58 results about "Cloud simulation" patented technology

The invention discloses a visual arrangement system and method for urban rail cloud simulation test resources, and aims to assist a user to conveniently and efficiently arrange a simulation test service scene, convert the service scene into a template, namely a reusable service scene architecture script, and enable a scheduling engine to schedule the simulation test service scene according to template data information. The method comprises the following steps: respectively docking with an on-cloud platform, an under-cloud system and a simulation interface, establishing a simulation test scene instance of a service system from the on-cloud to the under-cloud, and enabling a user to carry out the simulation test work of the service system on the scene instance. According to the method, a certain resource can be selected as a template to be stored, when needed in the follow-up simulation test process, a template file is flexibly called, the environment is pulled up and deployed through a scheduling engine, the problem that the resources of the test environment are limited is solved, and the convenience and efficiency of cloud simulation environment scene construction are improved.

The invention discloses an expressway traffic flow induction method and system based on an unmanned aerial vehicle. The system comprises a data acquisition and processing subsystem, a cloud traffic flow simulation subsystem and an induction subsystem. According to the method, control areas are divided for frequently-congested road sections (ramps and service areas) and upstream areas of the expressway, data acquisition is carried out, cloud simulation models of the corresponding control areas are constructed, and meanwhile, real-time updating of the models is carried out according to a certain time window; after the system recognizes congestion, a speed limiting strategy is calculated through the cloud model, the speed limiting strategy is sent to the airport, the unmanned aerial vehicle departs from the designated airport, arrives at the designated position of the road section and carries out speed limiting prompting to carry out traffic flow induction, the effect of relieving the traffic condition of the congested road section is achieved, and meanwhile the system can be used for accidental accident prompting.

The invention discloses a map generation method, electronic equipment and a robot, and relates to the technical field of artificial intelligence. The method comprises the steps of generating a structured prior map representing an environmental space occupation state according to environmental geometric shape design data of a target physical task space; determining a simulation path of the intelligent mobile device moving in the passage area of the structured prior map, and performing simulation scanning operation on the virtual physical model of the target physical task space along the simulation path to obtain laser point cloud simulation data and motion state simulation data; and generating a navigation map based on a pose map according to the laser point cloud simulation data and the motion state simulation data. According to the method and the device, the problems of high dependence on manpower, time consumption and uncertain generation results during map generation in the prior art can be solved, the map with high accuracy can be efficiently and automatically generated at low cost, and the task execution efficiency and the task execution precision of the intelligent mobile equipment are improved.

The invention discloses an automatic control system and method in the oil and gas field exploitation and production process based on artificial intelligence, relates to the technical field of oil and gas field exploitation and production, and discloses the automatic control system in the oil and gas field exploitation and production process based on artificial intelligence. Comprising a data acquisition module, an equipment control module and a cloud edge collaboration module, initial data are acquired in real time through the data acquisition module, and high-quality data input is generated through preprocessing of edge computing nodes. The equipment control module generates a preliminary equipment control instruction based on the data, and the cloud side cooperation module further utilizes a digital twin model and a cloud simulation platform to simulate the execution effect of the equipment control instruction and optimize the execution effect, so that a multi-level and multi-dimensional control strategy is formed, the operation efficiency and stability of the equipment are improved, and the equipment control efficiency is improved. And the energy consumption and the equipment loss are obviously reduced, so that the equipment control effect in the oil and gas field exploitation and production process is improved.

The invention discloses a channel dynamic cloud detection method and system based on a meteorological satellite hyperspectral infrared detector, and the method firstly proposes nonlinear channel optimal selection based on Gaussian mixture model probability approximation quantization relative entropy, and can reduce the error distribution of temperature and humidity. Secondly, based on layer-by-layer cloud simulation and clear sky brightness temperature simulation, a cloud profile inversion method of a weighted L1 norm constraint inverse problem of Gaussian disturbance + numerical approximation signal degree-of-freedom optimization channel weight is provided, cloud amount information of multiple layers from bottom to top is obtained, and the actual condition of actual cloud vertical distribution is met. And finally, a cloud detection result is obtained by customizing each channel of each field point by adopting an adaptive dynamic cloud detection method, which is beneficial for reasonably using the brightness temperature data of the hyperspectral infrared channel and realizing the application of partial cloud region data, so that the data quantity of the brightness temperature of the variational assimilation channel is increased, and the precision of numerical weather forecast is further improved.

