133 results about "Design knowledge" patented technology

The invention provides a ship design knowledge retrieval method and system based on a multi-modal knowledge graph. The method comprises the steps of collecting and constructing a ship design set from the ship design field; forming a hierarchical multi-modal knowledge graph for describing a ship design field concept, physical characteristics and design specifications; enhancing association among different modal data through vector similarity calculation; the hierarchical multi-modal knowledge graph is integrated into a ChatGLM model; positioning knowledge nodes related to user demands in the hierarchical multi-modal knowledge graph; matching and positioning the ship design knowledge related to the query content of the user, and feeding back the ship design knowledge obtained by the intelligent semantic retrieval to the user in a hierarchical form. According to the method, ship design knowledge retrieval based on the multi-modal knowledge graph enhanced ChatGLM is realized, and the information acquisition efficiency of engineering designers and the practical application value of the system are improved.

The invention relates to a multi-modal data and RAG technology fused power design knowledge base construction method, and belongs to the technical field of power software development. The method comprises the following steps: carrying out collection and information extraction on multi-source heterogeneous original data; the method comprises the following steps of: constructing a multi-dimensional knowledge element structure containing parameters, specifications and case relationships by carrying out classification, specialized and precise processing and cross-modal association on data; based on a vector, graph and relational database mixed storage architecture, semantic vector efficient retrieval, knowledge graph relation management and business data synchronization are achieved respectively; and a dynamic optimization result is subjected to hybrid retrieval, a dual-drive reasoning mechanism outputs compliance conclusions and bases, and a retrieval enhancement generation service ensures that output contents conform to specifications. And systematic management and intelligent application of the electric power design knowledge are realized.

A system and method for interactive visualization of knowledge provided by large language models (LLMs) is disclosed. The system advantageously organizes LLM responses into an interactive knowledge graph visualization. Additionally, the system enables the user to interactively expand a knowledge graph by further prompting the LLM to provide additional responses that include additional knowledge. When applied to the task of design ideation, the interactive knowledge graph visualization helps to mitigate design fixation and enhances the overall efficiency, quality, quantity, and depth of concepts in the ideation process.

The invention provides a transformer substation AI aided design method based on LLM and RAG, and the method comprises the steps: carrying out the demand analysis through a large language model LLM, and extracting key information; performing knowledge retrieval by using an RAG technology, wherein the knowledge retrieval comprises transformer substation aided design knowledge base construction, transformer substation aided design knowledge retrieval and knowledge reordering; according to the demand analysis and the knowledge retrieval result, the LLM is utilized to generate a preliminary design scheme of the transformer substation, and the design scheme comprises an electrical main wiring diagram, equipment type selection and layout. By adopting the combination of the LLM, RAG and AI aided design, the comprehensive improvement of the design efficiency, standardization and innovation of the transformer substation can be realized, and the problems of low efficiency, insufficient standardization and lack of innovation in the prior art are solved.

The invention discloses a product collaborative design management method and system based on data driving, and relates to the technical field of product design management, and the method comprises the steps: constructing a double-flow heterogeneous quantitative collection network; establishing an incidence matrix and calculating dynamic coupling strength among the parameters; designing a recursive deep belief network based on the incidence matrix and the dynamic coupling strength, encoding product structure parameters and design process data into a probability graph model, and constructing a design knowledge base; dynamically distributing the design rules in the design knowledge base by adopting a swarm intelligent optimization algorithm, generating a collaborative decision-making unit, and establishing a constraint propagation link; and generating a multi-target collaborative optimization scheme group, and screening an optimal scheme group based on Pareto frontier. According to the invention, omnibearing acquisition of product structure parameters and design flow data is realized through the double-flow heterogeneous quantitative acquisition network, and the data integrity is improved.

The invention discloses a boiler design file intelligent identification system and method based on a multi-modal knowledge graph. The method comprises the steps that S1, a data collection module is used for collecting a large number of existing boiler design files as a data set; s2, extracting information on the boiler design drawing in the data set by using a multi-modal feature extraction module to form a text-image multi-modal joint feature vector; s3, constructing a multi-modal boiler design knowledge graph with engineering semantics, graph structure association and reasoning capability; and S4, inputting the extracted key point information on the boiler design drawing to be examined into the knowledge graph model, and judging whether each design point meets the design specification requirements of the boiler drawing or not. According to the method, the identification period is greatly shortened, the working efficiency is improved, and the missed examination rate is remarkably reduced.

