156 results about "Virtual mirror" patented technology

The invention discloses an ocean holographic environment comprehensive digital twinning system, and relates to the technical field of ocean monitoring, the digital twinning system comprises a data layer, a model layer, an application layer, an environment layer, a governance layer and a service layer, multi-scale spatio-temporal data is used as a substrate, and a virtual-real mapping and intelligent simulation technology is used to simulate the ocean holographic environment comprehensive digital twinning system. A full-dimension virtual mirror image covering the seabed, the middle sea and the sea surface is constructed, and the system serves core scenes such as a supervisor, scientific research cooperation and ocean engineering. According to the digital twin system, a six-layer layered architecture is adopted, edge computing and cloud computing collaboration are combined, a data-model-service-governance-environment multi-dimensional collaboration system is formed, data-driven decision making and dynamic optimization are achieved, and the marine monitoring efficiency and accuracy are improved.

The invention provides a digital twinborn model and method for a coal mine disaster scene based on multi-modal data. The method comprises the following steps: acquiring original data in a mine; performing cleaning, normalization and de-noising preprocessing on the original data; fusing different types of preprocessed original data by using a data fusion algorithm, and constructing a comprehensive digital twinborn model; establishing a virtual mirror image of the mine by using a digital twinning technology, and mapping the mine in the real world into a digital twinning model; real-time mapping and simulation analysis are carried out based on the established digital twinborn model, and the disaster development trend is predicted by monitoring the internal environment and the equipment state of the mine; and according to a model analysis result, optimizing prevention and control measures of coal mine disasters, establishing a real-time monitoring and early warning system of the disasters, and taking measures in time when abnormal conditions are found. The system comprises a data acquisition module, a model construction module and a model analysis module. The pertinence and effectiveness of coal mine disaster prevention and control can be improved.

The invention discloses an energy management three-dimensional visualization method and system based on digital twin and Internet of Things, and relates to the technical field of energy management visualization, and the method comprises the steps: obtaining multi-source heterogeneous energy data of an energy management object; constructing a virtual mirror image model corresponding to the physical energy system based on the multi-source heterogeneous energy data and the digital twin model; generating a three-dimensional visual scene based on the virtual mirror image model so as to map the geographic position distribution of the physical energy system, and presenting the real-time energy consumption state, the energy flow transmission path and the environmental parameter change of the equipment; receiving a user interaction instruction, carrying out interaction operation on the target area or equipment, calling the associated multi-source heterogeneous energy data, and carrying out superposition display on the associated multi-source heterogeneous energy data; energy consumption abnormity early warning information or an equipment regulation and control strategy is generated in combination with the energy management optimization rule, and the equipment regulation and control strategy is input into the physical energy system to be executed. The invention provides an energy management method capable of realizing multi-source data fusion and accurate mapping of a physical system.

The invention relates to the technical field of high-end chips, and discloses a packaging defect detection method and system for an industrial solid state disk, and the method comprises the steps: collecting multi-source heterogeneous detection data, and extracting the multi-dimensional defect features of a packaging body; packaging process parameters and material attributes of the industrial solid state disk are input into the virtual mirror image body, and a defect sensitivity distribution diagram of the packaging body is generated; identifying a defect expansion path and a defect type of the packaging body; based on the process weak link, the defect expansion path and the defect type, generating a grading defect detection instruction of the packaging body; setting a personalized defect detection mode of the packaging body in combination with the number of NAND stacked layers, the solder ball spacing and the defect type; and outputting a defect detection result of the packaging body through the virtual mirror image body by utilizing a grading defect detection instruction and a personalized defect detection mode. According to the method, the accuracy and credibility of an industrial solid state disk packaging defect detection result can be effectively improved.

The invention relates to a digital twin simulation and optimization method for a large-scale stamping production line, and the method comprises a rapid lightweight modeling technology, a multifunctional fault indicator feedback technology, a three-dimensional dynamic real-time driving simulation technology, and a big data analysis intelligent optimization decision technology. According to the method, virtual-real fusion and a three-dimensional dynamic technology are combined, a three-dimensional visual user interface oriented to the whole manufacturing process is developed based on Unity, the whole stamping production line is simulated in real time, potential problems are predicted and solved through real-time monitoring of the stamping production line, various problems influencing the production efficiency in the production process are optimized, and the manual management and control difficulty is reduced.

