185 results about "Space transformation" patented technology

The invention discloses a power transmission line inspection unmanned aerial vehicle obstacle intelligent detection and obstacle avoidance method. The method comprises the steps that multi-source sensing data is acquired, and alignment is completed through calibration and timestamp matching; heterogeneous data preprocessing and feature enhancement; constructing a high-precision environment fusing a geometric structure and a semantic tag, mapping a two-dimensional target detection result output by the recognition network to a three-dimensional coordinate system through spatial transformation, and fusing the two-dimensional target detection result with a point cloud structure to construct a semantic occupation grid map; performing preliminary route planning according to a preset power grid topological structure and task coverage requirements, and generating a barrier-free flight path covering the whole inspection area; reinforcing learning of a dynamic obstacle avoidance strategy; track dynamic reconstruction and energy consumption optimization scheduling are carried out; the technical problems that an existing technical system has defects in the aspects of obstacle recognition accuracy, complex environment adaptability, data fusion capacity and obstacle avoidance strategy intelligence, and the requirements for high-reliability, low-energy-consumption and high-efficiency unmanned aerial vehicle power transmission line inspection are difficult to meet are solved.

The invention provides a building equipment operation data intelligent analysis method and system, and relates to the technical field of data processing, and the method comprises the steps: extracting historical positioning data in a space calibration interval, and calculating a position offset vector set between a predicted trajectory point and an actual trajectory point according to the trajectory point on a predicted motion trajectory; taking the weighted sum of squares of minimizing the position offset vector as an optimization target to obtain a three-dimensional space transformation parameter optimization model; according to the optimization model, a quasi-Newton optimization algorithm is adopted to solve the optimization model, and a final calibration parameter set is generated; and based on the final calibration parameter set, correcting the predicted motion trajectory, performing spatial relationship analysis on the corrected trajectory and a spatial risk field, calculating a collision risk probability and an accident severity level, generating a comprehensive risk score, and triggering a response action according to a preset threshold value. The construction safety level and the management efficiency are improved.

The invention relates to the technical field of laser engraving, and discloses a laser engraving method and system capable of automatically correcting coordinates of a galvanometer and a camera, and the method comprises the following steps: calculating a target conversion coefficient based on a calibration size and a pixel size of an image collected by the camera, and controlling the galvanometer to perform laser etching on a cross mark on the surface of a PCB (Printed Circuit Board), recording origin data of a galvanometer coordinate system; adjusting the position of the camera to enable the cross center of the view of the camera to coincide with the cross mark, and calculating the coordinate offset; coordinate space transformation is carried out on all the points to be machined, and galvanometer marking coordinate data are obtained; after laser engraving is carried out on the galvanometer marking coordinate data, an engraving area image is collected, the position residual error and the size proportion deviation are calculated, laser engraving is carried out again, and a laser engraving result is obtained. The technical problem that the visual positioning coordinate and the galvanometer marking coordinate in the laser engraving system are not consistent is effectively solved.

The invention provides a method and a device for predicting influence of sea wave fluctuation on signal intensity based on ship data. The method provided by the invention comprises the following steps: acquiring multi-attitude angle data of a ship based on a nine-axis inertial measurement unit; the multi-attitude angle data comprises a rolling angle, a pitch angle and a yawing angle; establishing a Cartesian coordinate system taking the gravity center of the ship as an original point; based on the multi-attitude angle data, calculating spatial transformation of the antenna position in the Cartesian coordinate system through an automatic spatial transformation algorithm to obtain the transformed antenna position; determining the direction of the transformed antenna through vector operation by combining the initial orientation of the antenna and the position of the transformed antenna; and determining a corresponding angle through an angle resolving algorithm based on the initial antenna direction and the transformed antenna direction, matching a corresponding antenna gain in an antenna gain database based on the angle, and determining a signal strength change prediction value based on the antenna gain.

The present invention relates to the field of robotic arm teleoperation technology, and specifically to a construction method and system for real-time teleoperation of a dual arm and hand robot based on vision guidance, which includes setting up a first experimental platform, acquiring pose information of the dual arm and hand robot and a homogeneous transformation matrix of an end joint and transforming a first coordinate system; setting up a second experimental platform; performing calibration by a plurality of cameras and transforming a second coordinate system; obtaining spatial transformation pose information of the end joint of the robotic arm under a tracking state, reading finger pose data, and performing real-time following. The real-time teleoperation system of the present disclosure includes a control system host, an operation glove, an optical locator, a positioning coordinate plate, a marker ball tool, and a dual arm and hand robot. The present disclosure introduces a method of identifying the marker ball tool by the optical locator into the teleoperation control of the dual arm and hand robot, which is more accurate and faster. Meanwhile, the method of remotely controlling the robotic arm by an operator wearing the operation gloves can provide better human-machine interaction function.

