140results about How to "Accurate mapping" patented technology

The invention belongs to the technical field of automatic industrial sorting, and discloses an automatic sorting digital twin system and a construction method. The construction method comprises the following steps: constructing physical entities for executing different operation functions in automatic sorting based on a physical entity layer, and sending the physical entities to a digital twin platform layer; the digital twin platform layer constructs a three-dimensional virtual model synchronous with different operation functions executed by the physical entity through three-dimensional design software; the three-dimensional virtual model is dynamically updated in real time; and loading the three-dimensional virtual model to a three-dimensional engine of a visual application layer through a communication protocol or a transmission network, monitoring the real-time states of different operation functions of the physical entity in an industrial automatic sorting simulation scene, and visually displaying the real-time states through a user interface. The digital twinning platform of the automatic sorting system is constructed, and visual interaction, real-time data monitoring and virtual and real synchronous operation of the automatic sorting digital twinning system are achieved.

The invention provides a comprehensive management and control method and system based on digital twin and multi-source heterogeneous data processing, and the method comprises the following steps: scanning a site, obtaining the point cloud data of a surrounding environment, reconstructing the reverse modeling of the geometric shape and structure of a building according to the point cloud data, and calibrating the model obtained through the reverse modeling with the site; carrying out optimization processing on the model; a multi-source heterogeneous data fusion technology is adopted to carry out process collection and classification on heterogeneous data of various specialties of rail transit, and standardized processing of the data is realized. According to the comprehensive management and control method and system based on digital twinborn and multi-source heterogeneous data processing, accurate mapping of a digital twinborn space to a real station environment is realized, a three-dimensional model can be associated with multi-dimensional data attributes, core functions such as virtual inspection, risk management and control and scheduling decision making are realized in an auxiliary manner, and the method and the system are suitable for popularization and application. And the intelligent operation level of the station is improved.

The invention relates to the technical field of slurry valve design, and discloses a large-diameter slurry valve sealing structure design method and device suitable for a high-wear working condition, and the method comprises the steps: firstly obtaining key geometric parameters of a sealing structure, constructing a three-dimensional topological basic model and a mechanical property simulation model, and then carrying out the fusion to form a digital twin model; then constructing a wear morphology time sequence data set; meanwhile, three-level early warning threshold values are set for the key working condition parameters, a working condition risk grade division rule is established, and a real-time working condition risk grade is obtained according to the working condition risk grade division rule; and finally, based on the wear morphology time sequence data set and the real-time working condition risk level, constructing a wear evolution prediction model, and optimizing key geometric parameters of the sealing structure in combination with a digital twin model to obtain an optimal geometric parameter combination. Accurate prediction and optimal design of the abrasion state of the sealing structure of the large-diameter slurry valve can be achieved, the service life of the sealing structure under the high-abrasion working condition is remarkably prolonged, and the reliability of the sealing structure under the high-abrasion working condition is remarkably improved.

The invention discloses a confocal microscope camera calibration method based on high-precision motion control. The confocal microscope camera calibration method mainly comprises the steps of establishing four coordinate systems, placing a checkerboard calibration plate on a high-precision platform and adjusting the checkerboard calibration plate to the center of the view of a camera, and shooting and recording image coordinates of a calibration point. And based on the imaging relationship between the optical center of the camera and the object point, determining the mapping relationship between the coordinate systems so as to establish a preliminary imaging model. Then, nonlinear correction is performed on the imaging model, lens distortion is eliminated, and corrected image coordinates are converted into pixel coordinates. The non-linear correction parameters are optimized through the multi-view data, the mapping relation between the image plane and the platform physical plane is further calculated, and the mapping relation is optimized through the least square method so as to improve the calibration precision. Finally, pixel coordinates in the image are converted into physical coordinates of a platform through the optimized matrix, and support is provided for the automatic focusing process of the confocal microscope.

The invention relates to the technical field of steel bridge deck system disease detection, in particular to a steel bridge deck system disease detection method and system and a construction method of the steel bridge deck system disease detection method and system. Attributes of a steel bridge deck system entity are mapped into a digital twinborn model of a virtual space by using a digital means, so that steel bridge deck system disease data are analyzed more comprehensively; the virtual service state analysis of the current steel bridge deck system entity and the prediction of the formation and development degree of the steel bridge deck system diseases are realized through the Internet of Things technology and big data processing. In the process of predicting the formation and development degrees of steel bridge deck system diseases, steel bridge deck system entity monitoring data are updated in a digital twinborn model and a steel bridge deck system twinborn database in real time by using the Internet of Things technology, so that accurate establishment of the digital twinborn model and accurate mapping of total data are realized; meanwhile, the virtual test model accurately simulates the service state of the steel bridge deck system, and it is ensured that the steel bridge deck system disease development model has credibility and reference in predicting the formation and development degree of the steel bridge deck system diseases.

