17 results about "Virtual plant" patented technology

A plant three-dimensional reconstruction method for a weak texture image and scale distortion comprises the following steps: step 1, recovering an initial Gaussian point cloud and camera parameters through an SfM method by using a multi-view RGB image; 2, differential rendering is executed in training iteration, a predicted image is compared with a real image, and a loss function containing various constraints is calculated to serve as a basis for gradient solving and parameter updating; 3, calculating a pixel weighted average gradient and an artifact suppression coefficient of each Gaussian in a visible view angle; 4, updating Gaussian parameters through back propagation, and adaptively triggering Gaussian cloning, splitting or deleting operation based on the pixel gradient, the covariance matrix and transparency; and 5, dynamically adjusting the Gaussian projection matrix according to the focal length and the resolution of the camera during rendering so as to maintain scale consistency, and performing anti-aliasing rendering in combination with pixel-level super-sampling. According to the method, the reconstruction precision and the structure reduction capability of the virtual plant in the weak texture region are remarkably improved.

This invention relates to a virtual inspection and process simulation method and system for rare earth production processes, belonging to the field of digital twin technology. A virtual workshop is established based on the geometric model of the production site, control scripts, and real-time data, simulating the entire process. By establishing the virtual rare earth workshop and creating a data connection between the actual workshop and the virtual factory, data visualization demonstrations of various production processes can be achieved, along with rapid inspection of production equipment. Furthermore, based on the extraction mechanism and historical data, component content is predicted, and automatic early warnings are issued, enabling real-time and accurate prediction of process indicators. Simultaneously, the system can quickly respond to changes in production conditions, providing system early warnings and optimization data, which helps reduce the burden on operators, optimize production process control, improve production management efficiency, and achieve effective utilization of on-site process data.

The invention discloses a plant management and control system based on artificial intelligence and big data, particularly relates to the field of plant management and control, and comprises a plant data acquisition module, a virtual plant construction module, a global coordination optimization module and a control instruction execution module. According to the plant management and control system based on artificial intelligence and big data, path conflicts and resource competition decision conflicts are recognized in advance through a virtual plant model of a virtual plant construction module, a predictive negotiation space is provided for management and control scheme optimization, and the risk of control instruction overlapping in the physical world is effectively avoided; global collaborative decision of multiple edge nodes is realized through a global collaborative optimization module, a control scheme is dynamically adjusted to eliminate conflicts, and instruction overlapping caused by independent operation is avoided; and a virtual model and agent strategy is continuously corrected through feedback data by the control instruction execution module, so that the stability of global coordination is further enhanced, conflict recurrence is avoided, and efficient operation of the system is guaranteed.

This invention provides a real-time bending and shaping method for virtual plants based on adjustable stiffness weights. The method involves configuring virtual plant parameter information and generating a parameterized plant model. The parameter information includes at least plant parameter information, plant control parameter information, and environmental parameter information. When the interactive mode is activated and the plant end is dragged, the end of the plant model is acquired and fixed at the target dragged position. Based on the target dragged position, the dragged virtual plant structure undergoes weighted inverse dynamic bending processing and interpolation. Based on the updated dragged virtual plant structure, other branch structures of the virtual plant are updated synchronously. The overall updated virtual plant structure is subdivided and subjected to Catmull-Rom curve interpolation. The interactive mode is then terminated, and the currently updated virtual plant structure is solidified. This invention uses gradual stiffness, mass curves, and weak bending moment constraints to make the bending shape of the virtual plant highly similar to the stress on real branches.