The invention belongs to the technical field of intelligent automobiles, and particularly relates to a system design method based on an intelligent automobile cyber-physical system field knowledge base, which comprises the following steps of: performing composition analysis on information elements and physical elements of an intelligent automobile cyber-physical system, and constructing an IVCPS field knowledge base by using an ontology representation method; the application technology method for constructing the IVCPS domain knowledge base comprises the steps that knowledge reuse based on the IVCPS domain ontology knowledge base is achieved through knowledge representation language conversion, and auxiliary system modeling design based on the IVCPS domain knowledge base is achieved; the knowledge representation language conversion comprises the following steps: constructing a mapping relationship between a knowledge modeling language and an extensible markup language and a system modeling language; based on an IVCPS field knowledge base application technical method, system design based on the IVCPS field knowledge base is realized, instance analysis is performed by using typical traffic scenes in the IVCPS field, the effectiveness of the system design method is verified, system design research can be effectively assisted, data collection time is shortened, and repeated work is avoided.

The invention discloses a method for constructing a vectorized knowledge base based on dynamic fields for an RAG system, and the method comprises the following steps: 1, designing knowledge base fields: designing vectorized knowledge base fields, including static fields and dynamic fields, according to needs; step 2, document analysis and vectorization: analyzing the knowledge documents in various formats to generate a plurality of text blocks, and performing vectorization representation on each text block; step 3, constructing an index: constructing an index for each text block; and 4, determining a recall mechanism, improving the recall accuracy and coverage rate by adopting a text matching or vector similarity mode, and serving the constructed knowledge base for the RAG system. According to the method, a user can be helped to design the knowledge base based on dynamic fields, the construction process of the knowledge base is simplified, the construction efficiency of the vectorized knowledge base is improved, and later data updating and maintenance are more intelligent.

The invention belongs to the technical field of structural engineering knowledge management, and relates to an aircraft typical structural member intelligent algorithm integration application platform which is associated with a knowledge base and a database of typical structural members and comprises an application end and a management end. The application end comprises a part type selection module, a positioning element selection and parameter input module, a model preview and installation module and a model evaluation scoring module; the management end comprises a design knowledge and data access module, an algorithm management module and a template management module; a designer can call an algorithm designed by an algorithm designer at any time to complete and verify the model in the process of designing the model, and an algorithm designer can verify and correct the algorithm through a newly designed model, so that dual optimization of the model and the algorithm is realized, and the algorithm design efficiency is improved. The design efficiency of typical structural parts and functional algorithms is effectively improved, resources are saved, and meanwhile integrated management of the functional algorithms and models is achieved.

The invention provides a bridge design scheme generation method and device, equipment and a storage medium, and relates to the technical field of engineering design. The method comprises the following steps: acquiring constraint data, and extracting feature data from the constraint data; according to the feature data, obtaining a matching scheme from a knowledge base of bridge design cases, and encoding the matching scheme to obtain a population; and optimizing the population through a genetic algorithm to generate a bridge design scheme. According to the method, the bridge design knowledge base and the genetic algorithm are combined to realize automatic optimization recommendation of the bridge design scheme, the design efficiency and the scheme selection diversity are improved, the experience knowledge base is fully utilized, personal errors are reduced, meanwhile, design demand changes can be quickly responded, and innovation and development of bridge design are promoted.

The invention provides a ship management system design assisting method based on a knowledge graph, which comprises the following steps of: processing scattered design documents and design criteria of enterprises by utilizing a natural language processing technology, extracting knowledge triple information in the design documents and design criteria, and on the basis of the constructed knowledge graph, further utilizing a retrieval enhancement generation (RAG) technology to generate a knowledge triple; according to the method, subjective query of design information of a graph database is achieved, analysis and proofreading of design information graph-text and document data corresponding to design drawings and models are achieved, and finally design requirement query and automatic check of the design drawings and models in the design process of aided designers are achieved. Integration and sharing of design knowledge are completed, and the design knowledge utilization rate is increased.

The invention relates to the field of knowledge graph data processing, and discloses an indoor space automatic layout and rendering method and system based on a design knowledge graph, and the method comprises the steps: maintaining an entity knowledge graph containing a variation path, and discretizing a continuous geometric space into an environment topological graph; executing node mapping and resource topology handshake verification based on subgraph isomorphism; and responding to the mapping deadlock, triggering recursive topology rewriting along the variation path to reconstruct the query sub-graph, and generating a configuration instruction. According to the method, continuous geometric search is converted into discrete atlas isomorphism and attribute propagation, the high-dimensional space layout calculation complexity is reduced, the deadlock problem under the over-constraint condition is solved by utilizing a recursive variation mechanism, and the configuration efficiency is improved. And the logic leakproofness and engineering compliance of the layout scheme are ensured.