The invention discloses a flash store digital site selection management system and method based on multi-channel site selection, relates to the field of flash store site selection management, and provides a mapping tool for subsequent mapping classification of site selection influence factor data of a plurality of to-be-selected points of a flash store by constructing a final category mapping equation; through mapping, flash store to-be-selected points with annual net profit data not meeting requirements are eliminated; a 0-1 integer programming model is constructed according to the construction cost data, the coverage data and the annual net profit data corresponding to each quick-flash store primary selection point, so as to solve the quick-flash store site selection points where quick-flash stores are constructed. The construction cost is smaller than the preset construction cost threshold value, and the corresponding total coverage range data is larger than or equal to the preset coverage range threshold value, so that the screened quick-flash store site selection point can meet various requirements at the same time, and the net profit maximization is achieved.

The invention provides a secondary network thermal load prediction method based on a CEEMDAN-KPCA-LSTM algorithm. The method comprises the following steps: dividing a complemented data set into a training set and a test set according to a proportion; key factors influencing the dynamic change of the thermal load of the secondary network in the training set data are used as input variables, and the thermal load data are used as output variables; performing local encryption and standardization processing on the thermal load data; building an improved neural network model for predicting the dynamic thermal load of the building; training the improved neural network model, and when the improved neural network model meets a convergence condition, obtaining a trained improved neural network model; performing standardization processing on the test set data, and setting test set input data according to an input variable selected from the test set data after standardization processing of the training set data; and inputting test set input data into the trained improved neural network model to realize prediction of the dynamic thermal load of a certain building in the future 24 hours.

The invention discloses a multi-target detection method based on a multi-source high-frequency track and a high-precision map, which realizes conversion of a video coordinate system, a millimeter wave radar coordinate system and a world coordinate system and fuses a radar target and a video target. The method comprises the following steps: automatically calibrating video and thunder vision; performing automatic deviation correction on a north corner and an equipment position based on multi-straight-line regression; transforming the video sensor into a world coordinate system; and carrying out decision association of the Leiyu tracking target. According to the method, the target trajectory and the high-precision map data are tracked by utilizing the thunder vision high frequency, the complexity of calibration between the sensors and between the sensors and a world coordinate system is reduced, meanwhile, the precision errors of coordinate transformation between the thunder vision sensors and thunder vision data world coordinate transformation are reduced, and compared with the prior art, the method has the advantages that in the application of complex traffic roadside vehicle detection scenes, the detection efficiency is improved. The precision is higher; and the data association has robustness.

The invention relates to the technical field of social media platform analysis, and discloses an abnormal psychology detection method based on multi-dimensional psychological feature modeling, which comprises the following steps: setting an emotion large category label and a behavior sub category label according to a contradictory dispute text on a social media; collecting a data set of contradictory dispute texts on the social media; cue words are designed, and an emotion classification task and a behavior recognition classification task of the contradictory dispute text are combined into one task; selecting a large language model and a parameter scale of the large language model, and performing training fine tuning on the large language model by using LLaMA-Factory based on cue words and training samples in a training set; and inputting the contradictory dispute text and the prompt word in the test set into the trained large language model to obtain an abnormal psychological detection result. According to the method, the emotion classification spanning single dimension can be realized, and the comprehensive assessment of the individual psychological state is realized.

The invention provides a method for realizing high-dimensional alignment and conversion of multi-modal features (vision and music), and aims to solve the problems of insufficient alignment of the multi-modal features, lack of consistency of styles and emotions and insufficient optimization of generated contents in the prior art. According to the method, through a multi-modal feature extraction module, a multi-modal feature alignment and mapping module, a dynamic generation and optimization module and a user interaction and feedback module, consistency of vision and music in style, emotion and dynamic characteristics is achieved, and accurate conversion from one mode to another mode is supported. Experimental results show that the method is remarkably superior to the prior art in feature alignment precision and generated content consistency, and has wide application prospects and technical innovation.