The invention relates to the technical field of industrial automation and intelligent manufacturing, and discloses an industrial big data simulation verification system based on digital twinning, and the system comprises a physical entity module which is used for deploying an industrial sensor array and collecting the real-time parameter data of production equipment; the digital twin mirror image module is linked with the physical entity module through a data mapping engine, and synchronously updates a virtual mirror image model at a millisecond level according to the parameter change of the physical entity; and the data transmission module is used for transmitting the data acquired by the physical entity module to the digital twin mirror image module and the multi-source data fusion module through a 5G or industrial Ethernet, and is used for cleaning the acquired multi-modal industrial data and eliminating noise data. Through the physical entity-digital twin mirror image real-time linkage design, the limitation that traditional simulation is disjointed with entities is broken through. The industrial sensor array is combined with the edge calculation module, so that rigid linkage of physical production equipment, a real-time database and a digital twin mirror image is realized.

The invention discloses a coal mine water flowing fractured zone observation method, device and system and a storage medium, and belongs to the technical field of coal mine safety monitoring and early warning. The method comprises the following steps: constructing an initialized transparent geologic model; acquiring historical fracture electrification method data; the initialized transparent geologic model is used for processing historical fracture electrification method data so as to construct a roof water flowing fractured zone virtual mirror image; processing the virtual mirror image of the roof water flowing fractured zone by using a numerical simulation algorithm to obtain simulation monitoring data; obtaining monitoring difference data according to the simulation monitoring data and the electrical method data characteristics corresponding to the early warning threshold; optimizing the initialized transparent geologic model according to the monitoring difference data to obtain a target geologic model; acquiring fracture electrification method data through a drilling electrical method technology; inputting the fracture electrification method data into the target geologic model to obtain monitoring data; judging whether the monitoring data exceed an early warning threshold value or not; and if yes, triggering an early warning mechanism.

A scanner redirection method for a remote desktop computer system that includes a client computer, a first virtual machine (VM), and a second VM, includes the steps of: receiving by the first VM from the second VM, a first request for an image, wherein the first request for the image is directed to virtual image capturing software in the first VM; in response to the first request for the image being directed to the virtual image capturing software, transmitting by the first VM to the client computer, a second request for the image, wherein the second request for the image is directed to an image capturing device connected to the client computer; and upon receiving the image from the client computer, transmitting by the first VM to the second VM, the image received from the client computer.

The invention belongs to the technical field of railway inspection, and particularly relates to a contact network safety inspection while shooting device based on image recognition, which comprises an acquisition end, an intelligent analysis end and an observation panel, the acquisition end is fixedly mounted on a train, and is used for synchronously acquiring continuous visible light images and infrared images of a contact network in the running process of the train, and transmitting the images to the intelligent analysis end in real time through a high-speed low-delay link; the intelligent analysis end calls a mirror image progressive multivariate fusion defect inference algorithm to generate a mirror image grid sequence, and grid correspondence is carried out on the visible light image and the infrared image in a virtual mirror image plane; a focusing clear frame is extracted after each time of sliding; multivariate feature fusion is carried out on the focusing clear frame, and a fusion result enters a defect candidate set. According to the invention, real-time and accurate inspection of catenary defects is realized in a high-speed operation and complex environment.

The invention discloses a control method and device of a vehicle cloud cooperative system and a vehicle, and relates to the technical field of vehicles. The method comprises the steps that a vehicle twinning request is acquired, and the vehicle twinning request carries a vehicle identifier and operation state data of a vehicle; based on the vehicle twinning request, virtual twinning and a channel key are generated, the virtual twinning is a virtual mirror image matched with the running state of the vehicle, and the virtual twinning is used for simulating the running state of the vehicle and predicting future behaviors of the vehicle; establishing a communication channel based on the channel key, and transmitting the current operation state data and the target demand of the vehicle based on the communication channel; analyzing the current operation state data and the target demand based on the virtual twinning to obtain an analysis result; and determining a target decision based on the analysis result, and controlling vehicle driving based on the target decision. According to the invention, the technical problems of unstable network connection, delayed state synchronization and limitation of an intelligent decision-making mechanism of a vehicle cloud cooperative system in the related technology are solved.

