3665 results about "Three dimensional data" patented technology

The present invention relates to the technical field of data transmission. Disclosed is an application-driven three-dimensional spatial data transmission method. The method comprises: determining system key performance indicators (KPIs) by means of qualitative and quantitative analysis; constructing an AI-driven adaptive three-dimensional data transmission mechanism, and dynamically adjusting a transmission strategy on the basis of a real-time network state, a device capability, an application scenario and the KPIs; developing an adaptive compression algorithm set oriented to three-dimensional data, so as to meet differentiated compression requirements of different application scenarios; performing loop execution of a test, and adjusting and optimizing the data transmission mechanism and the compression algorithm set on the basis of a test feedback result and the real-time network state; and deploying an optimized transmission method to a production environment, and collecting field data to optimize the system performance and verify the achievement of the KPIs. By constructing a qualitative and quantitative analysis framework based on machine learning, the present invention quantifies differentiated transmission requirements of different application scenarios and formulates transmission strategies meeting the scenario requirements.

The invention relates to the field of semiconductor packaging material defect detection, in particular to a semiconductor packaging material defect detection method based on deep learning, which comprises the following steps: acquiring a surface image, and extracting a two-dimensional contour and a feature point set; preprocessing the image, and separating a packaging material main body area; constructing a two-dimensional defect identification model based on Transform, and outputting a two-dimensional detection result; scanning suspected and unknown defect areas to obtain three-dimensional point cloud data, and extracting geometric and texture features; fusing two-dimensional and three-dimensional data through a space-time alignment model; utilizing the multi-modal fusion model to output defect positions and types; and evaluating the defect importance based on the material node connectivity and the stress distribution, and generating a visual detection report. According to the invention, high-precision detection of semiconductor packaging material defects is realized, the defect identification rate, the positioning precision and the detection efficiency are improved through multi-modal data fusion and a deep learning model, and a visual report can be generated based on material structure quantification defect importance.

The invention relates to the technical field of river pollution identification, in particular to a pollutant identification and early warning method and system for a river patrol pollution source, and the method comprises the steps: constructing a three-dimensional monitoring network system, so as to build a three-dimensional data collection architecture; establishing a space-time reference unified framework to realize synchronous time service of different monitoring nodes; deploying an edge computing node, and implementing data preprocessing at an equipment end of the monitoring node; constructing a pollutant feature library which comprises spectral features, water quality parameter correlation features and visual morphological features of river pollutants, and establishing a water quality parameter correlation model of organic pollutants and inorganic pollutants, which comprises a plurality of feature dimensions; and a self-adaptive threshold early warning mechanism is established, a space-time composite early warning model is constructed, and accurate positioning and hazard degree grading early warning of pollution events are realized. According to the invention, through the hierarchical fusion model of technology fusion, the precision and speed of identifying the river pollutants are improved.

The invention discloses a live-action three-dimensional model construction method, system and device based on a digital city, and the method comprises the steps: obtaining the multi-source sensing data of a city, and carrying out the data preprocessing, and the multi-source sensing data comprises city image data, point cloud data and GIS data; converting the preprocessed multi-source sensing data in different formats into a preset standard format, and performing registration and fusion of the multi-source sensing data to obtain fused multi-source data; performing data optimization on the fused multi-source data, and constructing a city-level three-dimensional real scene model according to the optimized fused multi-source data and a preset three-dimensional space analysis tool; the preset three-dimensional space analysis tool provides space analysis and three-dimensional space visualization functions; according to the invention, efficient and accurate real-scene three-dimensional data of a city is provided, and three-dimensional and visual space information is provided.