The invention relates to a zoom binocular system image ship target identification method based on homography matrix mapping, and belongs to the technical field of marine ship target image detection and identification. According to the method provided by the invention, ship targets identified through a deep learning algorithm are in two images of a binocular camera system, and four corner points and a central point of each target serve as corresponding points and are used for constructing a calculation basis of a homography matrix. Bidirectional accurate mapping between the visible light and the infrared image is realized through the constructed homography matrix, and target recognition of deep learning is supplemented. And a homography matrix group based on focal length change is constructed by adjusting the focal length of the binocular imaging system. When missing detection target identification of supplementary deep learning is carried out, the most suitable homography matrix is selected from the matrix library to be applied according to the current imaging condition and the focal length, and detection identification of missing detection or even zero detection ships obtained by a certain modal image only by using the deep learning method is realized.

According to the image recognition device and method, a current resistance relational expression is obtained according to the resistance values of a plurality of second memristors, the resistance value of a second column selection switch and a plurality of test currents, and the resistance value when the column selection switch is conducted is considered; after the weight voltage obtained according to the conductance value of the first memristor and the current resistance relational expression is input to the row signal end of the memristor sub-array, accurate mapping of the conductance value of the first memristor and the weight of the neural network can be realized. The plurality of column currents output from the plurality of column signal ends of the memristor sub-array are multiplication accumulation of the to-be-identified voltage and the conductance value of the memristor sub-array on the column, so that the accuracy of the image identification result determined according to the plurality of column currents is very high; switch control and data control are separated to different FPGAs, so that the reliability, flexibility and isolation of the device can be improved; and the serial-parallel conversion module is arranged, so that the IO interface pressure of the FPGA can be reduced, and the expandability is improved.

The invention discloses a traffic target monitoring and tracking system and method based on monocular vision daytime scene reconstruction. The system comprises a monocular camera, an inertial navigation module, a lightweight processor, a radio frequency communication module, a solar energy storage module and a Beidou positioning module. The monocular camera is used for continuously capturing multiple frames of images; the inertial navigation module utilizes a built-in high-precision gyroscope to measure the three-dimensional attitude of the monocular camera during photographing, and calculates an external parameter matrix of the camera; the lightweight processor is responsible for processing multiple frames of images acquired by the camera, performing image preprocessing, vehicle detection and trajectory calculation, and executing a core algorithm; the radio frequency communication module transmits the detected traffic flow information back to the traffic monitoring center; the Beidou positioning module provides geographical location information, so that traffic flow information can be synchronized with the geographical location. On the premise of not depending on high-power-consumption equipment, the vehicle information is transmitted back to the monitoring center through the radio frequency communication module, and the system is suitable for daily traffic monitoring and signal control optimization.

The invention relates to the technical field of medical health, in particular to a cardiac muscle tissue electrophysiology unmarked optical detection method based on deep learning. The method comprises the following steps: acquiring optical detection image data and electrophysiological signal data of myocardial tissue; the optical detection image data and the electrophysiological signal data are subjected to image preprocessing, so that optical-physiological signal mapping data are obtained, and image preprocessing comprises image registration, image cutting, periodic enhancement, time difference enhancement, spatial filtering, intensity normalization and data smoothing; and according to the optical-physiological signal mapping data, carrying out feature signal extraction based on a mechanical contraction curve and an electrophysiological curve so as to obtain mechanical contraction curve data and electrophysiological curve data. According to the method, unmarked optical detection is adopted, so that direct interference on myocardial tissues is avoided, and the physiological state of the tissues is better maintained.

The invention provides a method for predicting the influence of a noise environment on hearing, and relates to the field of machine learning. The invention provides a NoiseAudiito prediction model, which is applied to a background for predicting the influence of a noise environment on hearing, and comprises a self-adaptive variable attention module, a dynamic time attention module, an encoder and a decoder structure, the dynamic time attention module can capture the dependency relationship between the noise environment and hearing influence data time steps, and the encoder and the decoder can extract time and variable dependency features from the noise environment to hearing influence data and generate a final noise environment to hearing influence prediction result. Therefore, accurate prediction of the influence of the noise environment on hearing is completed.