The invention relates to the technical field of virtual reality, in particular to a virtual reality-based smart travel big data supervision platform, which comprises a data acquisition layer for acquiring multi-source data, a data processing layer for preprocessing the multi-source data to form a data packet, and a data transmission layer for transmitting the data packet, acquiring a data packet and constructing a virtual reality layer of the three-dimensional virtual mirror image space; and the supervision application layer is used for supervising the three-dimensional virtual mirror image space, and respectively issuing a priority transmission instruction of data at the problem to the data transmission layer and issuing a real-time reconstruction instruction of a three-dimensional scene at the problem to the virtual reality layer when the problem is monitored. According to the invention, in the data transmission layer, the redundant data shell of the protection data packet is dynamically adjusted according to the network quality, the temporary dedicated channel is constructed based on the SDN, and the data of the problem area directly reaches the virtual reality layer, so that the high-fidelity restoration and supervision of the virtual scene in the weak network environment are realized.

The invention discloses a data processing method and related equipment so as to improve the starting speed of a confidential virtual machine. The method comprises the following steps: receiving a secret virtual machine mirror image from client equipment and a hash tree corresponding to the secret virtual machine mirror image, and measuring a value of a root node of the hash tree to obtain a first measurement value; and running the confidential virtual machine according to the confidential virtual machine mirror image, wherein the first metric value is used for proving the integrity of the confidential virtual machine.

The invention discloses an active congestion avoiding method and system based on flow prediction, and relates to the technical field of network communication, and the method comprises the steps: collecting the network state information of a physical network in real time; dynamically synchronizing and mapping network state information of a physical network to a virtual mirror image by using a digital twinning technology; under the virtual mirror image, traffic prediction is carried out on the network state information based on a time domain convolutional network model, and a traffic prediction result is obtained; the traffic prediction result is transmitted into a scheduling strategy engine for dynamic analysis and evaluation, and an active traffic scheduling strategy for traffic prediction is determined; issuing the active flow scheduling strategy to a physical network for execution; and according to the latest network state information, an active flow scheduling strategy is dynamically adjusted to form a closed-loop adaptive system. According to the method, the virtual mirroring of the network state information is realized by using the digital twin technology, the traffic prediction result is obtained by using the time domain convolutional network model, and the traffic scheduling strategy is actively adjusted before traffic congestion occurs, so that congestion is effectively avoided.

The invention relates to the technical field of smart home, and discloses a virtual environment image home control method and system under digital twinning, and the method comprises the steps: building a digital twinning body through the physical data of a home scene, and building a user 3D human body model based on the human body scattered wave data, so as to generate a virtual mirror image; creating a communication channel between the virtual mirror image and the home equipment so as to construct a control interface of the virtual mirror image to the home equipment; based on the current behavior intention, setting a personalized control instruction of the virtual mirror image to the home equipment; according to the time sequence image and the behavior tracking network, setting a real-time synchronization mechanism of the virtual mirror image and the home scene, and constructing data binding of the home device and the virtual mirror image; and in combination with the virtual mirror image, the control instruction, the scene synchronization mechanism and the data security interaction system, executing the control instruction of the home equipment. According to the invention, one-to-one correspondence between the pictures displayed by the digital twinning and the real scene can be realized, so that a user can accurately control the actual state of the supervised object.

The invention belongs to the technical field of goods shelf arrangement optimization, and provides a digital twinning-based goods shelf arrangement optimization method, which comprises the following steps of: acquiring storage goods shelf dynamic data in real time and transmitting the storage goods shelf dynamic data to an edge computing node, and performing fusion processing on the storage goods shelf dynamic data by adopting a spatio-temporal data fusion technology, and dynamically refreshing a virtual mirror image of the storage shelf layout through three-dimensional modeling, and constructing a real-time digital twinborn model of the storage shelf. According to the method, the prediction model is constructed by using the Transform time sequence prediction algorithm, whether the orders are in the increasing trend is judged based on the chaos theory, the order change trend can be captured, potential order quantity increase can be perceived in advance, a basis is provided for planning shelf arrangement optimization in advance, unsatisfactory storage coping when the orders are suddenly increased is avoided, the stability of storage operation is guaranteed, and the storage efficiency is improved. And when the order increase trend is predicted, the generated scheme comprehensively considers various factors, so that the goods in-out warehouse time can be shortened, the goods picking path can be optimized, and the overall warehousing operation efficiency can be improved.

