583 results about "Product model" patented technology

The invention relates to the technical field of mold machining optimization, and discloses a mold machining optimization method, system and device and a storage medium. The method comprises the steps that design parameters of a mold are obtained and input into simulation software, and a mold product model is generated; performing parameter optimization through mold flow analysis to obtain optimized design parameters; actual production parameters are calculated according to the optimized parameter values, and key parameter values in the production process are recorded; and finally exporting and displaying an optimization result, and determining an optimal design value. The method has the following effects that through simulation analysis and multiple iterative optimization, the efficiency of mold design and the injection molding process is effectively improved, the precision and quality of product forming are ensured, and intelligent monitoring and optimized display of the production process are achieved.

The invention discloses an equipment control system and method for OPS computer mainboard production, and relates to the technical field of equipment control, and the method comprises the steps: collecting technological parameters, and constructing a topological vector space; key information in the line changing process is recorded and stored in the context memory network; when a new OPS mainboard production order is received, identifying a product model in the order, and performing similarity retrieval in the topological vector space and the context memory network; taking the parameters retrieved by the topological space as basic parameters, taking the adjustment strategy extracted from the context memory network as increment, and generating initial process parameter setting; small-batch trial production is carried out, and an actual production result is compared with an expected result; and utilizing a reinforcement learning algorithm to generate optimization parameters. According to the method, through collaborative retrieval of the topological vector space and the context memory network, the optimal process parameters are rapidly obtained, the line changing debugging time is shortened, and more accurate control is completed.

The invention discloses a product model detection method and system based on welding spots. The method comprises the steps that a welding spot identification mark is obtained, a welding spot file matched with the welding spot identification mark is identified from a product model, and the welding spot file is a data file comprising a welding spot model; identifying a part model having an interference relationship with the welding spot model based on the position relationship of the welding spot file in the product model; taking an intersection surface obtained by intersecting the part models as a welding surface of the part models, projecting the welding spot model onto the welding surface to obtain a welding spot projection position, and detecting a shortest spot edge distance from the welding spot projection position to a welding surface boundary; based on the shortest point edge distance, the width of the welding face is determined through an auxiliary face intersection method; and detecting whether the product model is qualified or not based on the shortest point edge distance and / or the width of the welding surface. The technical problems that in the prior art, welding spot detection mainly depends on manual estimation, so that subjectivity is high, efficiency is low, and missing detection is prone to occurring are solved.

The invention provides a component position determination method and system. The method comprises the steps of obtaining product model information of a product corresponding to a target order; according to the product model information, a target product model process rule is obtained through matching from a preset product model process rule database, and the target product model process rule comprises component attribute information of the product; based on the target product model process rule, obtaining material type information of parts required by the product, and determining each part required during production of the product according to the material type information; and based on the hierarchical structure type of the target order, according to the component attribute information, obtaining installation position information of each component from a corresponding bill of materials in the target product model process rule. According to the invention, the accuracy and the production efficiency of the intelligent manufacturing process are improved.

The invention discloses a large workpiece strain measuring point auxiliary positioning system and method, and the system comprises a professional software and automatic control system, and an industrial photogrammetry system, a car lifting system, a laser projection system and a three-dimensional scanning quantitative analysis system which are connected with the professional software and automatic control system. And a positioning target is arranged on the surface of the large workpiece product. According to the system, strain contact auxiliary lineation and laser guide assembly work of a large workpiece and quantitative analysis work of strain gauge pasting are achieved, the system takes a target arranged on a product as a positioning reference, the outline of a product model is extracted in a photogrammetry mode, the product model and a real object are matched and unified to the same coordinate system, and the product model and the real object are obtained. The position contour of the strain gauge needing to be pasted and auxiliary information are projected to the surface of a product through the laser projection technology, the current pasting position information can be efficiently and accurately reflected, and high-efficiency and high-precision assembly of the strain gauge is facilitated.