The invention discloses a cloud simulation training system suitable for integration of a master station and a transformer substation of a centralized control system. The cloud simulation training system comprises a monitoring service simulation unit, a power transformation operation and maintenance simulation unit and an automatic operation and maintenance training unit. The monitoring service simulation unit is used for realizing regional power grid operation mode adjustment, fault point setting and training teaching plan making based on a graph-analog-digital integrated simulation technology and a containerized scene creation technology; the power transformation operation and maintenance simulation unit is used for simulating primary equipment, secondary equipment and a monitoring system based on a virtual reality 3D technology, a graphical modeling technology and a load flow calculation technology; the automatic operation and maintenance training unit is used for extracting data of a typical transformer substation from an actual production operation system and truly simulating an automatic operation and maintenance scene of regional power transformation equipment; the working quality and efficiency of simulation training are improved.

The embodiment of the invention provides an automatic driving cloud simulation platform test method and device, and the method comprises the steps: obtaining multi-source data of an automatic driving cloud simulation platform, carrying out the classification and structural extraction of the multi-source data, obtaining corresponding knowledge fragments, and storing the knowledge fragments into a knowledge source database, according to the types of the knowledge fragments, vectorizing the knowledge fragments by adopting different language models to obtain a document vector set, a code vector set and a scene parameter vector set; receiving and vectorizing a test demand described by a natural language, performing vector retrieval in the document vector set and the scene parameter vector set according to a retrieval enhancement generation algorithm, and inputting a retrieval result into the artificial intelligence model to understand the scene demand of the test, so as to obtain test case logic output by the model, the test code template is retrieved in the code vector set according to the test case logic, the input parameters are injected into the test code template to obtain the test code for testing, and the efficiency and accuracy of automatic driving cloud simulation platform testing can be improved.

The invention discloses a spiral groove milling curved surface point cloud simulation calculation method based on intersection points, and the method specifically comprises the steps: firstly, constructing a tool general parameterized model; then, a cutter milling kinematics model is constructed and used for guiding the milling process, and the milling mode of the spiral groove is achieved; secondly, solving a spiral groove milling curved surface point cloud model based on an envelope principle; and finally, carrying out reconstruction calculation on the point cloud model through point cloud intersection point calculation and a point cloud selection principle, and carrying out comparison verification on the calculated spiral groove milling curved surface point cloud simulation model and a model after importing a cutter milling track and a geometric shape into Veicut to carry out spiral groove curved surface simulation. According to the method, high-precision visual display is carried out on spiral groove milling curved surface point cloud simulation, and correctness and effectiveness of related theories of the method are proved.

This application provides a testing method and apparatus for an autonomous driving cloud simulation platform. The method includes: acquiring multi-source data from the autonomous driving cloud simulation platform; classifying and structurally extracting the multi-source data to obtain corresponding knowledge fragments and storing them in a knowledge source database; vectorizing the knowledge fragments according to their types using different language models to obtain document vector sets, code vector sets, and scene parameter vector sets; receiving test requirements described in natural language and quantizing them; performing vector retrieval in the document vector set and scene parameter vector set using a retrieval enhancement generation algorithm; inputting the retrieval results into an artificial intelligence model to understand the test scenario requirements; obtaining test case logic output by the model; retrieving test code templates from the code vector set based on the test case logic; and injecting input parameters into the test code templates to obtain test code for testing. This application can improve the efficiency and accuracy of testing autonomous driving cloud simulation platforms.

This invention discloses a remote sensing cloud simulation method and apparatus based on a classification-guided diffusion model, belonging to the field of remote sensing image cloud and fog simulation. The method includes: acquiring and preprocessing multi-temporal remote sensing images to construct a dataset containing registered pairs of cloudless and cloudy images; pre-training a feature extraction network based on cloud mask data and performing unsupervised clustering using the cloud features extracted by the network to achieve automated cloud classification; training a pre-constructed cloud simulation diffusion model using the cloudless image and cloud classification results as input, and the corresponding cloudy image as the ground truth supervision signal, to learn the mapping relationship from cloudless to cloudy states; and inputting the target cloudless image and a specified cloud category into the trained cloud simulation diffusion model to generate a simulated cloud-containing remote sensing image. This invention effectively improves the realism of generated clouds and fog, the naturalness of integration with ground features, and the controllability of generating specific cloud categories, providing sufficient and realistic training samples for cloud-related data-driven models.