The invention provides a multi-Agent-based workshop management system and a cross-workshop migration method and system. The multi-Agent-based workshop management system comprises a sensing layer, an intelligent layer, an execution layer and a communication layer, a data acquisition module of the sensing layer is used for acquiring sensing data in a physical scene, and a sensing Agent of the sensing layer generates a corresponding virtual mirror image platform according to the sensing data and outputs an analysis result; the intelligent layer comprises a decision-making Agent and a coordination Agent, the decision-making Agent dynamically generates a global or local decision-making result according to an analysis result, and the coordination Agent monitors and evaluates the decision-making result through a preset mechanism and outputs an optimization strategy; the intelligent layer transmits the decision result and the optimization strategy to the execution layer; an execution Agent of the execution layer deploys a lightweight model through an edge calculation module, and analyzes a decision result and an optimization strategy into an equipment control signal to control equipment operation; and the communication layer provides an information interaction channel for the Agent of each layer. The limitation of a traditional layered architecture is broken through, and a self-organized, self-adaptive and self-optimized distributed intelligent ecological architecture is constructed.

The invention belongs to the technical field of new energy automobile liquid cooling systems and liquid leakage detection methods, and particularly discloses a liquid cooling plate liquid leakage detection system and a liquid leakage detection method.Pressure detection modules are arranged at a liquid inlet and a liquid outlet of a liquid cooling plate, the pressure difference of the liquid inlet and the liquid outlet of the liquid cooling plate is collected in real time, and whether liquid leakage occurs or not is judged through a processing module; meanwhile, more than three acoustic emission signal detection modules are arranged on the liquid cooling plate, acoustic emission signals on the surface of the liquid cooling plate are collected in real time, a processing module calculates the information source position of the acoustic emission signals through a positioning algorithm and stores the information source position, the information source position is further compared with the storage time of the liquid leakage judgment result, and the liquid leakage point position of the liquid cooling plate is determined. The method is implemented through the virtual mirror image model of the liquid cooling plate, so that a vehicle user or a maintainer can quickly and accurately position the liquid leakage position and take corresponding treatment measures, and the maintenance efficiency can be improved. According to the invention, the real-time accurate monitoring of the liquid leakage condition of the liquid cooling plate is realized, and the liquid leakage point positioning and display functions are realized.

The invention discloses a transformer substation abnormity intelligent diagnosis method based on a self-attention mechanism, and relates to the technical field of transformer substation abnormity identification, and the method comprises the following steps: S2, employing a computer vision technology, a sensor, an ultrasonic detector, and a current and voltage detector to collect the electrical parameters of equipment, and completing the collection of multi-source data; s3, realizing a virtual mirror image of the physical equipment by using a digital twinning technology; and S5, analyzing and processing the important information in the database through a self-attention mechanism, and predicting the health trend, risk point and service life of the substation equipment. According to the method, image information and equipment parameters of substation equipment are collected in real time, an attention weight matrix of data is obtained through calculation, multi-source data are associated, the fault probability is output, then a regression device is used, key parameter values of multiple time points in the future and the remaining service life are output, and the service life of the substation equipment is calculated. And predicting the health trend, the risk point and the service life of the substation equipment.

The invention relates to the technical field of agent training, and discloses an agent training system based on a mirror image. The system comprises a training environment mirror image module, a behavior feature reconstruction module and a training decision model module. The training environment mirror image module constructs a virtual mirror image environment which is completely synchronous with a real physical environment, covers an environment state parameter set, an agent interaction record sequence and a performance index time sequence, and can reproduce a real environment complex dynamic scene. And the behavior feature reconstruction module performs three-dimensional behavior trajectory analysis on the agent interaction record sequence, generates a behavior feature tensor containing a decision response delay gradient, an action space coverage degree and a cooperation intention fluctuation coefficient, and realizes multi-dimensional behavior analysis. And the training decision model module calls a pre-training agent evolution model, performs strategy space mapping on the behavior feature tensor, generates an optimization strategy parameter set and a behavior defect area identifier, and assists the agent to efficiently play a role in a real scene.