The invention relates to the field of data processing, and provides a cross-border e-commerce intelligent product selection system and method based on multi-platform data fusion, and the method comprises the steps: carrying out the data collection and preprocessing of a plurality of cross-border e-commerce platforms, constructing a neural network model through optimal hyper-parameters, training, and generating a selected product recommendation list. Meanwhile, the structural parameters and the search direction of the selected product model are continuously updated, and the selected product recommendation list is dynamically updated. According to the system, multi-platform commodity data are integrated, versioning feature snapshots are constructed, hyper-parameter selection of a multi-snapshot version evaluation strategy optimization model with a consistent time sequence is adopted, the generalization ability of a commodity selection model to a time-varying data environment is enhanced, the possibility that the accuracy of the model is reduced due to the change of data distribution is reduced, and the accuracy of the commodity selection model is improved. Meanwhile, dynamic updating of the selected product recommendation list is achieved, and it is ensured that the recommendation strategy can be fully matched with preference migration of the selected product trend.

The invention provides an automatic testing method and system based on an Internet of Things model, electronic equipment and a storage medium, and aims to solve the problems of low efficiency and incomplete test of compiling a model test case. The method comprises the following steps: exporting a specific format file of a product model on an Internet of Things platform, and analyzing the file to obtain a product model test case; extracting each field content under attributes, events and service function types; respectively storing the extracted field contents according to events, attributes and services; and automatically generating test input data for each test item in combination with the data type and the parameter value range in the field content through an effective equivalence class and boundary value method, and storing the automatically generated test input data in the test input data item of the corresponding test case file to complete the automatic generation of the test case. The test case can be automatically generated, the test efficiency is improved, and the timeliness, stability and reliability of the test case are effectively improved.

The invention belongs to the technical field of digital assembly process design, and discloses a product model data structured processing method, electronic equipment and a storage medium, and the method comprises the steps: constructing a data storage structure of a product model assembly, which comprises an attribute table and a relation table; identifying components, parts, standard components and assembly digital models in the product model data; extracting attribute information of components, parts, standard components and assembly digital models in the product model data, and storing the extracted attribute information into an attribute table; and extracting contact relation information of the parts and the standard parts in the product model data and assembly relation information of the assembly digital model, and storing the extracted contact relation information and assembly relation information into a relation table. According to the method, the problems of low efficiency, large workload and poor accuracy of existing three-dimensional model data structured processing are solved.

The invention discloses a product quality problem solution automatic generation method and device, a medium and a product, and relates to the field of data processing. The method comprises the steps that a fault code and product type information of a current product quality problem are determined as a target fault code and target product type information, the fault code comprises multiple pieces of fault identification information, and the fault identification information comprises failure part information, failure position information and failure mode information; determining a first recommended solution set from a historical database based on the target fault code and the target product type information; when the data size of the first recommended solution set is insufficient, a second recommended solution set is determined from a historical database based on the fault identification information, and the data size of the second recommended solution set is larger than that of the first recommended solution set; and finally, generating a quality problem recommendation solution based on the second recommendation solution set. The problem that the formulating efficiency of the product problem solution is not high can be relieved.

The invention discloses a production line test construction system based on an MES system, and relates to the technical field of intelligent manufacturing and production line testing, and the production line test construction system comprises a test configuration module, a test execution module, a data integration module, a visual interface module and an authority management module. The test configuration module is used for automatically obtaining a test process template from the MES system according to the product model information and completing process customization in a graphical mode; the test execution module identifies a to-be-tested product and calls a process file, and controls the test equipment to execute a test and perform data acquisition and judgment; the data integration module binds the test result with the unique identifier of the product, and uploads the test result to the MES system to realize full-process tracing; the visual interface module is used for displaying a process state and a test result; the authority management module is used for performing hierarchical control and version conflict detection on the operation authority; according to the system, the construction efficiency and execution reliability of the test process are improved, and closed-loop and intelligent management of data in the test process is realized.

