114 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 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 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 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.

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 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.

An imaging system having multiple imaging devices arranged in succession in the direction of an optical axis, including a first imaging device for generating a real intermediate image of an object on an intermediate image plane, a second imaging device for generating a virtual mirror image of the real intermediate image, the mirror image being laterally offset to the real intermediate image on the intermediate plane, and a third imaging device for imaging the real intermediate image and the virtual mirror image together as a real image on an image receiver surface to be arranged at an axial distance to the intermediate image plane. The imaging system has an optical filtering device for filtering the imaging of the real intermediate image and / or at least one of the virtual mirror images separately from each other. The imaging system includes the image receiver surface and a device for processing a real image captured by the image receiver surface. The processing device uses the image to determine positions in the direction of the optical axis of object region points, which are imaged by at least individual pixels of the pixels of the image.

The invention belongs to the technical field of wind power blade damage early warning, and discloses a wind power blade structure fault damage early warning system which comprises a data sensing module, a damage simulation module, a damage modeling module, a crack tracking module and a risk decision module. The data sensing module is used for constructing a multi-dimensional sensing network covering the overall situation and the local situation of the blade and is responsible for capturing all-dimensional information data of the blade from overall situation response to local slight change; the data sensing module comprises an actual load acquisition unit, a local damage sensing unit and an environment acquisition unit; and the damage simulation module can construct a virtual mirror image completely corresponding to the wind power blade based on the omnibearing information data. The method is not limited to single blade vibration signal spectrum analysis through the global and local multi-dimensional sensing network of the blade, the subsequent early warning accuracy is replaced, and meanwhile, the progressive damage process of the wind power blade in matrix cracking, fiber fracture and interlayer stripping can be accurately simulated.

The invention relates to the technical field of unmanned control, in particular to an algorithm training verification system for unmanned system cluster cooperative control, which is characterized in that a cluster control module generates a cooperative task instruction and distributes the cooperative task instruction to each heterogeneous unmanned module; the heterogeneous unmanned module receives and executes the cooperative task instruction; the model initialization module generates a virtual model based on the initial positions of the plurality of heterogeneous unmanned modules, and generates predicted movement data of the plurality of heterogeneous unmanned units based on the collaborative task instruction; the data synchronization module acquires actual execution data of the plurality of heterogeneous unmanned units, and synchronizes the actual execution data into the virtual mirror image model based on a timestamp to be aligned with the predicted movement data; the feature extraction module extracts training features based on the actual execution data and the predicted movement data, wherein the training features comprise formation retention degree, cluster overall movement consistency and task progress deviation rate; the efficiency evaluation module evaluates the efficiency of the control algorithm based on the training features, can automatically verify the cooperative control algorithm, and improves the working efficiency.

The invention relates to the technical field of Internet of Things, and discloses an intelligent business business travel data acquisition and analysis system based on Internet of Things, which comprises a data acquisition module, a data transmission module, a data processing and analysis module and a service module, through the multi-mode sensor network, the whole scene data acquisition of the business business travel is realized, and the limitation of a traditional single field is broken through; by means of edge computing and NB-IoT hierarchical data transmission, the delay problem of cloud centralized processing is solved, and meanwhile, the credibility of key data is guaranteed by means of block chain evidence storage; and then a digital twin module is combined with an AI algorithm, a dynamic virtual mirror image is constructed, intelligent analysis such as passenger flow prediction and anomaly detection is realized, and the defects of traditional visualization and decision support are made up.

The application discloses an in-game shooting parameter regulation method, an in-game shooting parameter regulation device, a computer readable storage medium, a computer device and a computer program product. The in-game shooting parameter regulation method provides a graphical user interface through a terminal, and the graphical user interface is used for displaying a game picture. The regulation method comprises the following steps: receiving a user instruction, wherein the user instruction is used for instructing to adjust a shooting parameter of the game picture; in response to the user instruction, generating an adjustment scheme of the shooting parameter through a preset parameter adjustment model, wherein the adjustment scheme of the shooting parameter comprises at least one of a virtual lens parameter, a light parameter, an environmental effect parameter and a character action parameter; and adjusting corresponding parameters of the game picture displayed in the graphical user interface according to the adjustment scheme of the shooting parameter, so as to present a picture after parameter adjustment.

The application provides an intelligent process design and verification integrated platform and method for ring forgings, applied to the field of intelligent automatic manufacturing technology. It comprises: a process management layer taking the processing mechanism model of each processing procedure in the process route of ring forging forming as the benchmark, constructing a dynamic mapping model for each processing procedure according to the equipment operation program parameters corresponding to the mechanical equipment used for each processing procedure and the numerical simulation parameters when simulating each processing procedure; a big data analysis layer adopts a station task algorithm to establish data flow correlation rules according to the virtual mirror image of the production line of the process route, then determines the current processing procedure from multiple processing procedures and inputs the actual execution data and real-time related state of the current processing procedure into the target dynamic mapping model of the current processing procedure to obtain the current equipment operation program parameters, then performs numerical simulation on the current processing procedure to generate a numerical simulation prediction result. The full-process design and verification of ring forgings in different processing procedures can be realized.

The application discloses an indoor parking lot vehicle positioning and reverse vehicle searching method based on visual semantic analysis, which comprises the following steps: dividing an image into a real physical surface and a mirror virtual image area, and calculating a ground reflection reference surface; establishing a virtual mirror camera symmetrical to the real main camera based on the reference surface, repairing the mirror virtual image feature to the effective observation of the virtual camera; introducing a symmetrical virtual observation factor in pose optimization, jointly optimizing the re-projection error of the real main camera and the virtual camera, converting the mirror interference into a geometric constraint for enhancing positioning, so as to solve the continuous vehicle pose, significantly improve the positioning accuracy and robustness in the mirror reflection scene such as the indoor parking lot, and realize reliable reverse vehicle searching application.

The invention provides an intelligent process design and verification integrated platform and method for ring forgings, and is applied to the technical field of intelligent automatic manufacturing. Comprising the following steps that: a process management layer constructs a dynamic mapping model of each processing procedure according to equipment operation program parameters corresponding to mechanical equipment used in each processing procedure and numerical simulation parameters during simulation of each processing procedure by taking a processing mechanism model of each processing procedure in a process route for forming the ring forging as a reference; the big data analysis layer establishes a data flow association rule by adopting a station task algorithm according to a production line virtual mirror image of the process route, and then determines a current processing procedure from a plurality of processing procedures and inputs actual execution data and a real-time related state of the current processing procedure into a target dynamic mapping model of the current processing procedure; current equipment operation program parameters are obtained, numerical simulation is carried out on the current machining procedure, and a numerical simulation prediction result is generated. The design and verification of the whole forming process of the ring forge piece in different machining procedures can be achieved.