying out feature point matching and removing abnormal values by using an improved RANSAC algorithm based on the prior geometrical relationship and confidence score; preliminarily calculating camera parameters; and a nonlinear optimization model fusing confidence weighting and adaptive regularization is constructed, joint optimization is performed on camera parameters, and a high-precision calibration result is output. According to the method, through an optimization mechanism of multi-scale feature fusion and confidence guidance, the problems of unstable feature point detection, abnormal value sensitivity and insufficient precision of a traditional method in a complex environment are effectively solved, and the accuracy, robustness and automation degree of image calibration are remarkably improved.

The invention discloses a water conservancy intelligent model evaluation method and device based on a large language model, equipment and a medium, and relates to the technical field of computers, and the method comprises the steps: verifying evaluation data of the water conservancy industry to determine target data; based on the to-be-evaluated water conservancy intelligent model and the target data, utilizing the evaluation case library to generate an evaluation task, performing preliminary evaluation on the evaluation task, performing collaborative calibration on the obtained preliminary evaluation result, and utilizing the obtained target optimization rule to optimize the target large language model to obtain a first optimized large language model; determining an updating strategy based on the target updating signal, verifying and evaluating a preset reference water conservancy intelligent model in combination with the first optimized large language model, and optimizing the first optimized large language model based on a target evaluation result and a calibration result, and evaluating the water conservancy intelligent model to be evaluated by using the obtained second optimized large language model to obtain a model evaluation result. And the evaluation result better meets the actual engineering requirements.

The invention discloses a vehicle distance measurement and calibration method based on laser radar and binocular vision fusion, relates to the technical field of measurement and calibration, and is used for solving the problem that the precision of a vehicle distance calibration result is reduced when a laser radar used for calibrating a highway vehicle distance snapshot system is under the conditions of rain, snow, wet and slippery or waterlogging road surfaces. Joint modeling is carried out on spatial distribution and echo energy characteristics of laser radar low-height point cloud, a point cloud echo coefficient and a low-height number proportion are introduced, a specular reflection state code is constructed, a self-calibration mechanism is adaptively triggered accordingly, and a specular reflection state is obtained. The discrete characteristic of a laser radar vehicle distance time sequence and the degradation trend of binocular vision parallax connectivity are subjected to quantitative analysis, the dominant source of ranging abnormity is judged through symbolic analysis, and an offset calibration or fusion correction strategy is selected according to the dominant source. Reliability and engineering adaptability of vehicle distance measurement under the wet and slippery road surface condition can be improved under the condition of not depending on an additional sensor.