The invention discloses a generative artificial intelligence-based banquet creative design system, which comprises: a demand determination module, which is used for interacting with a user terminal, obtaining a user demand and generating a demand theme; the banquet creativity generation engine is used for determining and operating a proxy artificial intelligence assembly line and generating a banquet creativity design project; comprising a main control unit, a domain knowledge acquisition unit, a creativity generation unit and a integrating degree evaluation unit, each unit is embedded with a multi-level intelligent agent as an execution main body, and prompt information is defined as input of the execution main body; the brand domain knowledge vector library is used for providing domain knowledge; the banquet design domain knowledge vector library is used for providing banquet design knowledge; and the design output module is used for obtaining the banquet creative design project and forming a banquet creative design scheme. According to the technical scheme, multi-modal brand domain knowledge and banquet creative design can be deeply fused, and automatic generation of multi-modal information of a high-end banquet catering art scheme is achieved.

The invention discloses an AI-AD intelligent machine design method and system based on a learning-generation mode. The method comprises the following steps: S1, enabling an AI-AD intelligent mechanical design system to understand design knowledge at first; s2, compiling a workflow with low codes; s3, compiling a Prompt strategy of the design Agent and a called knowledge base; s4, repeating the steps S1 to S3, and compiling various agents needing to complete various specific design functions; s5, according to the designed various agents, a multi-agent self-organizing framework is utilized, and product creation type design is completed; and S6, according to the generated design result, generating a VBA file and storing the VBA file in the cloud. And S7, the SW establishes a conversation with the agent through a back-end API of the agent, timely reads a VBA code of the cloud for modeling, and outputs a model. According to the invention, a system structure of knowledge processing, cloud data storage, SolidWorks-based secondary development modeling and a human-computer interface module is constructed, Agents are enabled to learn at first, then design is created, and a 3D model meeting user requirements is generated, so that the current situation that knowledge engineering has extremely high requirements for practitioners' admission threshold can be reduced.

The invention discloses an AI processing method and system for long-term memory of mechanical design knowledge, and the method comprises the steps: carrying out the semantic analysis and feature extraction of heterogeneous knowledge, such as parameterization formulas, engineering charts, technological processes and design principles, in the field of mechanical design through a multi-agent collaborative learning system; and establishing a multi-dimensional modular knowledge base and context-based Prompt strategy coupling mechanism. The method solves the problems of low efficiency, insufficient analysis accuracy, limited innovation support capability and the like in the existing mechanical design knowledge processing technology, and particularly solves the technical problems of high calculation complexity, inaccuracy in reasoning, poor adaptability and the like when multiple types of design knowledge are processed. Through the implementation of the method, the processing efficiency of the design knowledge and the design automation level are remarkably improved, the technical threshold of a designer is reduced, the design period is shortened, efficient analysis, accurate matching and innovative application of the mechanical design knowledge are achieved, and powerful support is provided for intelligent development of mechanical design.

The embodiment of the invention discloses a design code generation method based on cloud service. The method is applied to a cloud management platform. According to the method, the dominant design intention input by the user can be obtained from the configuration interface, and the target design knowledge associated with the current dominant design intention of the user can be inquired from the knowledge graph so as to capture the implicit design intention implicit to the target design object. Thus, the dominant design intention and the target design knowledge from the knowledge graph can be combined to guide the large language model to efficiently and accurately generate the target design code meeting the design requirement of the user, intelligent generation of the target design code is achieved, the design task is accurately and efficiently achieved according to the target design code, and the user experience is improved. And obtaining a target design object.

The invention discloses a knowledge graph and RAG-based multi-modal engineering design intelligent generation method and system. The method comprises the following steps of S100, multi-modal data analysis and structured processing; s200, constructing a domain knowledge graph; s210, constructing a standardized module library; s300, performing intelligent retrieval and scheme generation; and S400, compliance verification and feedback learning are carried out. Through deep collaboration of the domain knowledge graph and the standardized module library, spanning of engineering design knowledge from'retrieval 'to'understanding and driving' is achieved, the problems of knowledge fragmentation and low reuse rate are solved, and the design efficiency, quality and automation level are remarkably improved.

Disclosed in the embodiments of the present application is a cloud service-based design code generation method, the method being applied to a cloud management platform. The method can not only acquire from a configuration interface an explicit design intention input by a user, but also query a knowledge graph for target design knowledge associated with the current explicit design intention of the user so as to capture an implicit design intention of a target design object. Thus, the explicit design intention and the target design knowledge from the knowledge graph can be combined to guide a large language model in efficiently and accurately generating target design code that meets a design requirement of the user, thereby intelligently generating the target design code so as to accurately and efficiently implement a design task on the basis of the target design code to obtain the target design object.