The invention provides a data processing method and device, equipment, a storage medium and a program product, and relates to application of a simulation data processing technology in the field of vehicles. The method comprises the following steps: acquiring driving data acquired by a vehicle; processing the driving data in a cloud simulation environment matched with the vehicle to obtain sensing result data; the cloud simulation environment matched with the vehicle is configured to be a simulation environment simulating an actual scene of a vehicle end; and outputting the sensing result data according to a structured format to be used as training data of an auxiliary driving model. According to the method, the cloud simulation environment equivalent to the actual scene of the vehicle end can be constructed, and the driving data acquired by the vehicle can be stably and reliably processed by utilizing the sufficient computing power of the cloud end, so that the complete, consistent and traceable high-quality sensing data can be obtained. The sensing result can be output according to a preset format to be used for assisting training of the driving model, more accurate and richer learning signals are provided for the model, and the processing capacity of the model on a real driving scene is effectively improved.

The invention provides a simulation application generation method and device, electronic equipment and a storage medium, and the method comprises the steps: generating a corresponding function module based on a sub-assembly selected for a cloud simulation modeling platform for a pre-constructed starting instruction of the cloud simulation modeling platform, and displaying the function module through a canvas of the cloud simulation modeling platform; and if it is determined that the functional module can be subjected to simulation modeling, performing simulation modeling on the functional module to obtain a simulation application so as to subsequently simulate data input by a user based on the simulation application. In the embodiment of the invention, a GCAir platform does not need to be installed locally, and the pre-constructed cloud simulation modeling platform is started on the webpage through the starting instruction; and the user is allowed to completely customize or directly select the sub-components to generate the corresponding function modules, so that the simulation application of the user can be completely and freely combined and built subsequently, and the use experience of the user is improved.

1. The name of the design product: cloud simulation detection system information management display screen panel. 2. The use of the design product: the interface can be used on electronic devices such as physical carrier mobile phones, notebook computers, desktop computers, tablet computers, etc., for cloud simulation scene arrangement and monitoring related information display. 3. The design points of the design product: the graphical user interface in the screen. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: clicking the "deploy" button in the upper right corner of the main view interface can enter interface change figure 1, which is used as a simulation scene management interface; clicking the task icon in the middle of interface change figure 1 enters interface change figure 2, which is used as a simulation scene monitoring interface.

The invention discloses a mechanical, electrical and pipeline scene deep learning reconstruction method and system based on synthetic point cloud enhancement, and aims to solve the problem that a current deep learning model depends on a large amount of real marked point cloud data. According to the method, the synthetic point cloud is generated from the building information model BIM, and the real laser scanning process is simulated, so that the point cloud data capable of reflecting the shielding characteristics of the real scene is generated. Specifically, the method comprises the following steps: firstly, initializing the position, scanning resolution, scanning error and passable area of a laser scanner, and then sampling a BIM model by using a laser ray intersection algorithm to generate a synthetic point cloud; and then, improving semantic segmentation accuracy of an MEP scene by training a deep learning model, thereby realizing high-precision MEP model reconstruction. Operation and maintenance of mechanical, electrical and pipeline components in buildings can be effectively promoted, and the working efficiency and quality in related fields are improved.

The invention relates to the technical field of simulation deduction, in particular to a cloud simulation deduction platform and method, and the platform comprises a core simulation engine sub-platform which is used for carrying out the online detection of a simulation node based on MQTT, and controlling a simulator plug-in to carry out the frame data updating based on a step length; the matched tool chain sub-platform is used for obtaining a standard digital prototype according to a model embedding framework and managing digital prototype information and mirror image files based on model management and mirror image management, and the platform control subsystem is used for receiving detection information sent by the core simulation engine sub-platform, so that an engine is hooked with the standard digital prototype meeting a preset rule and is used for performing simulation on the standard digital prototype. Carrying out simulation deduction by adopting a platform simulation deduction mode, a multi-platform joint simulation deduction mode or a multi-platform parallel simulation deduction mode; the blue army model system sub-platform is used for carrying out blue army model system management based on equipment categories, and carrying out command and control model configuration management and tactical rule setting. According to the invention, the transmission efficiency and accuracy can be improved, and the deduction delay can be reduced.