The invention provides a video coding and compression transmission method for intelligent equipment, which belongs to the technical field of video coding and compression transmission, realizes advanced channel quality estimation by establishing a channel prediction model enhanced by a spatial transformation network, configures layered coding parameters according to a prediction result and optimizes motion search in combination with inertial measurement unit data. An optimal coding mode is selected by an application rate distortion optimization algorithm, enhancement layer sending is adjusted according to real-time feedback by adopting a dynamic transmission scheduling strategy, and differential forward error correction protection and a time-space domain error concealment mechanism are matched; the technical problem that video transmission is unstable due to violent fluctuation of channel quality when intelligent equipment moves and works in complex electromagnetic environments such as a transformer substation is solved.

The invention relates to the technical field of artificial intelligence, and provides a network intrusion detection method based on multidimensional feature collaborative analysis, and the method comprises the steps: calculating the correlation degree eta ij of any two feature columns in an original traffic feature matrix, and when eta ij is greater than eta thr, generating a new feature through Qij = Xi * Xj + (1-eta ij) * (Xi + Xj), outputting a dimension reduction feature matrix to perform nonlinear spatial transformation on the dimension reduction feature matrix X ', dynamically retrieving associated knowledge through a learnable memory library, fusing current input features and memory enhancement features, and outputting refined features; decomposing the refined features to a biological neural oscillation frequency band, applying carrier modulation, and performing feature reconstruction to generate a space-time correlation tensor; the refined features and the space-time correlation tensor are fused, and the intrusion behavior classification probability is output through multi-stage abstract compression and regularization processing; screening difficult samples based on classification confidence to construct a training library, and obtaining a conventional detection model and a special and precise detection model; and preferentially calling the special and precise model during real-time detection, and switching to the conventional model when the confidence coefficient is smaller than a confidence coefficient threshold value.

There are provided methods, systems, and non-transitory storage mediums for performing a meta-prediction of time series by using a set of forecasting models each associated with a forecasting theme. Time series data is received, and a set of forecast signals is generated. At least one signal and feature processing model generates a set of features. A meta-learner having been trained on historical time series data generates, based on the time series data and the set of features, a set of weights for the set of forecasting models. A meta-prediction is generated by using the set of features and forecast signals. Implementations may use combinations of endogenous and exogenous data, latent space transformations and generate interpretations and explanations for the meta-prediction.

The invention discloses a lithology analysis and identification method and system based on imaging logging, and the method comprises the steps: collecting imaging logging image data of different reservoir types, and constructing a lithology-imaging feature original data set; performing feature space transformation on the lithology-imaging feature original data set to generate enhanced feature representation in a manifold space, and taking the enhanced feature representation as a lithology-imaging feature enhanced data set; training an adaptive noise injection network by using the lithology-imaging feature enhanced data set to obtain a preliminary lithology classification model; judging a confidence index according to lithological characters output by the initial lithological character classification model to obtain a final lithological character classification model; and acquiring imaging logging image data of a to-be-identified well section, generating corresponding enhanced feature representation, inputting the enhanced feature representation into the final lithology classification model, and outputting a corresponding lithology identification result. The lithology identification accuracy and stability can be improved.

According to the method, a universe control equation set comprising a control equation, a free surface, upper and lower layer fluid interface continuity, structure-fluid interface continuity and fluid interface and seabed constraint conditions is constructed, and a vertical-horizontal decoupling modal analysis technology is combined, so that a multi-body radiation coupling model of the bottom-supported cylindrical array with relative motion between columns is provided; an intrinsic mode expansion technology is adopted to synchronously represent a joint radiation mechanism of a surface gravity wave and an internal wave, potential function space transformation and mode matching under a multi-column coordinate system are realized through a Graf addition theorem, and a radiation matrix coupling model considering a bottom-supported boundary constraint is constructed. According to the method, the wave-column coupling effect of the density layered interface can be accurately analyzed, a multi-column interference energy transfer path is quantified, and the modal truncation error is remarkably reduced.