The invention provides a budget data generation method and device for property transformation projects, equipment and a medium, and the method comprises the steps: associating a first correction coefficient in a historical data set of each transformation project, and representing a deviation ratio between prediction data and actual data through the correction coefficient, determining the first budget data by using the first correction coefficient and the prediction budget data obtained based on the historical data set, thereby realizing the correction of the prediction data; after the transformation plan is started, progress deviation data and a risk score are determined according to the real-time progress data of each transformation project, the progress deviation data are marked when the risk score is greater than a score threshold, and after the transformation plan is completed, each transformation project evaluates the accuracy of the first correction coefficient based on the progress deviation data and the risk score, and updating the first correction coefficient to the second correction coefficient based on the target step value, and associating the second correction coefficient to the historical data set to realize update iteration of the correction coefficient and improve the reliability of the budget data.

The invention belongs to the field of digital engraving, and particularly relates to a method for establishing a spatial relationship between an array clamping system and an engraving system, which comprises the following steps of: adjusting the geometric accuracy of each axis of the engraving system to be within a required range; adjusting the geometric accuracy of each shaft in the array clamping system; setting a zero point position of the array clamping system; fitting the X-axis direction and the Y-axis direction of the engraving system; preparing a measuring tool; constructing a coordinate system in the array clamping system; the initial position of each lifting column in the first row is controlled; the initial positions of the second row of lifting columns and other lifting columns are controlled; preparing a scribing tool and a scribing observation tool; determining X, Y and Z zero coordinates of a coordinate system of the engraving system; the spatial relationship between the array clamping system (2) and the engraving system (1) is established; according to the method, the spatial relationship between the array clamping system and the engraving system can be quickly established, the workload of technicians and operators is reduced, the precision of skin engraving machining is improved, and the machining cost is saved.

The invention relates to the technical field of virtual-real mapping positioning, in particular to a virtual-real space personnel mapping positioning system and method. The system comprises an image acquisition unit, a target detection unit, a camera parameter processing unit, a coordinate conversion unit, a real space model construction unit, a virtual space model construction unit, a coordinate extraction unit, a virtual-real registration unit and a personnel mapping unit. The spatial position of the target person in the real spatial model corresponds to the spatial position of the target person in the virtual spatial model through units in the system. According to the method, accurate positioning and mapping of the target entity personnel in the real space and the virtual space can be realized, so that convenience is provided for various application scenes, and more intelligent and accurate man-machine interaction and service can be realized in the fields of smart home, smart office, virtual reality and the like.

The invention relates to a three-dimensional curved surface capacitive sensor and a weaving method thereof. The weaving method comprises the following steps: modeling the shape of the three-dimensional curved surface capacitive sensor into a three-dimensional curved surface grid; converting the three-dimensional curved surface grid into weaving information readable by a weaving device; generating a control command according to the weaving information, and weaving the three-dimensional curved surface capacitive sensor by taking the conductive warps and the conductive wefts as fabrics; each of the conductive warps and the conductive wefts comprises a bendable wire core and an insulating layer wrapping the wire core; and one or more conductive warps are connected in parallel to form a driving channel, and one or more conductive wefts are connected in parallel to form an induction channel. Capacitance nodes are formed at the crossed and overlapped positions of the driving channels and the sensing channels and used for forming stray capacitance with the living body to detect approaching of the living body. And the capacitor node is used for detecting a pressure value when the insulating layer is deformed due to pressure. By means of the weaving method, the capacitive sensor can be accurately attached to the curved surface of the target, and accurate mapping of sensing signals in the three-dimensional space is achieved.

The utility model relates to bone hook coordinate mapping positioning equipment suitable for spinal surgery, which comprises a bearing rod, the bearing rod is connected with an adjusting rod through an adjusting shaft, a plurality of guide devices are arranged on the outer side of the bearing rod and the outer side of the adjusting rod, each guide device comprises a guide seat, and a bone power cutting groove is formed in the outer side of each guide seat. A bone hook groove is formed in the guide seat, and a plurality of bone hook assemblies are arranged in the bone hook groove through mapping assemblies. Therefore, the angles of the bearing rod and the adjusting rod can be properly adjusted, the physiological curve of the back of the human body can be fitted, and subsequent positioning errors are avoided. The angle of the guiding device can be adjusted, and a proper angle can be provided according to the mapping requirement. The guiding device can achieve stable positioning of the orthopedic power depth limiter installed subsequently, and sliding is avoided. The bone hook assembly can achieve accurate mapping of bone surface contact point coordinates, and the operation precision is improved.