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 discloses a home decoration design description specialization optimization method fusing a semi-structure RAG technology, and belongs to the technical field of artificial intelligence and home decoration design crossing. The method comprises the following steps: constructing a semi-structured home decoration design knowledge base, cooperatively processing an original corpus through a script and AI, generating a structured JSON knowledge unit, and performing vectorization storage; receiving natural language query of a user, performing intention recognition and vectorization, and recalling related knowledge units by adopting a mixed retrieval strategy in combination with semantic retrieval and metadata filtering; and dynamically constructing an enhanced cue word through an RAG technology, and inputting the enhanced cue word into the large language model to generate a professional and detailed home decoration design description text. According to the method, the problems that the content generated by the existing AI design tool is lack of specialty and the user demand conversion is inaccurate are effectively solved, the quality and the practicability of the design text are improved, and the use threshold of professional design is reduced.

The invention discloses a personalized design knowledge recommendation method based on knowledge graph and dynamic demand modeling, which comprises the following steps: firstly, constructing a design knowledge presentation layer which comprises a knowledge ontology and a knowledge graph, and then constructing a knowledge recommendation layer which comprises a knowledge ontology and a knowledge graph; the knowledge recommendation layer comprises a task stage knowledge demand model and a packet receiving party knowledge demand model, a dynamic knowledge demand vector and a task stage knowledge demand vector of a packet receiving party are matched with design knowledge nodes in the knowledge graph, and knowledge nodes most relevant to the demand of the packet receiving party are screened out; and according to a knowledge graph matching result, screening out a knowledge node most related to the demand of the packet receiving party, and generating a final recommendation result through an optimization algorithm. The method has the advantages that dynamic changes of knowledge requirements of a crowdsourcing party can be effectively solved, more personalized and accurate design knowledge recommendation can be provided, and the execution efficiency and design quality of crowdsourcing design tasks can be improved.

The invention relates to the field of mechanical intelligent design, in particular to a knowledge-based mechanical structure intelligent design method, system and device and a medium, and the key points of the technical scheme are that the method comprises the following steps: obtaining design demand information; converting the design demand information into a plurality of knowledge points; decomposing each knowledge point into a plurality of knowledge types, wherein each knowledge type corresponds to a plurality of pieces of knowledge content; combining the knowledge type and the knowledge content of each knowledge point to finally form a plurality of knowledge points meeting design requirements; and combining the plurality of knowledge points meeting the design requirements to form a design result, and outputting the design result. Starting from knowledge calling in the actual mechanical structure design process, the mechanical structure intelligent design scheme based on knowledge is constructed by mining design knowledge, decomposing knowledge points and designing knowledge combination, the logicality and interpretability of the design result are high, and the design quality and efficiency are remarkably improved.

The invention relates to an electronic product PCB design system and method. In the system, a data preparation and knowledge base construction module is used for collecting, cleaning and de-duplicating multi-source PCB design data and constructing a comprehensive PCB design knowledge base; the polymorphic large model construction and training module adopts a hybrid neural network based on a transformer architecture, and constructs a polymorphic large model with a cross-modal reasoning capability by jointly training a schematic diagram semantic understanding model, a layout topology optimization model and a signal integrity prediction model; the intelligent auxiliary Agent module is used for integrating a reinforcement learning agent and a rule verification agent, and providing a wiring path optimization suggestion, element type selection recommendation and design specification compliance detection in real time; and the system integration module is used for automatically designing the generation module and converting the optimization scheme output by the polymorphic large model into a final PCB design file. The system can improve the design automation level.

The present invention proposes a method for constructing a railway engineering design knowledge base based on a cloud platform, which is applied to the cloud platform. The method includes: using the cloud platform to collect multimodal data, designing a distributed file system to store preprocessed data, and establishing a data indexing mechanism to retrieve multimodal data; using a deep learning model to intelligently analyze these multimodal data; identifying and extracting entities and relationships in railway engineering design from feature vectors of multimodal data to construct a knowledge graph, and then using a graph neural network to train the knowledge graph; automating design suggestions and optimization plans; constructing a cross-railway engineering design institution sharing model based on federated learning for knowledge sharing and privacy protection; designing a reinforcement learning model to train the simulation environment, and automatically generating a railway engineering design plan based on the trained reinforcement model. The present invention provides an efficient, intelligent and reliable knowledge base construction method for railway engineering design.

