1240 results about "Observation point" patented technology

The invention discloses a matrix layout illumination state detection method, device and equipment, and the method comprises the steps: collecting and analyzing a power supply bus current waveform and a single lamp feedback signal, and generating a node feature cluster; extracting a power consumption difference value of adjacent lamps, identifying an abnormal observation point and constructing a fault diffusion chain; marking a timestamp for the fault diffusion chain, determining a fault source, and marking current by injecting characteristics to delimit an influence domain; deploying monitoring anchor points at the boundary of the influence domain, collecting the light color parameter variation and predicting the residual life; extracting the oscillation envelope of the starting current peak, evaluating the health degree of the driver and generating a maintenance density field; and a three-dimensional detection field is constructed by fusing multi-dimensional detection data, singular points are searched, and coordinates of a fault lamp are accurately analyzed through fault positioning pulses. According to the invention, three-dimensional monitoring from electrical characteristics and optical performance to driver states is realized, a single lamp fault can be accurately positioned, a life trend can be predicted, fault propagation can be tracked, and technical support is provided for intelligent operation and maintenance of a large-scale illumination system.

The invention discloses a river and lake water level and flow prediction method and system in the field of remote sensing hydrology and hydraulic engineering, and the method comprises the steps: obtaining satellite radar altimeter data, river and lake water system data, rainfall inversion data and surface temperature inversion data based on a target river, a target lake and a watershed range file; taking the cross interval as a virtual hydrometric station observation point, extracting and processing waveform data, calculating water surface elevation information through a wavelet tracking algorithm, constructing an elevation profile group to establish an initial water level time sequence, and generating a river and lake water level inversion data set through fitting and elevation reselection. Meanwhile, NDWI data are obtained from satellite radar altimeter data, water surface width data are extracted, an inversion data set is formed by combining actually-measured river channel section data and a Manning formula inversion river channel flow rate, and finally various kinds of data are input into a pre-constructed intelligent prediction model to obtain future river and lake water level and flow rate change conditions. According to the invention, the precision of river and lake water level and flow prediction in areas lacking data is effectively improved.

A slope monitoring method based on optical flow estimation and binocular vision belongs to the technical field of deformation monitoring and measurement, and adopts the technical scheme that a binocular stereoscopic vision system is built, and camera acquisition parameters are calibrated; transmitting the image to a server in real time through the Internet of Things; distortion correction and stereo matching are carried out to obtain a depth map; monitoring points are manually or automatically arranged on the corrected image, and dense optical flow estimation tracking pixel point movement is carried out; world coordinates of observation points and movement conditions of each frame are obtained, and displacement changes of slope monitoring points are obtained by combining coordinates before and after displacement; and obtaining a displacement rate by combining monitoring time and displacement, judging slope safety, obtaining a displacement track, and performing linear interpolation to obtain a slope deformation cloud picture, thereby realizing the monitoring purpose. The slope displacement monitoring method has the advantages that slope monitoring can be carried out more flexibly and efficiently, the safety of workers is improved, the slope monitoring cost is reduced, real-time slope displacement monitoring is achieved, and the intensive degree of slope monitoring points is greatly improved.

The invention provides a mobile robot active positioning method and device for an indoor dynamic scene, and the method comprises the steps: collecting indoor environment data, and constructing an indoor global map which comprises the geometric structure and semantic information of an environment; sensing data collected by the mobile robot in real time are matched with an indoor global map, the pose of the mobile robot in the three-dimensional space is estimated in real time, and the uncertainty index of pose estimation is calculated; evaluating information gains of different potential observation points based on uncertainty indexes of pose estimation, and selecting the observation point with the maximum information gain as a candidate target point; planning a path to the candidate target point; the mobile robot collects sensing data at the candidate target points, the sensing data are matched with the indoor global map again, and the pose of the mobile robot is updated; the indoor environment change is monitored in real time, the indoor global map is dynamically updated, and the indoor global map is regularly corrected and optimized.