The invention discloses a virtual plant modeling method and device, electronic equipment, a medium and a product, and is applied to the technical field of digital modeling. The method comprises the steps of obtaining a plant name of a to-be-generated virtual plant in response to a first input operation; determining matched vegetation morphological parameters of the plant name in a preset botanical knowledge base, wherein the vegetation morphological parameters are used for representing three-dimensional morphological characteristics of the virtual plant; determining the value of each vegetation morphological parameter, and performing parameter mapping on each vegetation morphological parameter to generate an initial model file, the initial model file comprising initial model parameters for generating a three-dimensional model of a virtual plant; and generating a three-dimensional model of the virtual plant based on the initial model file. Therefore, the modeling threshold can be reduced, the modeling efficiency of the virtual plant is greatly improved while the modeling reasonability is guaranteed, and the project development progress is effectively improved.

The application relates to the technical field of supply chain management, and discloses a supply chain cooperative management system based on composite material sharing intelligent manufacturing; the system comprises a feature extraction module, which is used for extracting shared manufacturing features; a role analysis module, which is used for dividing supply roles into primary roles and secondary roles; a virtual factory module, which is used for generating a virtual factory with a shared path; and a shared upgrading module, which is used for updating and upgrading the shared path; the application can convert actual physical layer shared manufacturing into one-time all-around virtual simulation, thereby being capable of discovering and avoiding adverse reactions and supply defects existing in capacity connection, efficiency matching, visual cooperation and the like of different types of suppliers in advance, realizing level crossing of supply chain cooperation from static matching to dynamic optimization and simulation verification, and reducing the error probability of supply chain cooperation during composite material sharing intelligent manufacturing.

Disclosed are a device and a method for providing metaverse-based farm operation content. According to an embodiment of the present application, the method for providing metaverse-based farm operation content may comprise the steps of: (a) by using spatial information of an offline farm and plant information of a real plant cultivable in the offline farm, generating metaverse-based farm operation content that enables cultivation of a virtual plant corresponding to the real plant in a virtual farm virtually simulated to correspond to the offline farm; (b) receiving a user input associated with the farm operation content from a user terminal; and (c) reflecting, in the farm operation content, at least one of an environmental factor constituting the virtual farm and a growth factor of the virtual plant, both of which change according to the user input, and outputting the farm operation content through the user terminal.

This invention provides an energy management system that can optimally control actual plant equipment using an operation plan formulated by an operation plan formulation device. [Solution] According to one embodiment, the energy management system comprises an actual plant facility, a plant simulator that simulates the operation of the actual plant facility, an operation plan formulation device that formulates an operation plan for the actual plant facility, a virtual plant control system that controls the plant simulator based on the operation plan, and an actual plant control system that controls the actual plant facility based on the operation plan. The virtual plant control system acquires the operation plan via a communication path connecting the operation plan formulation device and the virtual plant control system. The actual plant control system acquires the operation plan via a communication path connecting the operation plan formulation device and the actual plant control system.

The technical idea of the present invention provides a learning system for manufacturing a secondary battery, comprising: a simulation device constructing a virtual factory in which a plurality of manufacturing facilities configured to perform a secondary battery manufacturing process are disposed, and outputting the virtual factory to a display device; and an input device configured to transmit, to the simulation device, a user input signal generated on the basis of a user input. The simulation device is configured to change the position of the virtual factory displayed on the display device according to the user input signal, and to output, to the display device, content associated with a manufacturing facility selected by the user input signal from among the plurality of manufacturing facilities.

The technical idea of the present invention provides a secondary battery manufacturing learning system including a simulation device configured to construct a virtual factory in which a plurality of manufacturing apparatuses configured to perform a secondary battery manufacturing process are provided and output the virtual factory to a display device, and an input device configured to transmit a user input signal generated based on a user's input to the simulation device. The simulation device is configured to change a position of the virtual factory displayed on the display device according to the user input signal, and output content associated with a manufacturing apparatus selected from the plurality of manufacturing apparatuses by the user input signal to the display device.