The invention discloses a generator accessory assembly machine tool control method and system, and relates to the technical field of assembly control, and the method comprises the steps: obtaining the design data of a target generator, and constructing a plurality of digital accessory models; interacting the accessory assembly machine tool, and obtaining an assembly reachable domain of the accessory assembly machine tool; performing reverse engineering according to the finished product model of the target generator, and constructing an assembly relation graph of the target generator; randomly generating an assembly scheme set by taking the assembly relation graph as an assembly constraint; based on the multiple digital accessory models and the assembly reachable domain, a twin assembly space is constructed, and simulation assembly is conducted on the assembly scheme set; defining an assembly evaluation function, evaluating the simulation assembly result based on the assembly evaluation function, and extracting an optimal assembly scheme from the assembly scheme set; and the optimal assembling scheme is input into a control system of an accessory assembling machine tool, and assembling operation is carried out. Therefore, the technical effect of improving the assembly consistency and the assembly efficiency is achieved.

The invention discloses a semi-solid magnesium alloy forming management control system and method, and relates to the technical field of intelligent management, and the method comprises the following steps: sending a first regulation and control signal, calculating the similarity between an actual finished product picture and a first picture, judging the defect of an actual finished product, screening a second control parameter, and setting a first change amount; sending a second regulation and control signal to obtain a third control parameter, calculating the temperature change rate of the subspace, screening the fault subspace, sending a maintenance signal, and establishing a first association relationship. The quality of the finished product is improved by matching the first control parameters corresponding to the finished product model and the mold model, the generation of the defects is effectively detected and prevented by acquiring the actual finished product picture and the historical defect information, setting the similarity threshold and judging the actual finished product defects, intelligent control is realized through the association relationship, and the production efficiency is improved. The production efficiency and the product quality are improved, and defects are reduced, so that the waste of materials is reduced, and the production cost is reduced.

The invention relates to a product customization and configuration method and system based on a product model and a knowledge base. The method comprises the following steps: (a) associating a product structure model and a product knowledge base of a target product series; (b) constructing a product configuration model integrating a product structure model, a product knowledge graph and a configuration rule; (c) customer demand parameters are received, and a customized configuration scheme is generated through the product configuration model; (d) automatically generating a design material list and a process material list based on the customized configuration scheme; and (e) executing cost accounting according to the generated design bill of material and the process bill of material and outputting quotation data. The method has the advantages that the requirement of a user for customization can be met, the requirement for configuration can also be met, data such as technologies and processes can be automatically configured for the user, the data can be synchronously updated to related software systems such as PLM and PDM, and the intelligent design and intelligent manufacturing capacity of an enterprise is greatly improved.

The invention provides a method, system and device for collecting MODBUS device data based on an Internet of Things platform and a medium, and belongs to the technical field of data conversion, and the method comprises the following steps: obtaining point table information of a target MODBUS device, MODBUS channel information for data collection of the target MODBUS device, and point position information configuration; creating a product model, a device model and an object model for the target MODBUS device on the Internet of Things platform, and carrying out mapping relation binding with point location information of data acquisition of the target MODBUS device; reading data from the target MODBUS equipment according to the bound mapping relation, and storing the data according to a preset storage strategy; and converting the read target MODBUS equipment data into standard data which can be identified by the Internet of Things platform. The MODBUS equipment data is efficiently converted into the Internet of Things standard data, the cost period is shortened, and the method is compatible with a multi-equipment platform.

Three-dimensional (3D) modeling systems and methods are described for automatically generating photorealistic, virtual 3D package and product models from 3D and two-dimensional (2D) imaging assets. The 3D modeling systems and methods include loading, into a memory with one or more processors, computer-aided design (CAD) component(s) and assembling, with an automatic imaging asset assembly script, the CAD component(s) to create a parametric-based CAD model. A polygonal model of a real-world product or product package is generated based on the parametric-based CAD model. Digital surface finish artifact(s) of a virtual material library, as selected from the 2D imaging assets, are applied to the polygonal model. A virtual 3D model is generated based on the polygonal model and a UV coordinate mapping corresponding to a virtual product label, and rendered, via a graphical display, as a photorealistic image representing the real-world product or product package.