The invention belongs to the field of remote sensor calibration, and provides an ROLO model improvement method combining foundation and meteorological satellite lunar observation data, which comprises the following steps of: acquiring a meteorological satellite lunar observation image data set and a foundation lunar observation image data set, and respectively correcting the meteorological satellite lunar observation image data set and the foundation lunar observation image data set; obtaining standard meteorological satellite observation moon radiance and foundation observation moon radiance, and calculating observation moon irradiance; calculating geometric parameters of observation points, the earth, the moon and the sun at the observation moments of the foundation and the meteorological satellite, and calculating the moon irradiance of the ROLO model; polynomial fitting is adopted for the relative deviation between the observed moon irradiance of different wave bands and different moon phase angles and the moon irradiance of the ROLO model, and the ROLO model is improved. The method is not affected by the atmosphere, and errors caused by atmospheric correction of ROLO model foundation observation data are directly avoided; and the phase angle dependence of the ROLO model can be corrected, and the prediction precision of the ROLO model can be improved.

The invention relates to the technical field of geophysics, and particularly discloses a comprehensive inversion method and system based on bidirectional magnetic susceptibility weighted constraint, and the method comprises the steps: dividing an underground three-dimensional space, and building two different cuboid models; determining a total magnetic field observed on the ground and gradient anomaly thereof based on the observation point coordinates and the cuboid model position, and establishing a kernel function matrix; determining an inversion objective function reflecting the relationship between the total magnetic field and the gradient anomaly thereof and the physical property parameters; adding the bidirectional magnetic susceptibility weighted constraint function into an inversion objective function; the optimal solution of the comprehensive inversion target function is solved based on the conjugate gradient method, the high-level resolution capability of the magnetic gradient data and the deep detection advantage of the total magnetic field data are fused, the precision of fine depiction of the superficial anomalous body boundary and the reconstruction precision of the deep field source structure are remarkably improved, a vector cross multiplication regularization constraint mechanism is introduced, and the method has the advantages of high resolution and high resolution. The inversion multiplicity under the complex geological condition is greatly inhibited, and the reliability of the model result and the geological rationality are enhanced.

The invention provides a transformer substation unmanned aerial vehicle three-dimensional route real-time planning and autonomous obstacle avoidance system, and relates to the technical field of non-electrical variable control or adjustment systems. Through cooperative work of a navigation mode switching module and a near-field navigation control module, an electric field of equipment is used as a natural navigation beacon; and high-precision autonomous flight is realized in a strong electromagnetic interference area with RTK signal failure, and the dependence on external positioning is eliminated, so that the inspection blind area is eliminated. Meanwhile, a fusion environment map containing multi-physics field information is constructed, the value of observation points is scientifically quantified according to waypoint inspection efficiency indexes, and a path planning algorithm aims at optimizing a comprehensive target fusing energy consumption, risks and inspection efficiency. The design not only ensures that the unmanned aerial vehicle can safely get close to the core equipment, but also enables the planned route to be the most valuable path rather than the shortest path, and finally fundamentally improves the safety, the operation efficiency and the data validity of substation inspection.

Provided is an image generation device which detects an obstacle that is present in the surrounding space, on the basis of a captured image obtained by a stereo camera of a head-mounted display, and sets a boundary 72 of a play area in which a user wearing the head-mounted display is allowed to move. When a new obstacle is detected inside the play area, the image generation device generates tangent lines 82a and 82 from an observation point H on a floor surface to a contour 80 of the obstacle and uses the tangent lines and a portion which is a part of the contour 80 and which is between tangent points AB to set a new boundary 86 of the play area.

The invention discloses a real-time dynamic trajectory tracking method and system for millimeter wave radar gesture recognition, and relates to the technical field of gesture recognition tracking, and the method comprises the steps: receiving an echo signal reflected by a gesture, extracting a potential target point cloud, and carrying out the clustering generation of a gesture point cloud sequence; establishing a multi-modal motion model library, dynamically selecting an optimal motion model by adopting graph matching, and generating a prediction state in combination with a gesture point cloud sequence; on the basis of a Poisson multi-Bernoulli hybrid filtering framework, according to the signal-to-noise ratio and spatial distribution of the current gesture point cloud sequence, dynamically adjusting the observation weight, optimizing the observation point cloud, and carrying out optimal association by combining Mahalanobis distance with dynamic time warping; a multi-hypothesis tracking strategy is adopted to maintain trajectory hypothesis, an optimal trajectory is selected through a trajectory scoring mechanism, and Kalman filtering smoothing processing is performed on the optimal trajectory. According to the method, high-precision and low-delay tracking of gesture motion is realized, gesture habits of different users and complex environment interference can be adapted, and meanwhile, relatively high track precision is kept.