The invention belongs to the technical field of civil engineering technical construction, and particularly relates to a quantitative prediction method for engineering slurry and muck recycling output, which comprises the following steps: S1, synchronizing a construction scene in real time through BIM / GIS and Internet of Things data, and generating a virtual mirror image of a slurry / muck generation process; s2, correcting a theoretical model error according to real-time monitoring data; s3, predicting the mud / muck yield and the resource rate by adopting a time sequence analysis method and combining with a machine learning algorithm, and quantifying uncertainty; s4, dynamically optimizing model parameters through error feedback, and realizing a prediction-monitoring-correction closed loop; through cooperation of the structures, exclusive correction rules are formulated for different construction types, theoretical model errors can be corrected in time according to stratum changes and construction disturbance, and the adaptability of the model under different working conditions and the reliability of prediction results are improved.

The invention discloses a wearable device and a data analysis system for brain surgery postoperative patient rehabilitation monitoring, and relates to the technical field of medical health monitoring, the system comprises a federated learning module, a digital twinning module, a rehabilitation evaluation module, a universe interaction module and a feedback control module, and the federated learning module guarantees data privacy and realizes multi-center model training; the digital twinning module constructs a virtual mirror image of a patient and simulates a rehabilitation scheme effect; the rehabilitation evaluation module quantitatively evaluates the rehabilitation condition; the meta-universe interaction module creates a virtual community and supports brain-controlled interaction training; the feedback control module dynamically adjusts a rehabilitation scheme, the wearable device comprises an ultra-flexible sensing layer, a quantum signal acquisition layer, a nerve regulation and control layer, a data processing layer and a wireless communication module, high-sensitivity data acquisition, transmission and analysis are achieved, the accuracy, personalization and interactivity of brain surgery postoperative rehabilitation monitoring are improved, and the brain surgery postoperative rehabilitation monitoring system is suitable for being popularized and applied. And intelligent development of rehabilitation treatment is promoted.

Systems and methods for generating container images are described. An image tag comprising a set of code names is received at a virtual image server, wherein the virtual image server comprises a mapping of each code name of the set of code names to a corresponding image file. For each of the set of code names, a corresponding image file is retrieved from an image registry and an image manifest is generated by the virtual image server using the corresponding image file of each of the set of code names. The image manifest may reference the corresponding image file of each of the set of code names as a separate image layer. The virtual image server may provide the image manifest to a container host, which may build a container image based on the image manifest.

Provided in the embodiments of the present disclosure are a data processing method and apparatus based on a trusted execution environment, and a device and a storage medium. The method comprises: a host device determining a first metric value on the basis of a first parameter set, wherein the first metric value is used for describing a target virtual machine hosted on the host device; the host device sending the first metric value to a client device by means of a trusted execution environment component; next, the host device receiving, from the client device and by means of the trusted execution environment component, a decryption key for decrypting a first virtual mirror file of the target virtual machine; and on the basis of the decryption key, running the first virtual mirror file, so as to start the target virtual machine. In this way, a user can implement a data processing system based on a trusted execution environment.

The invention provides an archive management model based on digital twinning, and relates to the technical field of archive management. The archive management model based on digital twinning comprises a physical layer, the physical layer is connected with a data layer, the data layer is connected with a digital twinning layer, and the digital twinning layer is connected with an intelligent control layer. According to the technology, an archive management model is constructed by utilizing digital twinning, a virtual mirror image of an entity storehouse is created through a building information model and an internet of things data stream, millimeter-level precision three-dimensional modeling is realized, archive management is more accurate and intuitive, a weight sensor can monitor the weight of the archive in real time, the deviation can be compared during returning, mistakes and omissions are avoided, and the integrity of the archive is guaranteed; the intelligent control layer generates a three-dimensional navigation path, combines a virtual reality terminal, simplifies the archive searching and returning process, reduces manual errors, tracks an administrator and identifies archives in real time through an ultra wide band positioning module and a radio frequency identification reader-writer, optimizes borrowing and returning efficiency, achieves intelligent management of an archive repository, reduces cost and improves efficiency.