The invention relates to the technical field of traffic management, in particular to a smart city intelligent traffic management system based on big data, which comprises a multi-source data acquisition module, a data fusion module, a dynamic feature generation module, a situation prediction module, a multi-target optimization module and an instruction execution module, the multi-source data acquisition module acquires multi-source data in real time; the data fusion module generates a standardized traffic data flow and outputs a three-dimensional data cube; the dynamic feature generation module outputs a traffic feature matrix; the situation prediction module generates a dynamic situation map; the multi-objective optimization module outputs an optimization instruction set; and the instruction execution module issues a control instruction to the traffic signal controller, the variable information board and the vehicle-mounted terminal. According to the invention, traffic jam can be relieved, road traffic efficiency can be improved, bus priority scheduling can be optimized, vehicle delay can be reduced, and emergency response speed can be improved.

The invention discloses a building structure monitoring and management method, system and equipment and a storage medium, and relates to the field of civil engineering. The method comprises the following steps: acquiring three-dimensional data of a building structure, and constructing a digital twinborn model of the building structure according to the three-dimensional data; acquiring real-time state data of the building structure from a preset sensor network, and comparing the real-time state data with reference state data in the digital twin model; and when the difference between the real-time state data and the reference state data in the digital twin model is smaller than a first threshold value, performing performance prediction and life evaluation on the building structure according to the real-time state data in combination with influence factors. By implementing the technical scheme provided by the invention, informatization and intelligent management of the whole life cycle of the project is realized.

The invention provides a machine room control method and system based on communication between an air conditioner terminal and a water chilling unit, and the method comprises the steps: obtaining three-dimensional data and equipment attribute data of a machine room and accessory equipment of the machine room through a server, and building a digital twinborn model of the machine room; the server establishes a dynamic load prediction model and sends the dynamic load prediction model to a first controller of the water chilling unit; the intelligent sensor collects environment data and equipment data; a second controller of the air conditioner terminal obtains the environment data and sends the environment data to the first controller; the first controller predicts the cold load change according to the dynamic load prediction model and the historical data and adjusts the operation strategy of the air conditioning system; the server simulates a machine room environment and an equipment operation condition in real time by using a digital twin model, generates a control strategy in combination with a self-adaptive control strategy after evaluating a result, and sends the control strategy to the first controller; and the first controller dynamically adjusts operation parameters of the air conditioning system according to the strategy. By means of the scheme, efficient, intelligent and accurate real-time monitoring and control over the energy efficiency of the air conditioning system can be achieved.

The invention discloses a power distribution network tower abnormity monitoring method and system, and relates to the technical field of tower monitoring, and the method comprises the steps: arranging a multi-mode sensor on a power distribution network tower, and collecting the state data of the tower; constructing a power distribution network tower digital twinborn model, inputting tower state data, and predicting the future state of the tower; performing regular inspection on the tower by using an unmanned aerial vehicle, and collecting dynamic three-dimensional data of the tower; and the tower state data, the tower future state prediction result and the tower dynamic three-dimensional data are fused, and tower abnormity is monitored and early warning is performed. The invention also discloses a method. Through the application of the multi-source data fusion technology, the accuracy and reliability of anomaly detection are effectively improved, professional guidance is provided for maintenance personnel based on a grading early warning mechanism of a comprehensive anomaly index, the fault processing efficiency is improved, the accuracy and timeliness of tower anomaly monitoring are remarkably improved, and the safety and reliability of the tower are improved. And predictive maintenance and intelligent management are also realized, and the safety and reliability of the power distribution network are greatly enhanced.

The invention relates to the technical field of visual rendering, and provides a three-dimensional data visual rendering method and a visual rendering engine system.The method comprises the steps that space segmentation processing is conducted on three-dimensional model data to be rendered through the LOD technology to generate block slice data with different geometric detail levels, organizing the block slice data through a tree structure with a spatial relationship, and outputting the tree structure as an index file; the method comprises the following steps: adaptively screening block and slice data of different levels of detail based on a user vision field range, storing the block and slice data into a rendering request queue, querying block and slice data to be rendered from the rendering request queue according to index codes of the block and slice data, and updating a layer browser database; according to the method, to-be-rendered block slice data are downloaded and analyzed in parallel in batches in a separated collaborative operation mode, and a rendering task is executed according to a data analysis result, so that the rendering scheduling frame rate is remarkably improved, and rapid visualization of urban mass three-dimensional slice data at a webpage end is realized.