The embodiment of the invention provides a multi-element deep learning correction method and device for numerical mode forecasting. The method is applied to the technical field of data processing, and comprises the following steps: marking observation points, and performing loss function construction on the positions of the observation points to obtain a model optimization target; carrying out iterative updating on model parameters, and carrying out training process optimization by adopting a dynamic learning rate adjustment strategy to obtain a forecast field correction model; and applying the prediction field correction model to target numerical mode prediction data acquired in real time, performing prediction effect evaluation, and performing standardization processing and anti-standardization processing to obtain a correction prediction result. According to the method, the information extraction capability of a deep learning visual algorithm model is utilized, fine deviation correction of data of a numerical mode forecast space grid by meteorological station observation data is completed, meanwhile, multiple types of meteorological elements are fused, the deep learning model is utilized to learn mutual influences and restrictions between related elements, and the prediction precision of the numerical mode forecast space grid is improved. And finer deviation correction is completed.

The invention discloses an oil reservoir production dynamic prediction method fusing discrete gradient information, and belongs to the technical field of oil reservoir development and artificial intelligence crossing, and the method comprises the steps: building a heterogeneous oil reservoir oil-water two-phase flow numerical simulation data set based on a numerical simulation method; designing a double-branch network structure and extracting spatial and physical characteristics of input field data in parallel, wherein the spatial and physical characteristics comprise a main characteristic coding branch and a differential operator branch; designing a backbone network to carry out deep nonlinear modeling; an efficient pressure and saturation field prediction neural network model is constructed based on a double-branch network structure and a backbone network, in a model training stage, spatial region observation points of part of time steps are used to participate in data item loss calculation, and meanwhile, physical control equation residuals are introduced into all time steps and a whole space to serve as physical loss items; a trained efficient pressure and saturation field prediction neural network model is obtained, and high-precision prediction of a full-time-sequence pressure field and a saturation field is achieved.

The invention discloses a pollution source dynamic tracing method and equipment for industrial park hidden gas leakage. Comprising the following steps: acquiring meteorological monitoring data at each observation point through fixed monitoring equipment and / or mobile monitoring equipment; correcting the coordinates of the observation points; predicting a first gas pollutant predicted concentration corresponding to each observation point after coordinate correction according to a Gaussian plume diffusion model; inputting the first gas pollutant predicted concentration and meteorological monitoring data into a CatBoost model to obtain a second gas pollutant predicted concentration; taking the difference between the actual gas pollutant concentration at each observation point and the second gas pollutant predicted concentration as a target function, and solving the target function to obtain the pollutant source intensity and the source position; completing one iteration; and setting the observation point near the current predicted pollutant source position, and so on, and obtaining the final pollutant source intensity and source position after n iterations.

The invention discloses a dual-band InSar and GNSS fused high-precision three-dimensional deformation adaptive monitoring method, and the method comprises the following steps: constructing a dual-band observation equation, and decomposing the dual-band observation equation to obtain a dual-band InSAR resolving residual error; calculating the comprehensive weight of each GNSS observation point through an entropy weight method, selecting a plurality of GNSS observation points with high comprehensive weights as an optimal GNSS reference point combination, and converting the three-dimensional deformation observed by the optimal GNSS reference points into an LOS direction; expanding a two-dimensional radial basis function to a three-dimensional radial basis function, optimizing the number and distribution of the three-dimensional radial basis function according to the residual drop rate in the expansion process, and performing basis function encryption on the key area by combining the LOS direction result of the reference point; an original two-dimensional state equation in a Kalman filtering algorithm is expanded to be three-dimensional, meanwhile, a GNSS three-dimensional observation value serves as a strong constraint condition of the Kalman filtering algorithm, and a final three-dimensional deformation rate field is output through iteration and 3D-Va analysis.

The invention discloses a bridge tower section attitude intelligent prediction method and system based on multi-point cooperative localization, and the method comprises the steps: S100, selecting a plurality of observation points on two adjacent side surfaces of an installed section, obtaining the space coordinates of the observation points through a laser reflector, and carrying out the cooperative measurement through a plurality of total stations; s200, performing attitude change prediction on the to-be-installed segment based on the rigid body transformation mathematical model, calculating the optimal attitude of the to-be-installed segment by using a rotation matrix and a translation vector, optimizing attitude estimation by excessive-point redundant information, and controlling an accumulative error; s300, performing BIM modeling on the bridge tower structure, performing high-precision three-dimensional rendering, converting complex monitoring data into a visual graphical interface, and displaying a segment state in real time; s400, according to data comparison, analysis is carried out in combination with errors, and if the errors with design data are large, corresponding adjustment is carried out; and S500, the steps are repeated till all the bridge tower sections are accurately positioned and installed. And the erection precision and the construction efficiency of the bridge tower sections are improved.