The invention relates to the technical field of machine vision, and discloses an intraoperative hand-eye calibration method for a surgical robot, which comprises the following steps of: rigidly connecting a tracking camera with an endoscope, acquiring a fixed pose relationship of the tracking camera and the endoscope through spatial calibration, converting a pose of the tracking camera into a pose of the endoscope, and recording a paired sample of an image and the pose of the endoscope; based on the image and endoscope pose pairing sample, training an image pose regression model, and outputting the rotation amount and the translation amount of the endoscope at the image acquisition moment; inputting the trained regression model, estimating the posture of the endoscope, and recording the posture information of an end effector of the robot; image relative movement and mechanical arm relative movement are constructed, and the spatial transformation relation between the endoscope and the tail end of the surgical robot is calculated. According to the method, preoperative calibration is adopted, the space fixed pose relation between the tracking camera and the endoscope is combined, the absolute pose estimation model of the endoscope is established through the accurate calibration process, and it is ensured that the pose of the endoscope can be inferred only through images in the operation.

The invention provides a dental implant robot path generation method. The method specifically comprises the following steps: constructing a tooth space pose vector; constructing a regression model for predicting spatial features of target missing teeth by combining spatial pose features of opposite-side homonymous teeth and upper and lower occlusal teeth, and predicting spatial positions and attitude angles of the target missing teeth; tCP calibration is carried out on the dental implant robot; carrying out TCF calibration on the dental implant robot; constructing a spatial transformation relation between an end effector of a mechanical arm of the robot and an external visual positioning system; constructing a spatial transformation matrix between the digital model and the entity printing model by adopting a point cloud registration technology; an initial obstacle avoidance path of the mechanical arm is constructed based on a fast expansion random tree sampling algorithm, and meanwhile, smoothing and speed regulation are performed on a joint track through polynomial interpolation and B spline curve interpolation in combination with an improved algorithm RRT *. According to the technical scheme, the problems that in the prior art, planting errors are large, and the fitting degree is not high are solved.

The invention discloses a gait recognition method based on contour and skeleton mixed attention feature fusion. The gait recognition method comprises the following steps: constructing a double-branch gait recognition framework GitFusion; in the skeleton branch, using a graph convolution network GitGCN with a channel attention mechanism to extract skeleton features; in a contour branch, a convolutional neural network GaitContour of an integrated space converter is adopted to extract contour features, and the integrated space converter captures a long-distance dependency relationship; and designing an adaptive feature fusion module to realize intelligent fusion of the two features. The method can effectively cope with gait recognition challenges in complex scenes such as article carrying and wearing change, has the characteristics of high recognition accuracy and strong robustness, gives consideration to model lightweight and calculation efficiency, is suitable for being deployed on resource-constrained equipment, and has wide application prospects in the fields of intelligent security and protection, identity authentication and the like.

The invention discloses a reduced-order modeling and integrated rapid forecasting method for dynamic motion and structural response of a floating fan. The method comprises the following steps: performing finite element modal analysis on a floating fan structure, extracting a rigid body modal and a main elastic modal, constructing a low-dimensional modal space, orthogonalizing mass and stiffness matrixes, and reducing the degree of freedom of a system; hydrostatic force recovery, mooring, gravity rigidity and external exciting force are calculated according to the initial position of the structure, a hydrostatic balance control equation is established through modal space transformation, and generalized displacement is solved through iteration; recalculating the water pressure at the Gaussian point of the structural grid based on the radiation diffraction theory, calculating the pneumatic load in combination with the blade element momentum theory, and obtaining a generalized external load through modal transformation after superposition; a motion equation is established in a modal space, generalized displacement is solved through numerical integration, a global displacement field is reconstructed, a stress time history is directly calculated, and integrated rapid forecasting is achieved. According to the method, the calculation efficiency is remarkably improved while the key dynamic characteristics and the response precision of the structure are kept, and reliable support is provided for near-real-time evaluation of operation and maintenance of the floating type draught fan.