The utility model discloses an internal expansion assembly mechanism, which belongs to the technical field of flange assembly and comprises a main body, a control device, a fixing device and an internal expansion device are mounted on the main body, a tool product is mounted on the fixing device, and the control device and the fixing device are connected with the internal expansion device. The internal expansion device comprises a tool assembly and an internal expansion assembly, the tool assembly is connected with the main body, the tool product and the internal expansion assembly, and the internal expansion assembly is connected with the main body and the control device. By means of the mode, the tool assembly is driven by the internal expansion assembly to conduct internal expansion assembly work on a tool product, rapid assembly of the product is achieved, operation is easy, and efficiency is high; through detachable connection of the tool base and the tool quick-change head, different fixing devices and tool assemblies can be replaced to adapt to different product models; through the arrangement of the tension sensor, the tension borne by each product is kept consistent, the assembly effect is unified, and the tension can be adjusted according to different product models or requirements.

The invention discloses a text-guided 3D knitted product model generation and editing method and device, and relates to the field of computer vision, and the method comprises the steps: S1, employing a 3D diffusion model to enable a knitted product prompt text to generate an initial point cloud; s2, optimizing the initial point cloud and initializing the initial point cloud into a 3D Gaussian; s3, performing projection rendering on the initial 3D Gaussian to obtain a multi-view image sequence, and performing semantic segmentation on the multi-view image sequence based on an editing prompt text to obtain a mask sequence; s4, acquiring a 3D Gaussian with a semantic tag based on the mask sequence; s5, projecting the 3D Gaussian with the semantic tag to a 2D plane to obtain a rendered image; inputting the rendered image and the editing prompt text into a 2D diffusion model, and outputting a loss gradient; and utilizing the loss gradient to guide the 3D Gaussian to carry out iteration, wherein the 3D Gaussian obtained after iteration is finished is the final 3D knitted product model. According to the method, the 3D Gaussian is introduced, the semantic tag is added for the 3D Gaussian by using the editing prompt text, and the generation efficiency, the local semantic control and the high-precision editing are considered.

The invention discloses a multi-machine cooperative control system based on injection molding, which relates to the technical field of intelligent control, comprises an acquisition module, an analysis module and a control module, and is characterized in that a first similarity is calculated, a first operation is executed, a change gradient of problem parameters is set, and the problem parameters are continuously controlled according to the change gradient; and continuously obtaining a regulated second similarity, and executing a second operation. By obtaining the standard production data and the current product model, the number of times of new product mold testing is reduced, the production efficiency is improved, the process parameters are automatically calculated and recommended, the accuracy and efficiency of process parameter setting are improved, and by simulating production and calculating the similarity between the finished product image and the standard defect image, abnormity in the production process can be found in time, and the production efficiency is improved. Through continuous control and timely adjustment, defective products are reduced, and the product quality is improved, so that injection molding control has relatively good decoupling capability, anti-interference capability and robustness, and the product quality problem is reduced.

The invention relates to the technical field of disease detection and disposal methods, in particular to an intelligent detection and disposal method for large-displacement modular expansion and contraction diseases, and the method comprises the steps: obtaining static data and dynamic data of a large-displacement modular expansion and contraction device; wherein the static data comprises equipment specification, product model and manufacturer information, and the dynamic data comprises temperature, humidity, displacement, tensile stress and speed information; constructing a data analysis model by adopting an artificial intelligence algorithm based on the static data and the dynamic data; determining the health condition, predictive maintenance time and fault diagnosis information of the large-displacement modular telescopic device according to the output result of the data analysis model; generating an intelligent detection report containing health conditions, predictive maintenance time and fault diagnosis information; and based on an intelligent detection report, a disposal scheme of the large-displacement modular telescopic device is formulated, so that the reliability and the service life of the equipment are remarkably improved, and the maintenance cost is greatly reduced.

The invention discloses a product component material matching method, electronic equipment and a storage medium, and the method comprises the steps: obtaining configuration demand information which comprises a product model, a use working condition type and a working condition demand specification corresponding to the use working condition type; corresponding material information is matched according to the configuration demand information, and the material information comprises a material name, a material model and a material number; and generating a bill of materials according to the material information. According to the technical scheme, the corresponding material information is matched according to the configuration demand information, and then the bill of materials is generated according to the material information, so that the material matching process is automatic, the error risk caused by human factors is reduced, and the material matching accuracy is improved.