The invention discloses a natural resource supervision method based on three-dimensional GIS scene and video fusion, and relates to the technical field of intelligent natural supervision. Comprising the steps of collecting a video stream through a preset observation point, extracting a continuous frame sequence, and calling a space parameter set; performing dynamic region detection on the video frame sequence to generate change feature data; mapping the change characteristic data into a topological structure to be updated based on the projection matrix; calling a pre-constructed three-dimensional GIS scene model, and positioning an update area; according to the type identifier of the change feature data, executing an operation of deleting the associated geometry or constructing and fusing a new geometry; adding a state attribute label to the updated geometry, and storing an update model; the resource change rate is calculated, and when the change rate exceeds a preset industry threshold value, an early warning instruction is generated and pushed to the control terminal. And the space accuracy, the model updating efficiency and the early warning reliability of resource change identification in a complex natural scene are remarkably improved.

The invention relates to the technical field of radio, and particularly discloses a high-precision electromagnetic spectrum map construction method and system for a topographic relief environment, and the method comprises the steps: obtaining spectrum data in a to-be-constructed region, the spectrum data comprising signal intensity and geographic position; combining terrain digital elevation and topographic relief elevation information in a to-be-constructed region with the signal intensity, and matching with an observation point according to resolution to obtain topographic relief elevation information of the observation point; establishing a model for the topographic relief elevation information of the observation point based on a Gaussian regression process, and performing parameter optimization on the model by using hyper-parameters of a kernel function; and according to a posterior probability estimation formula of the Gaussian regression process, constructing a spectrum map of the to-be-constructed region by using the monitoring value of the spectrum data in the to-be-constructed region as input.

The invention relates to a photoelectric pod air target correction method based on target information, which comprises the following steps: before an aircraft takes off, measuring the geographic position of a selected target point, after the aircraft enters an airline, observing and aiming a target in the intervals of 0-90 degrees, 90-180 degrees,-90-0 degree and-180--90 degrees of the azimuth of a photoelectric pod respectively, and after the aircraft enters the airline, observing and aiming the target in the intervals of 0-90 degrees, 90-180 degrees,-90-0 degree and-180--90 degrees of the azimuth of the photoelectric pod; the current inertial navigation information and the GPS geographic position are recorded at each observation point through a ground snapshot instruction, target correction acquisition point collection is completed after target observation of each azimuth angle under each quadrant is completed, the installation deviation angle of the photoelectric pod and the aircraft inertial navigation is calculated, the installation deviation angle is written into a pod EEPROM to be stored, and the installation deviation angle of the photoelectric pod and the aircraft inertial navigation is obtained. In a word, the method is suitable for all ground station systems and airplanes with air boresight conditions, and has the advantages of low cost, short time, convenience in use and capability of ensuring the correction precision of the installation deviation angle.

The invention discloses a 3D GS cultural relic digital reconstruction method and system based on a block chain, and the method comprises the steps: collecting the RGB image data and depth perception data of a cultural relic, eliminating the influence of different shooting conditions through an illumination separation processing technology, and building a standardized image data set; recognizing a surface area suitable for reconstruction based on image analysis, determining feature point distribution by using kernel density estimation, and generating initial three-dimensional representation through Gaussian ellipsoid fitting; performing gradient calculation and feature extraction on the depth data, and combining with Gaussian representation to form a geometric constraint mechanism; self-adaptive encryption based on visual importance is executed for a sparse region, and a layered rendering effect is achieved through opacity parameter adjustment; the rendering characteristics and the conversion relation of different view angles are analyzed, key observation points are determined through stability analysis, and a smooth multi-view-angle display sequence is constructed; and integrating multi-view rendering information to generate volumetric representation, and completing right confirmation of the high-quality three-dimensional digital model through digital signature.

A light absorption probe includes an arm segment, a main segment located at one side of the arm segment, a testing segment connected to another side of the arm segment, and a light absorption coating layer. The main segment has a soldering end portion and an extending end portion respectively located at two opposite sides thereof along a predetermined direction. The testing segment has an upright shape along the predetermined direction and includes a pinpoint portion and an upright portion that connects the pinpoint portion and the arm segment. The light absorption coating layer covers the upright portion, and the pinpoint portion is exposed from the light absorption coating layer. Through the light absorption coating layer, the testing segment only forms an observation point at the pinpoint portion in an observation process of a detection apparatus.