The present application discloses an automatic control system and method for oil and gas field exploitation and production based on artificial intelligence, which relates to the technical field of oil and gas field exploitation and production. The disclosed automatic control system for oil and gas field exploitation and production based on artificial intelligence includes a data acquisition module, an equipment control module, and a cloud-edge collaboration module. The data acquisition module acquires initial data in real time, and generates high-quality data input after preprocessing by the edge computing node. The equipment control module generates preliminary equipment control instructions based on these data, and the cloud-edge collaboration module further utilizes the digital twin model and the cloud simulation platform to simulate the execution effect of the equipment control instructions and optimize them, thereby forming a multi-level and multi-dimensional control strategy, which not only improves the operating efficiency and stability of the equipment, but also significantly reduces energy consumption and equipment loss, thereby improving the equipment control effect in the oil and gas field exploitation and production process.

The invention discloses a remote sensing image thin cloud removal method based on self-supervised domain adaptation, and belongs to the technical field of remote sensing image thin cloud removal, and the method comprises the steps: inputting a remote sensing image to be subjected to thin cloud removal into a trained remote sensing image thin cloud removal model based on domain adaptation, and obtaining a remote sensing image subjected to thin cloud removal, according to the remote sensing image thin cloud removal model, a simulation data set serving as a source domain is obtained through a thin cloud simulation model giving consideration to cloud distortion and a spatial form, and on the basis, the problem that precision is reduced when a cloud removal model is applied to a real thin cloud image due to the fact that data distribution of a simulation thin cloud image and data distribution of the real thin cloud image are inconsistent is solved. The invention provides a remote sensing image thin cloud removal model based on domain self-adaption, and the thin cloud removal model belongs to a domain self-adaption method based on self-supervised learning, so that the generalization ability of the model is enhanced, and a good cloud removal effect can be achieved under the condition that no target domain label or few target domain labels are used.

The present application relates to cloud computing and clean room equipment operation and maintenance management technical field, specifically to clean room equipment operation and maintenance system based on cloud computing;Contain data access, cloud simulation processing and terminal execution module;The system constructs management benchmark model through collecting business plan and operation and maintenance rule data;Its core is to combine resource account to generate theoretical damaged data through abnormal disturbance simulation, and calculate the dynamic time warping similarity and time series cross-correlation value of actual and theoretical residual vector to generate state decision result;When outputting state decision, the system will issue corresponding operation and maintenance instruction work order, and dynamically correct the disturbance operator weight;The present application realizes the change from single judgment depending on fixed threshold to accurate distinction between normal load deviation and abnormal equipment degradation, which can reduce the false positive rate of unnecessary room inspection and the false negative rate of equipment out of control.

This invention discloses a nuclear power industry mechanism model platform architecture for integration with an industrial internet platform, comprising a runtime environment layer, a service layer, an interface layer, a view layer, and an application layer. The runtime environment layer abstracts the hardware, provides the necessary library files for the upper-layer environment, and handles inter-cluster scheduling and communication. The service layer includes AI models, real-time computing models, cloud simulation models, industrial cloud software models, auxiliary analysis tools, and integrated development and execution tools. The interface layer standardizes and uniformly manages the interfaces of the service layer. The view layer includes mechanism model library interfaces, an operation management module, a data management module, and an engineering management module. The application layer includes artificial intelligence application scenarios, real-time computing scenarios, cloud simulation scenarios, and cloud-based industrial software scenarios. This invention provides an integrated development and execution environment for nuclear power industry mechanism models.

The present application provides a cloud real-time simulation calculation method, system, device, and storage medium. The method includes: the front end receives a design scheme update instruction input by a user, generates change data based on the design scheme update instruction, and sends the change data to the cloud simulation service; the cloud simulation service performs incremental data change on the simulation scenario data in the memory based on the change data to obtain the changed simulation scenario data; performs simulation calculation on the changed simulation scenario data to obtain a simulation result, and saves the changed simulation scenario data in the memory; the cloud simulation service sends the simulation result to the front end. According to the solution of the present application, real-time high-precision simulation can be achieved, thereby improving the simulation experience of users.