The embodiment of the invention discloses a commodity information display method and electronic equipment. The method comprises the steps that a 3D space model and 3D commodity models of multiple commodities are determined; performing ray tracing-based panorama offline rendering on the 3D space model to obtain a background panorama layer; the method comprises the following steps: respectively placing a single 3D commodity model at a target position corresponding to a category in a 3D space model, setting material parameters of the 3D space model to be transparent and keeping light and shadow information, and then carrying out ray tracing-based panorama offline rendering to obtain foreground panorama layers respectively corresponding to the plurality of 3D commodity models; determining a superposition sequence between the layers corresponding to the multiple target positions; and superposing the background panoramic image layer and the foreground panoramic image layers corresponding to the plurality of commodities according to the superposing sequence to generate a panoramic stereogram for displaying commodity information. Through the embodiment of the invention, the rendering quality can be improved, the loading time is shortened, and interactive experience is provided for the user.

The invention relates to the field of wind power generation tool design, in particular to a tool parameterization rapid design platform and method for a wind power generator, the tool parameterization design platform is established on UG software, secondary development is carried out based on the UG software, and an incidence relation is established with a TC platform; the tool parameterization design platform comprises a tool parameterization design specification module and a tool parameterization design knowledge base, the tool parameterization design specification module and the tool parameterization design knowledge base are stored in a TC platform, and the tool parameterization design specification module and the tool parameterization design knowledge base are called to achieve the tool parameterization design specification module and the tool parameterization design knowledge base. And parameterization design of the wind power generator tool is realized. By setting the tool parameterization rapid design platform of the wind power generator and the corresponding design method, the incidence relation between the tool design of the wind power generator and the product model is established, linkage control over the key size and the design size of the tool model is achieved, the design process is optimized, and the tool design efficiency is improved.

The invention relates to a powder filling method and system of a hydraulic servo forming machine and an intelligent terminal, and relates to the field of hydraulic servo forming machines. The powder filling method comprises the steps that the product model of a to-be-formed product and image information of a forming cavity are obtained; matching powder demand according to the product model and a preset product database; shape and size information of the forming cavity is determined according to the image information of the forming cavity; according to the powder demand quantity and the shape and size information of the forming cavity, a powder filling device is controlled to fill the forming cavity with the metal powder and conduct preliminary smoothing, and metal powder image information after the forming cavity is filled with the metal powder is obtained; establishing a powder top surface fall model according to the metal powder image information and preset powder characteristics; determining all powder valley point positions and powder peak point positions according to a powder top surface fall model; and according to the powder valley point position and the powder peak point position, an air blowing device is controlled to conduct pulse air blowing on the metal powder so as to smoothen the metal powder. The forming device has the effect of improving the forming quality of the metal parts.

A system for receiving a product dataset associated with a product comprising one or more subproducts, a first corresponding product dataset associated with a first corresponding product, and a second corresponding product dataset associated with a second corresponding product. A system may determine a product model output corresponding to the product, wherein the product model output is a single, value-weighted indicator of the product. A system may determine a first variability index corresponding to the first corresponding product based at least on the product model output and the first corresponding product dataset, and a second variability index corresponding to the second corresponding product based at least on the product model output and the second corresponding product dataset. A system may display a visual indicator on a graphical user interface the first variability index and the second variability index.

A system for processing images captured in a retail store is provided. The system may include a processor configured to: access a database storing a group of product models; receive an image depicting at least part of a store shelf having a plurality of products of a same type displayed thereon; analyze the image and determine a first candidate type of the products based on the group of product models and the image analysis; determine a first confidence level associated with the first candidate type; when the first confidence level is below a confidence threshold, determine a second candidate type of the products using contextual information; determine a second confidence level associated with the determined second candidate type of the plurality of products; and when the second confidence level is above the confidence threshold, initiate an action to update the group of product models stored in the database.