The invention provides a three-dimensional space data analysis method and system based on deep learning, and relates to the field of computer vision, and the method comprises the steps: carrying out the modeling of a static scene fundamental model and a dynamic object motion track through a space-time separated dynamic nerve radiation field; a lightweight dynamic neural radiation field model is deployed at an edge computing node, multi-modal sensor data are processed in real time, local three-dimensional scene representation is generated, rendering and prediction computing of a neural radiation field are executed on the edge node, and the implicit feature difference quantity of scene change is uploaded to a cloud; and the cloud end aggregates feature difference data of multiple edge nodes through a federated learning framework, dynamically updates a global scene priori knowledge base and issues the global scene priori knowledge base to the edge nodes. The method can improve the processing efficiency, precision and applicability of the three-dimensional data, and is especially suitable for carrying out tasks such as object recognition, target detection and semantic segmentation in a complex environment.

The invention relates to the technical field of water quality detection, and discloses a water quality pollutant detection method, system and equipment based on spectral analysis, and the method comprises the following steps: carrying out real-time spectral data acquisition on a water body sample in a vehicle driving process through a multispectral sensor array in a vehicle-mounted water quality detection device; obtaining a water body spectrum three-dimensional data cube; carrying out anti-vibration wavelength calibration and ambient light source interference elimination processing to obtain a preprocessed spectrum data set; performing standard multivariate decomposition processing and horizontal local constraint optimization of a pollutant target wave band on the preprocessed spectrum data set to obtain enhanced feature fingerprint spectrums for different types of water quality pollutants; and inputting the enhanced feature fingerprint spectrum into a deep belief network model to perform pollutant feature matching analysis to obtain various pollutant types and corresponding concentration values in the water body sample, thereby effectively eliminating ambient light changes and other background interferences, not only determining the pollutant types, but also accurately quantifying the concentration values.

The invention relates to the technical field of nondestructive testing, in particular to a lead seal defect detection method based on a phased array ultrasonic testing technology. The invention discloses a lead seal defect detection method based on a phased array ultrasonic detection technology. The method comprises the following steps: acquiring surface three-dimensional data; carrying out data processing and modeling; phased array ultrasonic detection preparation; performing ultrasonic scanning; data analysis and defect identification; positioning and quantifying defects; and performing evaluation and report generation. According to the method, laser scanning is combined with phased array ultrasound, microscopic and macroscopic characteristics of the surface of the lead seal are obtained through laser scanning, an accurate three-dimensional geometric model is generated, the solid form of the lead seal is reproduced, a visual reference frame is provided for subsequent phased array ultrasound, and self-adaptive frequency adjustment and dynamic focusing control technologies are combined, so that the accuracy of the lead seal is improved. Different areas and heterogeneity of the lead sealing material are identified, the focusing position and depth of the ultrasonic beam are adjusted in real time, and the flexibility and accuracy of defect detection are improved.

The invention relates to a dynamic load distribution method, device and equipment based on a vehicle body controller and a medium, and the method comprises the steps: collecting the mechanical load, electrical load and thermal load data of a vehicle body in real time through a distributed sensor network, and generating multi-source heterogeneous initial load data; performing standardization processing on the initial load data, and constructing a three-dimensional data cube type standard load data set; comprehensive characterization features are extracted through feature space mapping, and a fusion load feature set containing a threshold range is dynamically generated in combination with historical data; constructing a load correlation model based on the fusion features, and mapping to generate a steering and braking control parameter combination; and according to the real-time load threshold cross-border state, dynamically adjusting the task priority, allocating real-time calculation core resources to the chassis system, and generating an optimal allocation scheme. According to the method, the problems of multi-source load data fusion failure, resource allocation rigidity and safety task response delay in the prior art are solved, and dynamic load optimization of the vehicle body control system under complex working conditions is realized.