The invention provides an illumination rendering method for a game scene and electronic equipment, and belongs to the technical field of global illumination. According to the method, the voxelization processing area is determined based on the observation point, only voxelization processing needs to be carried out on the scene in the limited range around the observation point, the calculation complexity can be greatly reduced, and memory resource occupation is reduced; tasks are distributed through a main thread, and a plurality of background threads execute voxelization processing in parallel, so that the utilization rate of a GPU can be improved, and blockage of the main thread can be avoided; by determining the processing priority of the voxel blocks, the voxel blocks which greatly influence the picture effect can be processed preferentially, real-time updating of the illumination effect of the central area of the visual field of a player is ensured, and delay or distortion of the key area of the picture is avoided.

The present invention provides a method, device, and system for tracing the source of atmospheric pollutant emissions. The method comprises: obtaining tracer observed concentrations and pollutant observed concentrations at multiple observation points within a predetermined time range; determining the atmospheric diffusion coefficient and ground reflectance coefficient of a target Gaussian model based on the tracer observed concentrations at the multiple observation points; generating an initial chromosome population, and determining the fitness of each initial chromosome in the initial chromosome population based on the atmospheric diffusion coefficient, ground reflectance coefficient, the pollutant observed concentrations at the multiple observation points, and the target Gaussian model; determining a target chromosome population based on the fitness of each initial chromosome, and determining the emission source location and / or emission rate of the target pollutant based on the target chromosome population. Embodiments of the present invention can effectively improve the accuracy of tracing the source of atmospheric pollutant emissions.

The invention relates to the technical field of illumination angle adjustment, in particular to a tea table illumination angle adjustment control method and system, and the method comprises the following steps: obtaining optical reflection characteristic data of a desktop area, three-dimensional geometric data of an article and user observation point information, and constructing a space model for illumination evaluation; when it is monitored that the desktop environment changes, the changes include that an object enters an unstable state, whether the illumination state touches a preset judgment threshold value or not is evaluated based on the current light source projection angle, and the judgment threshold value comprises a glare threshold value, an illumination uniformity threshold value and a secondary reflection avoidance threshold value; if any judgment threshold value is touched, re-calculation and adjustment of the current light source projection angle are started; and if any judgment threshold is not touched, the current light source projection angle is maintained. The problems of glare, uneven illumination, secondary reflection and the like are effectively solved, and the visual comfort of a user is improved.

The invention relates to the technical field of harmonic intelligent positioning, and discloses a coupling harmonic intelligent positioning method and system based on multi-modal fusion, and the method comprises the steps: obtaining the voltage amplitude time sequence data of each observation point, constructing a frequency distribution characteristic curve, and extracting a frequency center and a broadening parameter; parameter updating is realized in combination with priori information of power grid impedance, and an adaptive frequency analysis window is constructed on this basis to extract energy distribution characteristic quantity; the reliability weight of an observation point and the time sequence weight of harmonic source equipment are further introduced, and the dynamic characteristics of the space credibility and the operation state are comprehensively reflected; and finally, taking the two types of weights as weighting factors, carrying out weighted calculation on the harmonic propagation model deviation of the candidate nodes to obtain a comprehensive residual value, and positioning the node with the minimum comprehensive residual value as a coupling harmonic source node, thereby remarkably improving the accuracy of harmonic source positioning in a complex power grid environment.

The invention relates to the technical field of wind field construction, and provides a low-altitude three-dimensional real-time wind field construction method and system based on unmanned aerial vehicle data inversion, and the method comprises the steps: collecting the multi-dimensional data of a flight attitude, a power system, navigation positioning and the like in real time through an unmanned aerial vehicle group in the process of executing a distribution task; and extracting key indexes such as attitude change features, control response deviation features, energy consumption features and the like from the data, inputting the features into a deep neural network with a physical model as a constraint to carry out wind field inversion training, and finally carrying out multi-scale spatio-temporal interpolation on discrete observation points through a Gaussian process regression algorithm fused with the physical constraint. And generating continuous three-dimensional wind field distribution meeting the law of conservation of mass. Dynamic wind field monitoring under urban complex terrains is realized by utilizing the characteristics of high-frequency and wide-coverage operation of the unmanned aerial vehicle, and the problem of insufficient observation data of a traditional weather station in a building dense area is effectively solved.