The invention relates to the technical field of battery management, and discloses a battery health state evaluation method and system for an electric tool energy supply device, and the method comprises the steps: obtaining multi-source sensor data in the operation process of an electric tool, and carrying out the preprocessing of the data; identifying and classifying multi-stage pulse discharge events, extracting multi-scale voltage response features and performing temperature compensation; equivalent circuit model parameter identification is carried out, abnormal identification results are checked and removed, and parameter aging characteristics are extracted; constructing a time sequence prediction model for prediction; evaluating the overall health state and the monomer consistency of the battery pack; defining a judgment standard of effective cycles, predicting the number of remaining effective cycles, calculating a confidence interval of a prediction result, and generating a battery management suggestion; formatting into a standardized evaluation report, carrying out data synchronization and model optimization through edge cloud collaboration, and recording a system operation log; according to the invention, accurate health state evaluation and residual life prediction are realized.

The present invention provides a comprehensive management and control method and system based on digital twins and multi-source heterogeneous data processing, the following steps: scan the site, obtain point cloud data of the surrounding environment, reconstruct the reverse modeling of the geometric shape and structure of the building based on the point cloud data, and calibrate the model obtained by reverse modeling with the site; optimize the model; use multi-source heterogeneous data fusion technology to process and classify the heterogeneous data of various professional rail transit, and realize standardized data processing. The comprehensive management and control method and system based on digital twins and multi-source heterogeneous data processing provided by the present invention realizes the accurate mapping of the digital twin space to the real station environment, can associate the three-dimensional model with the multi-dimensional data attributes, assist in realizing the core functions such as virtual inspection, risk control and scheduling decision-making, and improve the intelligent operation level of the station.

The invention discloses a variable component sub-line, a quantum state amplitude coding method, a quantum state amplitude coding device, quantum state amplitude coding equipment and a medium. The first operation column comprises n-1 first uncontrolled RY gates; each first uncontrolled RY gate is respectively arranged on the second quantum bit to the nth quantum bit; the line module comprises a plurality of second operation columns, and each second operation column comprises one second uncontrolled RY gate and (n-1) controlled RY gates; the second uncontrolled RY gate is arranged on the first quantum bit; each controlled RY gate is respectively arranged on the second quantum bit to the nth quantum bit; the third operation column comprises n third uncontrolled RY gates which are respectively arranged on n quantum bits; the line module is located between the first operation column and the third operation column, and each uncontrolled RY gate and each controlled RY gate carry training parameters. According to the invention, the amplitude coding efficiency can be effectively improved under the condition that the number of quantum gates using quantum circuits is reduced.

The invention provides a brake clearance prediction method and device, electronic equipment and a readable storage medium, and belongs to the technical field of data prediction.The method comprises the steps that a fatigue backstepping model is determined based on simulation fatigue parameter data and historical fatigue parameter data, the fatigue back-stepping model is used for constructing a mapping relation between running state data and fatigue state data of the brake; determining a brake clearance-fatigue relation model based on the fatigue state data and the first brake clearance data; the brake clearance-fatigue relation model is used for constructing a mapping relation between brake clearance and fatigue state data of the brake; and the brake clearance of the target brake is predicted based on the fatigue backstepping model, the brake clearance-fatigue relation model and the target operation state data, and second brake clearance data are obtained. According to the brake clearance prediction method and device, the electronic equipment and the readable storage medium, the accuracy of brake clearance data prediction of the brake can be improved.

This invention discloses an online search method for particle spelling variants and properties usable by intelligent agents. The steps are as follows: inputting the baseline spelling of a particle and the constructed particle-specific prompt words into a large language model to generate a core variant corresponding to the particle; integrating the core variant of each particle with the authoritative benchmark information corresponding to the particle to form a full variant set for each particle; each record in the full variant set contains a unique identifier for a particle, a multi-scene benchmark name, a core variant, and extended attributes; dynamically mapping a remotely callable interface set on the server to a local proxy object on the client; after receiving a query request, the local proxy object parses the particle spelling parameters in the query request and performs multi-dimensional spelling matching in the full variant set to realize online search for particle spelling variants and properties. This invention effectively improves the ability of AI intelligent agents to handle domain-specific tasks.