The invention discloses a BIM-based two-dimensional data and three-dimensional model verification matching method and system. The system comprises a 2D drawing processing module, a 3D model processing module, a difference detection module and a report generation module. In the 2D drawing processing module, a user imports a process pipeline plan and a profile map, and through preprocessing and image semantic analysis, pipeline elevation labeling information is extracted and numbered. And the 3D model processing module loads a target BIM model, locates a process pipeline area, analyzes pipeline parameters and a space state, analyzes a pipeline topological relation and performs conflict verification. And the difference detection module binds the 2D drawing with a corresponding pipeline object in the 3D model, establishes a mapping relation, compares differences, and performs labeling and classification. And the report generation module is used for carrying out visual annotation in the 2D drawing and the 3D model based on the annotation difference, automatically generating a difference comparison table and outputting a report, so that efficient and accurate verification and matching of the two-dimensional data and the three-dimensional data are realized, the examination period is shortened, and the rapid collaborative correction efficiency of the construction team is improved.

The invention discloses a power generation equipment state fault diagnosis method and system based on artificial intelligence, and the method comprises the steps: actively injecting a mechanical excitation signal of a preset frequency spectrum into a key part according to a physical topological structure of power generation equipment, and carrying out the fusion to generate a time-space-frequency three-dimensional data volume; inputting the three-dimensional data volume into a physical embedded variational auto-encoder, and outputting an equipment state pure feature tensor; inputting the pure feature tensor into a graph space-time causal reasoning network to generate a fault propagation causal graph with probability weight; performing multi-agent diagnosis on the fault propagation causal atlas, and outputting a fault diagnosis report which has a credibility interval and comprises fault positioning and root cause analysis; and mapping the fault diagnosis report to the digital twin of the equipment in real time, and outputting a self-adaptive maintenance strategy sequence which minimizes the expected value of the whole life cycle operation and maintenance cost. According to the embodiment of the invention, the accuracy and anti-interference capability of fault diagnosis can be improved, and the operation and maintenance cost can be effectively reduced.

The invention belongs to the technical field of path planning, and particularly relates to a charging path planning method for an intelligent mobile charging vehicle, and the method comprises the steps: collecting the three-dimensional data information of a charging scene through a camera and a laser radar, and constructing a three-dimensional space model; image acquisition of a charging scene is carried out through a camera and a laser radar, and a plane navigation map is established; after the mobile charging vehicle receives a charging instruction, performing global path planning based on an improved PSO algorithm to obtain an optimal path; real-time image acquisition is carried out through a camera and a laser radar, local path planning is carried out through an improved DWA algorithm, obstacles are avoided in time, and whether a target point is reached or not is verified; and the charging manipulator grabs the charging wire to perform charging operation. According to the invention, the optimization of global and local path planning is realized, the accuracy and efficiency of path planning are improved, and the charging vehicle can safely and quickly reach the target charging position.

The invention provides an automatic building design scene generation method and system based on artificial intelligence. According to the method, a geometric feature parameter library and a spatial topological relation parameter library of a special-shaped component are integrated, an artificial intelligence optimization engine is used for carrying out conjoint analysis, and a building scene dynamic form constraint map is created. The process comprises the following steps: acquiring three-dimensional data of a construction site by using laser point cloud scanning, and extracting real-time curvature gradient parameters and functional region connection node parameters from the three-dimensional data; and then matching verification is carried out on the parameters and corresponding threshold values and conditions in the dynamic form constraint map, so that a building scene self-adaptive correction parameter set is generated. And finally, building component processing track control points are adjusted based on the parameter set, and a construction instruction containing spatial form and functional topology linkage is formed. According to the technical scheme provided by the invention, the efficiency and flexibility of building design scene automatic generation can be improved.