The invention relates to the technical field of power systems, and provides a power transmission line lightning stroke fault positioning method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring transient voltage data after a power transmission line is directly struck by lightning; defining a set of possible fault locations based on the historical fault data; converting the transient voltage into a transient current; reversely injecting the transient current into a simulation model of the power transmission system from the same observation point, and simulating a transverse branch current at each possible fault position; and calculating the time domain similarity between the transient current and the transverse branch current at each possible fault position, and determining the fault position with the highest similarity as a lightning stroke fault position. According to the invention, high-precision positioning of the lightning stroke fault can be realized only by installing one measurement point in the main substation, and the reliability is high. The method is not only suitable for a lossless system, but also suitable for a lossy transmission line.

The invention comprises a method for controlling a mobile service robot for monitoring the movements of a person, comprising identifying the person, associating the identified person with a stored monitoring profile, capturing the person's movements by means of a motion detection sensor, generating observation points for the captured person, evaluating the captured movements of the person, retrieving position data as coordinates of a map, and automatically outputting information to the captured and identified person via an output unit of the mobile service robot.

The invention discloses a new energy power system transient instability tracing method, device and equipment and a storage medium, and is used for solving the technical problem that a traditional simulation method is difficult to accurately judge transient stability of a power system, especially local transient stability. The method comprises the following steps: determining a traditional observation point of a target power system and a traditional observed quantity corresponding to the traditional observation point; performing fault-free simulation on a target power system by adopting the traditional observed quantity to obtain a simulation model; performing fault simulation on the target power system according to the simulation model to obtain a plurality of fault observation quantities corresponding to the traditional observation points; performing transient stability judgment according to the fault observed quantity; when the transient stability judgment result is unstable, obtaining new energy station observation quantity in the target power system; and determining a transient instability disturbance source according to the fault observation quantity and the new energy station observation quantity.

The embodiment of the invention provides a laser radar wind field inversion method based on a filtering speed volume processing algorithm, and is applied to the technical field of laser radars. The method comprises the following steps: obtaining observation data base data of each voxel of laser radar wind field inversion, the observation data base data comprising signal-to-noise ratios at observation points in the voxels for calculating an average signal-to-noise ratio in the voxels; when the average signal-to-noise ratio is greater than or equal to a preset signal-to-noise ratio switching threshold value, inverting a three-dimensional wind vector in the voxel based on a velocity volume processing algorithm; and otherwise, inverting the three-dimensional wind vector in the voxel based on a preset filtering speed volume processing algorithm. In this way, the speed volume processing algorithm can be adopted to invert the three-dimensional wind vector for the inversion of the near-field wind field data with the high signal-to-noise ratio so as to improve the calculation efficiency, and after the signal-to-noise ratio in the far field is reduced to the preset signal-to-noise ratio switching threshold value, the three-dimensional wind vector is inversed based on the preset filtering speed volume processing algorithm, so that the calculation efficiency is improved. Therefore, the laser radar wind field inversion precision is improved.

A method for estimating fault location in an electrical power line system (PLS) is provided. The method includes receiving an observed signal caused by a real fault in the PLS. The observed signal is measured at a real observation point in the PLS. The real fault has occurred at one of two or more real locations in the PLS; accessing a library representing model signals between model guessed fault locations and a model observation point in a network model of the PLS; selecting a model GFL by: (i) calculating metrics for the model signals by processing the model signals with the observed signal, and / or (ii) selecting the model GFL corresponding to a highest calculated metric; estimating a fault location of real locations in the PLS based on a corresponding location of the selected model GFL; and sending the estimated fault location to an external management system.

The invention provides a camera calibration error analysis method and system based on Kinect V2. The method comprises the following steps: calculating internal parameters and external parameters of a camera; applying a calibration result to a new image, calculating a distance between a re-projection point and an actual observation point, evaluating the calibration result, carrying out statistical analysis on re-projection errors of all images, and calculating statistical indexes such as an average error and a maximum error; the method comprises the following steps: adjusting input parameters such as a calibration plate position and a camera attitude, observing the change condition of a calibration result, determining the influence degree of each input parameter on the calibration result, carrying out eigenvalue decomposition on a covariance matrix of a calibration error, and analyzing an error source and the influence degree of the error source on the calibration result; if some error sources are found, calibration is carried out again by adding calibration points or changing calibration conditions. The system comprises a parameter calculation module, an error analysis module and a calibration optimization module. The accuracy and reliability of the calibration result are improved.