The invention discloses a simple method for robot hand-eye calibration and a structured calibration device, and aims to solve the problems of complex operation, large calculation amount, low efficiency and poor repeated precision of a calibration method in the prior art. The structured calibration device comprises a calibration plate, a connecting bracket, a disc base and a positioning device for accurate installation, the core of the calibration device is that the spatial transformation relation between the calibration plate and the disc base is a predetermined fixed constant. The method comprises the steps that the device is installed at the tail end of the robot, an image of the calibration plate is collected through the camera, the pose of the camera and the calibration plate is calculated through a pose estimation algorithm, and finally the final hand-eye transformation relation is obtained through calculation in combination with the fixed transformation relation predetermined by the device. Through structure solidification and algorithm simplification, complex motion of the robot is not needed, and the method has the advantages of simple operation, light calculation, high repetition precision, high calibration efficiency and the like.

The invention relates to a privacy protection technology in a large language model, and provides a method for realizing privacy protection through embedded space conversion in retrieval enhancement, which comprises the following steps of: generating a target training sample by utilizing a pre-training language model based on near-end optimization training; and the potential privacy leakage query statement is mapped to the security target in the embedding space through the conversion of the embedding space to realize the protection of privacy. According to the scheme, on numerous representative large language models and data sets, it is proved that the normal function of the retrieval enhancement generation model is guaranteed, and meanwhile the defense efficiency is excellent.

This application discloses a method, apparatus, device, and storage medium for determining the pose of a photovoltaic panel, relating to the field of photovoltaic technology. The method includes: performing coordinate transformation and spatial filtering based on the original point cloud and corner pixel coordinates of the target photovoltaic panel to obtain a region of interest (ROI) point cloud of the target photovoltaic panel; performing filtering and matching processing on the ROI point cloud to obtain a photovoltaic target point cloud of the target photovoltaic panel; constructing a photovoltaic panel coordinate system of the target photovoltaic panel based on the spatial transformation relationship between the photovoltaic target point cloud and the point cloud template; and obtaining the target spatial pose of the target photovoltaic panel in the camera coordinate system based on the axial correspondence between the photovoltaic panel coordinate system and the camera coordinate system. By fusing the point cloud information and corner pixel coordinates of the photovoltaic panel, and further performing filtering and transformation processing to construct the photovoltaic panel coordinate system, the accuracy of photovoltaic panel pose recognition is improved.

The invention provides a drilling and blasting method tunnel construction quality evaluation method and system, and relates to the technical field of tunnel construction quality evaluation. According to the method, drilling, charging, blasting vibration and tunnel contour data are collected in real time and transmitted to a server. The server maintains a dynamically updated tunnel contour reference, calculates a contour quality vector through spatial transformation, and integrates construction parameters and geological data to construct a construction state vector. Based on a construction response field constructed by historical data, the system deduces an expected vibration speed and contour quality as a prediction reference. And through difference analysis of actual data and a predicted value, the system generates a current state conflict vector, and inquires a decision mapping table to output a construction parameter adjustment instruction. And the equipment control system executes parameter cooperative adjustment and feeds back new data to the server to form closed-loop control of evaluation and optimization, so that real-time, accurate and adaptive control of the construction quality is realized.

This invention relates to the field of robot intelligent control and precision operation technology, and discloses a charging gun insertion positioning and error correction method and device based on a robotic arm. The method guides the charging gun into the target charging port based on constant force control. When edge contact jamming occurs, the constant force is maintained, and a six-dimensional force sensor is used to collect force and torque information in real time. By establishing three spatial coordinate systems at the end of the robotic arm, spatial transformation and decoupling analysis of force and torque are performed. Using the constraint that the z-direction of the charging gun end plane is zero, the actual contact position of the charging port relative to the charging gun end plane is calculated, obtaining the jamming correction vector. The jamming correction vector is transformed into a coordinate system based on the end of the robotic arm to obtain the target movement vector. The robotic arm is then controlled to move along this direction, achieving precise error correction and smooth insertion. This invention can accurately identify the jamming point location, achieve directional correction, and improve the charging gun insertion success rate.

The application belongs to the technical field of underwater acoustic, and discloses a line spectrum detection front tracking method and a multi-target distinguishing method based on signal space transformation. The track energy accumulation value on the slice obtained after signal space transformation is constructed as a cost function in a particle swarm parameter optimization algorithm, so that the complexity of slice search in the transformation space is reduced, and the calculation amount is greatly reduced. Meanwhile, a hidden Markov model is established on the slice, and a Viterbi algorithm is used to track the track, compared with the method of using a Radon algorithm to integrate on the slice, the selection of the integration path is more accurate, and the processing gain is improved. The method improves the detection probability, tracking accuracy and parameter optimization speed of the uniform motion target under low signal-to-noise ratio. The searched parameters can be used as the characteristics of the target to distinguish the target, and multi-target distinguishing is realized.