The invention provides a real-time deep sea subsurface buoy monitoring system, which belongs to the technical field of deep sea measurement, and comprises a control chip, a multi-parameter sensor array, a data storage device and a power supply, high-precision monitoring is realized through the following steps: recording ocean data acquired by a multi-parameter sensor; correcting the sound wave propagation model and calculating the relative position of the subsurface buoy; constructing a three-dimensional data matrix and realizing data compression; identifying abnormal data by using a matrix disorder index; processing the time sequence data by adopting a sliding window weighted average method and eliminating jump; carrying out distributed preprocessing on the multi-source heterogeneous data and carrying out parallel processing by applying a matrix partitioning technology; accumulated errors are corrected by combining historical data and applying a Kalman filtering algorithm, and the problems of environment interference and sensor drift are solved through a deep sea environment disturbance compensation network model and a self-adaptive weighted error optimization function.

The invention discloses a low-altitude three-dimensional data acquisition method and system for an unmanned aerial vehicle, and particularly relates to the field of three-dimensional data acquisition, and the method comprises the steps: selecting a four-rotor unmanned aerial vehicle, carrying a laser radar, a high-resolution camera and high-precision positioning equipment, and carrying out the low-altitude flight; the laser radar collects surface information, and the camera shoots a ground image; then, processing the acquired data, including abnormal value removal, missing value supplementation, image denoising and image enhancement; thirdly, converting the processed data into three-dimensional point cloud data, and identifying an image to obtain an actual appearance and a name of a target object; and finally, performing high-precision topographic surveying and mapping and three-dimensional modeling according to the processed three-dimensional point cloud data to generate a final three-dimensional model.

The welding path autonomous optimization system includes a quality—welding-condition correlation database in which a constraint condition of welding by a welding robot that operates a welding torch is stored, an interference analysis part configured to determine a welding path that does not interfere with an object to be welded based on three-dimensional CAD data of the object to be welded and the constraint condition stored in the quality—welding-condition correlation database, and a welding-robot-operation / welding-condition output part configured to output welding process information based on the welding path.

The invention relates to a milling cutter machining method and system based on a CAM simulation technology, and the method comprises the steps: obtaining three-dimensional data of a workpiece mold and milling cutter parameters, and carrying out the process planning, and obtaining an initial workpiece machining strategy; cutter path planning and contact point calculation are conducted on the initial workpiece machining strategy, and a corresponding cutter movement path is obtained; carrying out CAM simulation analysis on the initial workpiece machining strategy to obtain corresponding real-time simulation data, and carrying out collision interference detection on the tool movement track according to the real-time simulation data to obtain a corresponding safe movement path; carrying out cutting force and cutting temperature analysis on the safe motion path to obtain a corresponding process verification result; and carrying out machining analysis on the safe motion path and the cutter predicted use data, and carrying out NC machining code optimization on the initial workpiece machining strategy to obtain a corresponding optimized workpiece machining scheme. The machining strategy can be flexibly adjusted according to the characteristics and machining requirements of different workpieces.

Systems and methods for generating simulation data based on real-world environments are provided. A method includes obtaining multi-modal sensor data indicative of a dynamic object within an environment of a robotic platform. The multi-modal sensor data is associated with a plurality of timesteps including a first timestep and a second timestep. The method includes providing the multi-modal sensor data indicative of the dynamic object within the environment as an input to a machine-learned dynamic object removal model. And, the method includes receiving as an output of the machine-learned dynamic object removal model, in response to receipt of the multi-modal sensor data, a scene representation indicative of at least a portion of the environment including a reconstructed region based at least in part on removal of the dynamic object and multiple levels of granularity. The scene representation is used as a template for generating different simulations within the depicted environment.