The invention discloses a smart city monitoring and simulation deduction method based on a digital twinborn model, and belongs to the field of electric digital data processing.The smart city monitoring and simulation deduction method based on the digital twinborn model comprises the following steps that dynamic data are continuously accessed, static data are obtained at the same time, a digital twinborn body with a timestamp is constructed, and the digital twinborn body is constructed; forming a virtual mirror image of the physical state of the city; on the basis of real-time indexes in a digital twinborn body, hydrological model parameters are corrected in real time, the short-term rainfall prediction precision is improved by fusing an LSTM model, and a twinborn driving model matched with the current reality is generated; compared with the prior art, the method has the advantages that dynamic data and static data of a city are collected in real time, a digital twinborn model for analyzing city drainage is constructed, the ponding risk level can be rapidly evaluated, differentiated emergency plans are automatically generated according to different risk levels, and the method has the advantages of being high in prediction precision and high in response speed.

The invention relates to a cascade reservoir flood control capacity collaborative optimization method and system based on a dynamic game, and belongs to the technical field of hydropower station group flood control regulation and storage. Comprising the following steps: collecting a historical water level sequence, upstream flood discharge flow, drainage basin rainfall confluence data, radar flow measurement data, dam body stress indexes and dynamic correlation parameters of a cascade reservoir group, inputting the collected data into a space-time risk field model, and constructing a space-time risk field; constructing a game model based on the space-time risk field, taking an upstream reservoir as a leader to formulate a reservoir capacity allocation strategy, taking a downstream reservoir as a follower to dynamically adjust a flood discharge scheme according to the leader strategy, and coordinating a flood control target and an economic target through a time-varying game weight; solving the game model by adopting an improved distributed ADMM optimization algorithm to generate a scheduling instruction, and verifying the legality of the scheduling instruction through a block chain smart contract; and pre-executing the scheduling instruction in the digital twin simulation platform, dynamically calibrating the mapping parameters of the physical reservoir and the virtual mirror image through reinforcement learning, generating a final scheduling instruction, and issuing and executing the scheduling instruction.

The invention relates to a method for determining an ophthalmic lens for a wearer and suitable for correcting the wearer's vision, comprising c) determining a virtual lens by an optimization process involving calculating iteratively a surface of the virtual lens so as to match target optical characteristics of a target lens, checking whether peripheral defocus values of the virtual lens satisfy a predetermined criterion, and if the predetermined criterion is not satisfied, reiterating the calculation of the surface of the virtual lens after modifying the target lens of the previous iteration. The determined ophthalmic lens is defined as being the virtual lens at the end of the optimization process. The invention also relates to an ophthalmic lens for a wearer for correcting the wearer's vision and intended to reduce peripheral defocus.

A virtualization-based trusted computing measurement method and apparatus, a device, and a storage medium. The method comprises: determining an application program to be measured; separating target measurement data from the application program, and storing the target measurement data into a virtual image file of a virtual machine, the virtual machine comprising a trusted execution environment; determining the credibility of a target virtual image file loaded to the trusted execution environment; and according to the credibility of the target virtual image file, allowing or forbidding an application program corresponding to the target virtual image file to operate in the trusted execution environment. In the embodiments of the present application, fine-grained trusted computing measurement may be performed on the application program, thereby better providing a service on the basis of the fine-grained measurement result.

Examples described herein provide a method for performing a predictive collision analysis. The method includes initiating, on a processing system, the predictive collision analysis to be performed on the processing system. The further method includes defining a virtual mirror property for a virtual mirror for the predictive collision analysis. The method further includes performing, by the processing system, the predictive collision analysis. Performing the predictive collision analysis includes generating a virtual mirror graphical representation including the virtual mirror based on the virtual mirror property.

The invention relates to the technical field of intelligent exhibition hall control, and discloses an intelligent exhibition hall control system based on the Internet of Things. The system synchronizes the operation state of a physical exhibition hall through a digital twin model, and performs operation situation slicing and feature extraction on a virtual mirror image to obtain a situation feature vector. And constructing an exhibition hall operation situation evolution graph based on historical data, mapping the real-time feature vectors to graph nodes, and performing multi-hop state deduction along the edges, thereby generating a future situation prediction path and identifying potential abnormal nodes. And finally, simulation regulation and control are performed in the digital twinborn model according to a deduction result, and a preventive regulation and control instruction is generated. According to the scheme, a closed loop from real-time state sensing to future evolution prediction and active regulation and control is realized, and the predictability and management and control perspectiveness of the operation risk of the complex exhibition hall are improved.