The invention discloses a high-entropy alloy electrode production management method and system based on quality tracing, and belongs to the technical field of production management, and the method specifically comprises the steps: endowing an identifier for an electrode production batch, and collecting a technological parameter curve; dividing application scenes and storing data in a classified manner by associating batch identifiers with terminal product models; obtaining the statistical failure life of the terminal product and extracting related process curves to form an analysis sample set; quantitative fluctuation characteristics of the process curve are extracted, and correlation analysis is carried out on the quantitative fluctuation characteristics and corresponding batches of life; defining a process characteristic value interval in positive correlation with the long life in a specific scene and generating a corresponding production control parameter set; and matching an application scene according to the order product model, and calling a corresponding parameter set to execute directional production. According to the method, closed-loop tracing and correlation analysis between process data and terminal service performance are constructed, so that the performance suitability and the production control accuracy of the high-entropy alloy electrode in subdivision application are improved.

The invention relates to the technical field of data processing, and provides a product sales prediction method and device, electronic equipment and a medium, and the method comprises the steps: obtaining historical sales information of a plurality of marketing categories of a product and a historical sales proportion information set of each marketing category; predicting the total sales volume of each marketing category in a future set time period according to each piece of historical sales volume information; according to each historical sales volume ratio information set, predicting a sales volume ratio of each product model in a future set time period; and according to the total sales volume of each marketing category and the sales volume proportion of each product model in each marketing category, predicting the sales volume of the product model in a future set time period. According to the method, the set of the plurality of product models, namely the overall total sales volume of each marketing category in the future time period, is predicted firstly, and then the sales volume proportion of the future time period is predicted according to the sales volume proportion change of the single product model in the marketing category to which the single product model belongs, so that the product sales volume prediction is realized, and the prediction accuracy and efficiency are improved.

The invention relates to a product model generation method and device, electronic equipment and a readable storage medium. The method comprises the following steps: obtaining product key elements from obtained product demand information, and constructing structured product demand data according to the product key elements; matching a target reference model from a preset reference model database based on the structured product demand data; matching a target reference parameter instruction from a preset reference instruction database according to the target reference model and historical design data corresponding to the target reference model; according to a preset parameter recommendation neural network, performing parameter mapping based on the structured product demand data, the target reference model and the reference parameter instruction set, and generating a target design instruction set; and generating a product model based on a parameter driving technology and the target design instruction set to obtain a first target product model. According to the scheme provided by the invention, product model generation can be automatically driven in a whole process, the design efficiency and the result consistency are improved, and then the demand of quickly responding to the market is met.

The invention provides a product test scheme design method and device and a storage medium. Establishing a standard test case library and a definable test case library; when a test scheme is constructed, an information file of a to-be-tested product is provided for the large language model, and the large language model is restrained through a first system cue word to analyze the information file to obtain a model and a version of the to-be-tested product; on the basis of test function instructions of the test cases in the library, standard to-be-tested functions are classified and summarized from the information file, and the to-be-tested functions, newly-added to-be-tested functions and respective sources can be defined; the large language model matches a target standard test case and a target definable test case suitable for the to-be-tested product from a standard test case library and a definable test case library based on the standard to-be-tested function, the definable to-be-tested function, the version and the model under the constraint of a second system cue word; and creating a test scheme task by combining a definable to-be-tested function source, a newly added to-be-tested function and the source of the newly added to-be-tested function of the matching target definable test case.

The invention relates to the technical field of image processing, in particular to a data processing method for building structure model design. Obtaining a plurality of historical product models and a current product design sketch, and respectively constructing corresponding undirected graphs; taking each node in the undirected graph of the current product design sketch as a first initial node, and obtaining a path set of the first initial node; acquiring a second initial node corresponding to the first initial node, and acquiring a path set of the second initial node; obtaining the similarity between the first initial node and each corresponding second initial node; arranging the part types corresponding to the second initial nodes to obtain a type recommendation sequence of the part types corresponding to the first initial nodes; and obtaining a model recommendation sequence of each part type in the current product design sketch to carry out product model design. According to the method, the models of the parts in the current product design sketch are recommended through the attribute association among the parts in the historical products, so that the model establishment is more convenient.