The invention discloses a construction project whole-process management system and method with a BIM3D-6D technology as a base, and relates to the technical field of construction project management, and the method comprises the steps: loading a 3D building information model through a BIM lightweight calculation server, extracting the spatial topological relation and IFC semantic attributes of geometric components, and carrying out the calculation of the 3D building information model through a BIM lightweight calculation server; spatial topology analysis and semantic attribute mapping are carried out on the spatial topology relation of the geometric components and the IFC semantic attributes, and a three-dimensional data topology network packet based on a graph structure is generated; performing multi-dimensional deduction operation on the three-dimensional data topology network packet based on the graph structure to obtain a deviation compensation strategy containing an optimal cost control path; and carrying out dimension expansion and data fusion on the 3D building information model to generate a 5D cost dimension data set. Discrete decisions are converted into a continuous field model through mathematical transformation, so that a resource flow path has spatial relevance and time continuity, and the beneficial effect of dynamically optimizing a construction process is achieved.

The invention relates to the technical field of image processing, and discloses a visual positioning system and method for a complex box five-axis numerical control comprehensive processing machine. The system comprises a calibration module for collecting multi-angle images and utilizing mark point calibration coordinates to obtain a parameter mapping table, an extraction module for carrying out edge detection and contour extraction splicing features to obtain a three-dimensional data set, a marking module for calculating the actual position of a box and marking inner cavity machining areas, a recording module for analyzing and determining cutting parameters and deformation of all the areas, and a display module for displaying the cutting parameters and the deformation of all the areas. The processing module generates an obstacle avoidance cutter path and a thin-wall area machining strategy, and the comparison module monitors and compares actual effects to dynamically adjust parameters to obtain compensation data. According to the five-axis numerical control comprehensive processing machine, high-precision visual positioning and intelligent processing parameter optimization of the complex box on the five-axis numerical control comprehensive processing machine are realized, and the processing precision, efficiency and reliability of the complex box are improved.

The invention relates to the technical field of CIM (common information model) platforms, in particular to a multi-element and multi-scale data management method and system based on a CIM basic platform, and relates to data acquisition, access and classification in a service interface, incremental acquisition and offline copying mode. Data needs to be translated to conform to spatial, elevation and temporal references of a CIM platform, unify geocoding and spatial expression, and semantic-based place name address association. And the BIM and the CIM are fused through a knowledge graph. And performing three-dimensional data grading processing, and constructing CIM1 to CIM5 grade data. Government affair data are subjected to graph falling through a unified address library. Overall data governance covers data aggregation, classified governance, two-dimensional and three-dimensional fusion, BIM and CIM fusion technology and government affair data association, classification and level-to-level management of data is realized, different data combination application is supported, and CIM business application and government affair process auxiliary approval and decision making are assisted.

The invention relates to the technical field of data processing, in particular to a confidential propaganda and education system based on multi-modal interaction, which comprises a data acquisition module, a data processing module, a training module and an optimization module. The data collection module collects user eye movement tracks, voice instructions, operation behaviors and physiological signal data, noise is eliminated through time synchronization and self-adaptive filtering, and then a three-dimensional data cube is constructed through a tensor decomposition algorithm. And reversely adjusting knowledge graph nodes and scene parameters by using a genetic algorithm to form a closed-loop feedback link. And the cross-module cooperation unit aggregates a global cognitive feature model through a federated learning framework, and realizes privacy protection and resource dynamic allocation in combination with differential privacy protection and an ant colony optimization algorithm. Through multi-modal data fusion, dynamic strategy generation and closed-loop evaluation optimization, the problem of unidirectional interaction and feedback lag of a traditional system is solved, and user confidential knowledge internalization efficiency and complex scene coping capacity are improved.