The invention discloses a report management system, method, equipment and medium for virtual device cloud simulation, and the system comprises a storage server which is configured to store report content; a database configured to store report records; the report container is configured to query and modify the report record in the database, access the report content of the storage server according to the report record, and display and modify the report content; the virtual tester container is configured to manage starting, running and ending of the virtual device container and read reports in the virtual device container; the server is further configured to store the report content to the storage server and add or modify accessible report records in the database; and the virtual device container is configured to read the numerical value in the virtual tester container, simulate actual device operation and record an operation report. The technical framework of the container cloud platform can be met, the virtual device test report can be stored, checked and shared, and the simulation test efficiency and the user experience can be effectively improved.

The invention belongs to the field of artificial intelligence, computer vision and computer graphics, and discloses a VR real-time rendering method and system for low-bit-rate cloud rendering plug flow, and the method comprises the steps: obtaining a rendering frame image; a lightweight super-resolution model is constructed; inputting the rendered frame image into the lightweight super-resolution model to obtain a reconstructed 4K-resolution image; and performing real-time rendering and display on the VR equipment based on the reconstructed 4K-resolution image. According to the invention, high bandwidth pressure caused by direct transmission of the 4K video is avoided, and the hardware limitation that low configuration equipment cannot carry out complex rendering tasks is overcome. Through the combination of a scene customization model and video coding, high-quality and low-delay visual experience under limited resources is realized, and the method is suitable for various application scenes with relatively high requirements on image quality and real-time performance, such as large-scale cloud simulation, VR tourism and intelligent power grid monitoring.

The application discloses an intelligent control method and system of an electromagnetic oven based on an industrial cloud platform, and relates to the technical field of the industrial cloud platform. In the industrial cloud platform, a high-dimensional state tensor is input into a digital twin model, and an information neural network is combined to perform evolution deduction on an electromagnetic energy conversion process and a heat flow transfer field, and corresponding inversion results are output. The digital twin model and the industrial cloud platform are further controlled, and the accuracy of the inversion results is improved. The industrial cloud platform retrieves a matched cooking process baseline in a cloud knowledge base according to a refined working condition label; the cooking process baseline is taken as a constraint condition, and corresponding multi-target reward content is determined in combination with real-time working data of the electromagnetic oven; rolling time domain optimization is performed in a cloud simulation environment, so that corresponding adaptive control instruction sets are generated; and intelligent control events of the electromagnetic oven are further determined in combination with a current working sequence of the electromagnetic oven, so that the accuracy of the intelligent control events of the electromagnetic oven is improved.

The embodiment of the invention discloses a safety performance cloud simulation method and device of a building structure, equipment and a medium. The method comprises the steps that the method is applied to a cloud management platform, structural security analysis basic data uploaded by a user is received, and the structural security analysis basic data comprises building body model data, structural analysis category data and geographic data; utilizing the building body model data, the structure analysis category data and the geographic data to carry out target type structure safety performance analysis on a building body corresponding to the building body model data to obtain an analysis result; and after the analysis result is uploaded to the cloud, the user can browse the analysis result of the building interactively at the cloud and screen concerned key information, so that the structural safety is effectively judged. Through cloud computing, the process of structure safety performance analysis is completed at the cloud, and safety performance simulation analysis of the building structure can be realized without configuring high hardware and more resources locally.

This application discloses a map generation method, electronic device, and robot, relating to the field of artificial intelligence technology. The method includes: generating a structured prior map representing the occupancy state of the environmental space based on environmental geometry design data of the target physical task space; determining a simulated path for the intelligent mobile device to move within the traversable area of ​​the structured prior map, and performing a simulated scanning operation on a virtual physical model of the target physical task space along the simulated path to obtain laser point cloud simulation data and motion state simulation data; and generating a pose-based navigation map based on the laser point cloud simulation data and motion state simulation data. This application can solve the problems of related technologies in map generation, which are highly dependent on manual labor, time-consuming, and produce uncertain results. It can efficiently, cost-effectively, and automatically generate highly accurate maps, improving the task execution efficiency and accuracy of intelligent mobile devices.