The application discloses a mesh generation method and device, computer equipment, medium and program product. For a first appearance mesh that has been generated, a mesh generation request for generating a second appearance mesh is obtained. Feature point data respectively identifying feature points in the first object mesh and the first appearance mesh, and first space transformation data are obtained based on the request. The first appearance mesh can be converted into a second appearance mesh for wrapping the surface of the second object mesh by combining the first object feature point data, the first appearance feature point data and the first space transformation data. The second appearance mesh can be directly controlled by the skeletal mesh bound to the first appearance mesh based on the reused binding relationship, so that the second appearance mesh generated therefrom can be directly applied in a game engine, greatly improving the generation efficiency of the appearance mesh and effectively reducing the technical threshold for generating the appearance mesh.

The invention discloses a positioning device for registration and fusion of a multi-modal medical image, and relates to the field of image auxiliary equipment, the positioning device comprises a transfer plate and a support, the transfer plate and the support are detachably connected, and the transfer plate is provided with a positioning assembly; according to the positioning device, by arranging the positioning assembly, the guide rail and the sliding block structure of the positioning assembly, a fixed physical track is provided for supporting tool adjustment, randomness of manual positioning is avoided, the position of the supporting tool can be rigidly fixed through a rack and an insertion block type locking component, no displacement risk exists after adjustment, an air bag on the inner side of the supporting tool forms flexible physical constraint, and body micro-movement of a patient in the examination process is limited; the whole set of design ensures that the body position of a patient has mechanical structure guarantee in the whole process from positioning, fixing to examination during each time of scanning, the body position difference of two times of scanning is extremely small, the body position repeatability is greatly improved, a software algorithm can give full play to the space transformation effect, perfect image registration is easily achieved, and a solid support is provided for the high-precision requirement of multi-modal image fusion.

The application provides a path planning method based on space transformation, and belongs to the technical field of path planning of unmanned vehicles; the method comprises the following steps: pre-processing a real map, converting the real map with obstacles into an obstacle-free space through space transformation; establishing and saving a dynamic mapping relationship between the obstacle-free space and the navigable area of the vehicle; obtaining a starting point and an ending point in the obstacle-free space, and obtaining path discrete points between the starting point and the ending point; and transforming the path discrete points into the real map to obtain path planning points in the coordinate system of the real map. The path planning method based on space transformation has the characteristics of less iteration and search process, less occupation of computing resources, and high computing efficiency.

This invention relates to the field of prefabricated building installation accuracy control technology, specifically disclosing an intelligent calibration system for prefabricated building installation accuracy that integrates point cloud data and BIM. The system collects on-site point clouds and acquires design geometric information; after distance attenuation compensation for the point cloud reflection intensity, it generates on-site and design projection intensity maps along the normal direction of the component installation plane, and obtains the in-plane pre-translation amount through phase correlation calculation; using this pre-translation amount as the prior center, it constructs a spatial transformation objective function containing an exponentially growing dynamic penalty coefficient, and solves the final spatial transformation parameters through weighted centroid closed-loop inversion iteration; it calculates the signed vertical distance along the normal of the aligned point cloud and removes outliers to form a deviation field, outputting translation or rotation fine-tuning amounts according to the median deviation of the joint sub-region; this invention solves the in-plane sliding problem in the registration of flat components, improving the accuracy of installation deviation calculation and calibration reliability.

The invention discloses a multi-mode fault diagnosis method and device based on automatic machine learning and a medium, and the method comprises the following steps: S1, collecting a signal sample of a rotating mechanical device, and carrying out the preprocessing; the signal sample comprises an acoustic signal and a vibration signal; s2, according to the processed signal samples, acoustic signal features and vibration signal features are extracted respectively, the features are fused and normalized, and multi-modal fusion features are obtained; s3, according to the multi-modal fusion features, feature space transformation and dimension reduction processing are carried out through an automatic machine learning process, and an optimized feature set is obtained; s4, performing model selection, hyper-parameter optimization and training according to the optimized feature set to obtain a plurality of base models; s5, based on the plurality of base models, performing model fusion by adopting a double-layer integrated learning strategy to obtain an integrated diagnosis model; and S6, inputting a to-be-diagnosed sample into the integrated diagnosis model, and outputting a fault type.