The invention provides a virtual plant real-time bending shaping method based on an adjustable rigidity weight, parameter information of a virtual plant is configured, a parameterized plant model is generated, and the parameter information at least comprises plant parameter information, plant control parameter information and environment parameter information; when the interaction mode is activated and the tail end of the plant is dragged, obtaining and fixing the tail end of the plant model at a dragging target position; according to the dragged target position, weighted inverse dynamic bending processing and interpolation processing are carried out on the dragged virtual plant structure; according to the updated dragged virtual plant structure, synchronously updating other branch structures of the virtual plant; subdivision and Catmull-Rom curve interpolation processing are carried out on the virtual plant structure after the overall updating is carried out on the virtual plant structure; and ending the interaction mode and carrying out solidification operation on the currently updated virtual plant structure. According to the method, the bending form of the virtual plant is highly attached to the stress of a real branch through gradual rigidity, a mass curve, weak bending moment constraint and the like.

The invention relates to the technical field of virtual reality, in particular to a digital twin system construction method, system and device. The method comprises the following steps: dividing each piece of real equipment in a real factory according to a preset dimension to obtain a plurality of real equipment bodies, and constructing a virtual factory model based on the plurality of real equipment bodies; constructing a virtual-real mapping action of a virtual device body corresponding to each real device body in the virtual factory model; collecting production data of a real factory in real time; the equipment state information and each virtual-real mapping action in the production data are used for controlling each virtual equipment body to synchronize the action of the corresponding real equipment body in real time; and constructing a visual billboard and displaying statistical data obtained based on production data statistics through the visual billboard. The factory data is synchronized in real time from multiple aspects and multiple sources, and the production management efficiency can be improved.

1. Name of the product in this design: Graphical User Interface for a Smart Virtual Plant Factory for Electronic Devices. 2. Application of this design: The graphical user interface of this design is applied to an electronic device. 3. The key design features of this product are the combination of shape and pattern. 4. The image or photograph that best illustrates the design's key points: the front view. 5. Purpose of the graphical user interface: This graphical user interface is used for interactive teaching and planting training in agricultural virtual simulation of smart virtual plant factories. 6. Description of the changing states of the graphical user interface: The main view is the "Smart Virtual Plant Factory" main interface. After logging in, you will see screen transition diagram 1, which is the factory creation interface. Click the "Create" button in screen transition diagram 1 to create a factory, then see screen transition diagram 2, which shows the successfully created factory interface. Click the created "factory icon" in screen transition diagram 2 to see screen transition diagram 3, where you can view the current factory planting tasks. Click the "Start Training" button for planting plan task number 1 in the list in screen transition diagram 3 to see screen transition diagram 4, the planting plan task interface. Complete the planting plan task in screen transition diagram 4 and click the "OK" button. The system will then display screen transition diagram 5, the current task results interface. Click the "OK" button in screen transition diagram 5 to see screen transition diagram 6. Click "Continue Task" in screen transition diagram 6 to see screen transition diagram 7, which displays the basic information for the next task. Click the "OK" button in screen transition diagram 7 to see screen transition diagram 8, the theoretical test interface. After completing the theoretical test in screen transition diagram 8, click the "OK" button to see screen transition diagram 9. The task training interface; in interface change state diagram 9, click the "Environmental Control Management" button at the bottom to enter the environmental control system interface in interface change state diagram 10, which is the training operation interface; click "Lighting System" at the top of interface change state diagram 10 to enter interface change state diagram 11, which is the training operation interface; click "Nutrient Solution Configuration" at the top of interface change state diagram 11 to enter interface change state diagram 12, which is the training operation interface; after completing the nutrient solution settings in interface change state diagram 12, click the "Save" button to enter the material list interface in interface change state diagram 13, where you can view the relevant information for this nutrient solution replenishment; click the "OK" button in the material list in interface change state diagram 13 to enter the factory roaming interface in interface change state diagram 14, where you can browse the 3D virtual scene and perform training operations; after completing the 3D virtual scene browsing and training operations in the factory roaming scene in interface change state diagram 14, you will enter the sales interface in interface change state diagram 15; click on interface change state diagram 15... Click "Confirm Sale" to proceed to the interface change state diagram 16 after the sale is completed, where you can view the current factory operation statistics and training results; click the "×" close button in the interface change state diagram 16 to proceed to the interface change state diagram 17; click "End Training" at the bottom of the interface change state diagram 17 to complete the lettuce planting training.