The application relates to a kind of super-high-speed collision space debris cloud simulation calculation method and device in aerospace technology field, the method comprises the following steps: establishing the three-dimensional geometric model of projectile and target plate, the model is meshed, each grid corresponds one SPH particle, reads initial parameter and assigns to the SPH particle, searches the particle adjacent to the SPH particle and the particle adjacent to the SDPH particle, calculates the update parameter of the SPH particle and the update parameter of the SDPH particle based on the search result, judges whether SPH particle is converted into SDPH particle or not;If not, the update parameter of SPH particle is used to update SPH particle parameter;If yes, the update parameter of the SDPH particle obtained by using the update parameter calculation method of SDPH particle is used to update the SDPH particle parameter, after the end of the above loop calculation, the debris cloud shape distribution and scale distribution can be visualized and displayed.The application reduces the amount of calculation, and has better accuracy.

Systems and methods are provided for implementing virtual cloud simulation within a public cloud network. In examples, a domain name system ("DNS") server in a virtual cloud network receives, from a service under test that is running within the virtual cloud network, a request to access a resource, the request including non-routable cloud configurations for the resource. A central configuration repository in the virtual cloud network maps the non-routable cloud configurations for the resource that are identified in the request from the service under test to public cloud configurations of the resource. A reverse proxy server in the virtual cloud network directs the request to a public cloud instance of the resource that is running in another portion of the public cloud network, directs return data traffic from the public cloud instance of the resource back to the service under test in the virtual cloud network.

The invention discloses a nuclear power industrial mechanism model platform architecture for industrial internet platform integration. The nuclear power industrial mechanism model platform architecture comprises an operation environment layer, a service layer, an interface layer, a view layer and an application layer, the operation environment layer is used for abstracting hardware, providing library files required by operation for an upper-layer environment and carrying out scheduling and communication among clusters, and the service layer comprises an AI model, a real-time calculation model, a cloud simulation model, an industrial cloud software model, an auxiliary analysis tool and an integrated development operation tool; the interface layer carries out standard packaging and unified management on interfaces of the service layer, the view layer comprises a mechanism model library interface, an operation management module, a data management module and an engineering management module, and the application layer comprises an artificial intelligence application scene, a real-time calculation scene, a cloud simulation scene and a cloud industrial software scene. According to the invention, an integrated development operation environment is provided for a nuclear power industrial mechanism model.

This invention discloses a radar echo simulation method based on layered chaff cloud simulation, constructing the chaff cloud as a layered mathematical model segmented according to vertical height. The relationship between the shape parameters of the chaff layers and the chaff scattering coefficient is studied, solving the problems of excessive chaff unit numbers and slow computation speed caused by traditional ellipsoidal modeling based on small cube equivalents. First, the chaff cloud is divided into chaff units at different heights according to its density; second, the relationship between the shape of the chaff unit and the radar scattering coefficient is considered; finally, the echo signal generated by the motion law corresponding to the chaff unit is modeled, and the signals of the overall chaff units are superimposed to obtain the final echo. This invention only requires estimating the shape and size of the chaff cloud, thus achieving fast and accurate simulation of radar echoes from chaff clouds.

The present application relates to the field of AI. The present application specifically relates to a point cloud simulation model training method and a related device. The method comprises: acquiring a plurality of pieces of first point cloud data at a plurality of different positions in a target scene; on the basis of the plurality of pieces of first point cloud data, constructing an initial point cloud simulation model, and determining a plurality of pieces of pose information of a target object, parameters of the initial point cloud simulation model comprising the reflection intensity and loss rate of a Gaussian sphere corresponding to a point in a point cloud, and the target object is an object in the plurality of pieces of first point cloud data; on the basis of camera intrinsic parameters, respectively converting the plurality of pieces of first point cloud data into a plurality of first depth maps; and training the initial point cloud simulation model on the basis of the plurality of pieces of pose information and the plurality of first depth maps, so as to obtain a target point cloud simulation model. Real-time rendering of point clouds can be achieved, and rendering precision of point clouds can be improved.