The invention discloses a rapid magnetic resonance imaging reconstruction and segmentation method and system, a medium and a product, and relates to the technical field of image processing. The method comprises the following steps: decomposing original three-dimensional magnetic resonance data into a plurality of independent two-dimensional magnetic resonance data slices along a slice sequence; image reconstruction is carried out on the two-dimensional magnetic resonance data slices through a pre-trained forward generator in the frequency domain Schrodinger bridge diffusion model so as to generate a two-dimensional magnetic resonance image, and the forward generator integrates a Fourier convolution module and is used for carrying out frequency domain transformation and feature enhancement processing on feature mapping in the image reconstruction process; inputting each two-dimensional magnetic resonance image into a pre-trained segmentation model in sequence, performing segmentation of a target region and a preset dangerous organ, and generating a corresponding two-dimensional segmentation mask; all the two-dimensional segmentation masks are rearranged and stacked according to the slicing sequence, and a three-dimensional segmentation result is generated through three-dimensional fusion operation. By implementing the technical scheme, magnetic resonance imaging reconstruction and segmentation can be quickly and accurately carried out.

The invention relates to a video and map data mapping method based on three-dimensional geographic information, and the method comprises the steps: (1) obtaining the three-dimensional geographic coordinates of a starting point and a target point, respectively including the longitude, latitude and elevation data of each point, picking up the video pixel coordinates and the three-dimensional geographic coordinates of the target point, and constructing a serialized feature point pair; (2) according to the serialized feature point pairs, camera geographic calibration based on the feature point pairs is carried out; and step (3), mapping the three-dimensional geographic coordinates of all points in the geographic space in the video coverage area into video pixel coordinates based on a rotation matrix constructed after camera geographic calibration, or mapping the video pixel coordinates of all points in a camera picture into three-dimensional geographic coordinates.

This invention relates to the fields of laser additive manufacturing and digital twin technology, and discloses a multi-axis laser cladding topography digital twin system. The system includes a process parameter acquisition and equipment status mapping module, a two-dimensional topography prediction module, a real cladding process video module, and a virtual three-dimensional topography real-time update module. The process parameter acquisition and equipment status mapping module is used to acquire and synchronize process parameters, multi-axis motion status, TCP position, TCP feed direction, and laser switch status. The two-dimensional topography prediction module is used to call the laser cladding topography prediction model and output a two-dimensional cladding cross-sectional contour line. The real cladding process video module is used to acquire on-site images or video video information. The virtual three-dimensional topography real-time update module is used to map the two-dimensional cladding cross-sectional contour line to three-dimensional space and incrementally construct a triangular mesh model of the cladding layer. This invention can achieve real-time linkage updates and virtual-real synchronous display of equipment status, cross-sectional contour, and three-dimensional cladding topography without relying on online point cloud measurement of the cladding weld bead.

The invention discloses a method for simulating phosphorus and chromium migration during farmland irrigation with acid mine wastewater, which comprises the following steps: mixing a plant-derived organic material with deionized water to obtain a soluble organic matter; h2O2 oxidizes Fe < 2 + > to prepare pure Schwertmannite, and the pure Schwertmannite is placed in a phosphate solution to obtain phosphorus-loaded Schwertmannite; mixing the phosphorus-loaded Schwertmannite and the soluble organic matter with a chromate solution, carrying out oscillation adsorption, carrying out solid-liquid separation after adsorption, carrying out CrO and POconcentration change test on filtrate, and carrying out mineral characterization on separated solids; a three-dimensional fluorescence spectrum is adopted to track composition conversion of the soluble organic matter in the reaction process; and analyzing the component change of the supernate before and after the reaction by adopting Fourier transform ion cyclotron resonance mass spectrometry. The influence mechanism of DOM on phosphorus and chromium fate in mineral / water interface molecular fractionation is disclosed from the molecular level, and a scientific basis is provided for collaborative migration risk assessment of phosphorus and heavy metal in acid mine wastewater irrigation area farmland.

This application relates to the field of gas sensor packaging technology, specifically to an automated packaging method, system, and packaging device for gas sensors. The method includes: pre-establishing a packaging process parameter-gas-sensitive channel adaptation model; calculating the actual coaxiality deviation and correcting the sealing pressure reference value based on the gas-sensitive channel aperture; starting the integrated packaging unit, applying pre-pressure according to the corrected sealing pressure, and simultaneously collecting the temperature of the sealing area through an infrared temperature measurement module to determine whether dynamic adjustment of the welding temperature is needed; after welding, maintaining the corrected sealing pressure, and dynamically adjusting the pressure holding time based on the gas-sensitive channel length and the creep coefficient of the sealing material to complete the sealing process. This application achieves a precise balance between sealing performance and conduction efficiency by establishing a dynamic adaptation model of process parameters and gas-sensitive channel structure, overcoming the coupling imbalance bottleneck of existing technologies.