The invention discloses a tunnel crack detection method and a tunnel crack detection system, and belongs to the field of tunnel safety detection.The tunnel crack detection method comprises the steps that a tunnel inspection robot is utilized to conduct inspection in a tunnel to obtain complete three-dimensional data in the tunnel so as to construct a three-dimensional map in the tunnel, and the position of each crack area in the three-dimensional map is determined; determining an inspection tour area corresponding to each crack area and executing path planning, and generating an optimal inspection tour path of the unmanned aerial vehicle; the optimal inspection path enables the unmanned aerial vehicle to sequentially pass through each inspection area and then leave the tunnel after entering the tunnel under the condition that obstacle avoidance conditions are met, and the total time is shortest; enabling the unmanned aerial vehicle to move according to the optimal inspection path, and scanning the crack region by using the depth camera when the unmanned aerial vehicle moves to one inspection region so as to obtain fine three-dimensional data of the crack region; and performing analysis processing on the fine three-dimensional data of the crack area to complete tunnel crack detection. According to the invention, the efficiency and precision of long tunnel crack detection can be improved.

The invention discloses an LSTM-COF-based power equipment data anomaly detection method and system, and relates to the technical field of power equipment state monitoring, and the method comprises the following steps: collecting historical data, and constructing a three-dimensional data matrix; predicting equipment parameters at the extreme temperature through an LSTM model; compressing the features, quantifying the covariance deviation degree between the features in combination with a correlation abnormal factor algorithm, and detecting abnormal points; the system integrates a data collection module, a data preprocessing module, a data prediction module, a detection model generation module and a visualization module. According to the method, the multi-dimensional historical operation data of the power equipment is collected, the equipment parameters in the extreme temperature environment are predicted by using the LSTM model, the principal component analysis dimensionality reduction and correlation abnormal factor algorithms are combined, insulation degradation type and electrical connection type faults can be dynamically identified, the data distribution change is adapted through the incremental learning mechanism, and the fault diagnosis accuracy is improved. The problems of low high-dimensional data processing efficiency and poor anomaly detection adaptability due to manual experience dependence in a traditional method are solved.

The invention provides an oral implant navigation method and system and a storage medium, after an optical locator is fixedly arranged on an implant mobile phone, three-dimensional data of a rotating shaft of the implant mobile phone, the tail end of the rotating shaft and a spherical drill on an optical three-dimensional coordinate system of the optical locator are obtained, and a registration pit is used as a medium to obtain a three-dimensional coordinate system of the implant mobile phone; and positioning three-dimensional data of the three-dimensional coordinate system in the optical three-dimensional coordinate system, registering the three-dimensional data of the pits on the CT three-dimensional coordinate system to complete registration, calculating the pose of the tip of the drill point and the pose of the ideal path under the positioning three-dimensional coordinate system, and performing real-time navigation on the planted mobile phone according to the difference between the tip of the drill point and the ideal path. An optical positioning instrument is fixedly arranged on the planting mobile phone, and while the planting mobile phone is used for drilling operation, image data of the optical identification points are collected through the optical positioning instrument for real-time navigation; the optical positioning instrument and the planting mobile phone are integrally connected, so that the process of positioning the planting mobile phone in real time can be omitted, and navigation errors are effectively reduced.

The invention discloses a city-level CIM scene streaming rendering method based on multi-modal fusion, and the method comprises the following steps: S1, collecting city data, and carrying out the preprocessing of the city data; s2, establishing a cross-modal entity alignment relationship, and constructing a city object structure body; s3, dividing a space by adopting a quadtree method, generating rendering sub-blocks and distributing a unique space code; s4, binding the rendering sub-blocks with the urban object structure body, constructing a multi-modal fusion network, and generating a multi-modal rendering unit set; s5, constructing an inter-frame rendering cost function, and scheduling and sequencing the multi-modal rendering unit set to form an inter-frame scheduling sequence; s6, loading the rendering units according to the inter-frame scheduling sequence to form a city-level three-dimensional view of continuous frames; and S7, updating the scheduling sequence, dynamically adjusting the loading sequence, and realizing stable and efficient streaming rendering of the city-level CIM scene. According to the method, the fusion efficiency and rendering performance of the urban large-scale three-dimensional data are improved, and the method has remarkable engineering applicability and popularization value.