This invention discloses a multi-label classification method for medical images based on spatiotemporal integration and adaptive normalization, belonging to the field of medical image processing and computer-aided diagnosis technology. The invention proposes an improved scheme. Firstly, it constructs a dynamically balanced data input stream through frequency inverse sampling and cosine annealing strategies. Secondly, it introduces group normalization to replace batch normalization in the feature extraction network, solving the training convergence problem under limited GPU memory. During training, it employs a focal loss function to mine hard-to-classify samples. In the inference stage, the invention constructs a spatiotemporal integration mechanism based on multi-view space transformation and multi-stage model weight fusion, combined with an adaptive threshold decision algorithm based on maximizing F1 scores to output diagnostic results. This invention effectively improves the recognition accuracy of key pathological features such as cardiac hypertrophy and edema, while significantly improving the recall rate of small lesions, exhibiting high robustness and clinical auxiliary value.

The embodiment of the invention discloses a three-dimensional model cutting method and device, and the method comprises the steps: receiving at least one bottom surface vertex coordinate set and at least one box height value of at least one bounding box inputted by a user, and at least one spatial transformation matrix corresponding to the at least one bounding box; determining at least one initial bitmap based on the at least one vertex coordinate set and the at least one spatial transformation matrix; performing coding processing on the at least one initial bitmap to obtain a target bitmap; based on the target bitmap and the at least one box height value, determining whether at least one pixel point in a to-be-cut model is located in the at least one bounding box, and obtaining at least one judgment result; cutting the to-be-cut model according to the at least one judgment result; according to the embodiment of the invention, rapid cutting judgment is realized, and the model cutting efficiency is improved.

The invention relates to a semantic abstract generation and security verification method and system for multi-modal data, and belongs to the technical field of data security and information process.The method comprises the steps that feature extraction is carried out, specifically, a client processes a multi-modal plaintext data stream, and key features of the multi-modal plaintext data stream are extracted; vector mapping: the client performs vector space transformation on the extracted features to generate a unique corresponding data abstract; local persistence: the system stores the generated data abstract back to a user local database for subsequent use; abstract collection, wherein the detector obtains generated data abstract information from the data stream; and integrity verification: carrying out consistency comparison on the data stream with the data abstract by the detection and verification device, and judging whether the data stream is complete and reliable or not. The data abstract generation system comprises a client module, a server module and a middleware module. According to the method, efficient and reliable data stream abstract generation and credible management are realized on the premise of fully guaranteeing user data privacy.

An electronic device performs a method of decoding video data, including: receiving video data corresponding to a coding unit from a bitstream, where the coding unit is encoded in an inter prediction mode or an intra block copy mode; receiving a first syntax element from the video data, where the first syntax element indicates whether the coding unit has any non-zero residual; in accordance with a determination that the first syntax element has a non-zero value: receiving a second syntax element from the video data, where the second syntax element indicates whether the coding unit has been encoded using an adaptive color space transform (ACT); in accordance with a determination that the first syntax element has a zero value: assigning the zero value to the second syntax element; and determining whether to perform inverse ACT on the video data of the coding unit according to the value of the second syntax element.

The application relates to the technical field of precision microelectronic and semiconductor devices, and discloses a micro TEC cold and hot ceramic sheet stacking and mounting production line control method and system.The method comprises the following steps: collecting a surface image of a ceramic sheet to be mounted and extracting key points to generate a real-time deformation distribution benchmark; registering the benchmark with a previous layer benchmark and performing differential operation to construct a deformation difference field; solving a three-dimensional deviation when a displacement amplitude exceeds a limit, fusing historical interlayer cumulative deviation to determine a total cumulative offset vector and a total cumulative rotation angle; decomposing the total deviation into a rigid translation and a distortion deformation component, generating a space transformation compensation instruction based on a warping mode match, projecting and transforming a theoretical coordinate with the instruction and synthesizing a vector to generate a final adjustment mounting coordinate to drive a mechanical arm to move, and finally updating compensation parameters in a closed loop iteration according to actual interlayer deviation feedback. The method can solve the problem of low non-linear thermal deformation compensation precision in the multi-layer ceramic mounting process of the prior art.