This application provides a scheduling method, device, and readable storage medium for flexible production lines. The electronic device constructs a virtual factory environment for the target production line. Based on the real-time status of each dimension belonging to a first set of multiple dimensions of the target production line, it determines the production sequence of each product in the target order. Then, based on the production sequence and the real-time status of each dimension belonging to a second set of multiple dimensions of the target production line, it allocates workstations to each process of each product in the production sequence to obtain a workstation allocation scheme. Finally, the electronic device schedules the target production line according to the production sequence and the workstation allocation scheme to complete the target order. This scheme balances multiple scheduling objectives at the order level by determining the production sequence of each product in the target order, and coordinates and balances multiple scheduling objectives at the workstation level by allocating workstations to each process of each product in the production sequence. This adapts to multi-objective optimization while improving production efficiency.

The invention relates to the field of intelligent manufacturing and industrial internet, and discloses a virtual factory application method based on DNC and digital twinning, which comprises the following steps: step 1, determining workshop field networking equipment and machine tools; 2, performing field measurement on a workshop and equipment; 3, carrying out the precise modeling of a workshop and equipment through 3DMAX; 4, performing triangular surface and structure optimization on the model; step 5, carrying out effect rendering in the Unity 3D engine; step 6, integrating the data of the networked equipment by using the DNC system to form a database table; step 7, developing a function of reading DNC and MES data in real time at a Unity end through C #, determining a data representation form of a data bearing interface, and making a billboard and a data analysis icon; 8, manufacturing a UI interaction layer; and ninthly, workshop field application is achieved. According to the method, a comprehensive and intelligent solution is provided for workshop production management, and the competitiveness and production benefits of enterprises can be improved.

This invention discloses a method for quantifying three-dimensional plant architecture and evaluating light interception capacity in multi-genotype plants. The method includes the following steps: Step 1, multi-view image acquisition; Step 2, high-fidelity three-dimensional plant structure reconstruction; Step 3, three-dimensional phenotypic parameter extraction; Step 4, plant architecture classification based on unsupervised learning; Step 5, virtual plant population construction; Step 6, calculation of light interception for different plant architectures based on a radiative transfer model. This invention achieves quantitative acquisition and comparability of plant architecture structural parameters by constructing a high-fidelity three-dimensional plant structure model. Based on this, it completes automatic plant architecture classification and further simulates and evaluates the light interception process based on real plant architecture parameters, thus forming an integrated evaluation system of plant architecture and light energy utilization supported by three-dimensional structure. This system can be used for plant architecture phenotypic analysis, resource utilization efficiency evaluation, and breeding screening.

The invention discloses an industrial element universe SAAS system based on digital twinning, and the system comprises the steps: S1, constructing a three-dimensional digital model of industrial equipment, and forming an industrial equipment model library; s2, building a virtual simulation production line environment, and placing the industrial equipment and the monitoring equipment model in a virtual factory; s3, setting a virtual monitoring point location, and binding the virtual monitoring point location with a data acquisition point location of an actual factory to realize real-time data synchronization; s4, generating a digital twin factory monitoring page, and displaying production data and an equipment state; s5, processing sensor data through heterogeneous data fusion and a multi-dimensional behavior analysis mechanism, and analyzing an equipment behavior mode; s6, dynamically adjusting a resource scheduling strategy by adopting a dynamic adaptive resource scheduling and multi-agent collaborative optimization mechanism; s7, performing fault simulation and emergency drilling, and simulating a production fault scene; s8, remotely controlling factory equipment; and S9, providing a multi-user management and public service function. According to the invention, the management efficiency and the intelligent level of the industrial element universe platform are effectively improved.