The invention discloses a numerical control machining method for a wood substitute transition mold based on equal-residue dynamic machining. The numerical control machining method comprises the following steps that S1, a machining path is optimized; s11, designing a knowledge enhanced path planning model; s12, generating an equal-residual-height cutter contact track; s2, cutting parameter collaborative optimization; s21, designing a multi-target parameter optimization model; s22, designing a dynamic parameter adjustment strategy; s3, numerical control machine tool parameter joint optimization design; s31, servo shaft parameter matching is carried out; and S32, cooling system cooperative control is carried out. According to the method, multi-dimensional collaborative optimization is adopted, and path planning, parameter optimization, machine tool debugging and cooling control are fused to form a closed-loop optimization system; according to the method, intelligent decision making is adopted, a knowledge graph and reinforcement learning are combined, and self-adaptive adjustment of a processing strategy is achieved; and high-precision guarantee is achieved, and the machining precision is improved to + / -0.02 mm through servo parameter matching and cooling control.

We provide an invention creation system and program that can systematically analyze technical and market information, accurately identify unexplored areas, and efficiently create and evaluate novel solutions for those areas. The invention creation system creates new inventions by analyzing a database containing technical literature, patent information, and market information. This invention creation system is characterized by comprising: a technology space modeling unit that analyzes the database, classifies technical elements into functional features and structural features, and maps the relationships between them onto a multidimensional technology space; a white space identification unit that identifies, as technological blank areas, areas in the multidimensional technology space where the combination density of existing technologies is low or areas where no structural features corresponding to specific functional features exist; a general-purpose design knowledge base that systematizes the mapping relationship between the functional space and the structural space and technological principles; and an automatic invention creation unit that sets required functions in the technological blank areas, searches for structural combinations that realize the required functions based on the general-purpose design knowledge base, and generates design solutions.

The invention provides a multi-modal knowledge graph generation method and system for hardware design analysis, which break through design, verification and physics, realize information barriers among the three traditional EDA (Electronic Design Automation) fields, perform semantic fusion and association on information from different data fields, create a unified and queriable hardware design knowledge representation, and improve the reliability of hardware design analysis. And a coherent and operable unified knowledge model is formed. A multi-modal design knowledge graph is created by integrating a simulation result (dynamic data) and a physical implementation feature (performance data) into a static structure model, and a comprehensive design model with structure, behavior and performance features is analyzed in a unified framework. An engineer does not need to manually switch between different tools and data formats, but can access all-dimensional information about a static structure, a dynamic behavior and a physical property of a design through a single query interface.

The invention discloses a ship maintainability design recommendation method and system, and relates to the technical field of ship maintainability design, and the method comprises the steps: obtaining and processing ship maintainability design knowledge and ship DFMEA knowledge, and constructing a ship maintainability design knowledge base; constructing a ship maintainability design ontology according to the ship maintainability design knowledge base; the ship maintainability design ontology is structured representation of a knowledge base; obtaining text data input by a designer, and performing entity recognition on the text data by using a natural language processing technology to obtain an entity and a corresponding class; and obtaining a maintainability design strategy of the ship based on the ship maintainability design ontology and entity and the corresponding classes thereof. According to the method, the ship maintainability design ontology is constructed, effective management of ship maintainability design knowledge and ship DFMEA knowledge is realized, and an objective ship maintainability design strategy can be provided according to data input by designers, so that the maintenance efficiency is improved.

The present invention provides a ship design knowledge retrieval method and system based on a multimodal knowledge graph, the method comprising: collecting and constructing a ship design set from the field of ship design; forming a hierarchical multimodal knowledge graph that describes concepts, physical properties, and design specifications in the field of ship design; enhancing the association between different modal data by vector similarity calculation; integrating the hierarchical multimodal knowledge graph into a ChatGLM model; locating knowledge nodes related to user needs in the hierarchical multimodal knowledge graph; matching and locating ship design knowledge related to user query content, and feeding back the ship design knowledge obtained by intelligent semantic retrieval to the user in a hierarchical form. The present invention realizes ship design knowledge retrieval based on multimodal knowledge graph-enhanced ChatGLM, which improves the information acquisition efficiency of engineering designers and the practical application value of the system.

The invention provides a cross-modal multi-scale information fusion method and system supporting design knowledge push, and the method comprises the steps: constructing a patent data set containing patent abstracts and abstract drawings, extracting long text features and short text features through a text encoder, and extracting fine-grained and coarse-grained image features through an image encoder; the text and image features are input into a cross-modal attention fusion module, cross-modal information interaction of the text and the image is realized through a multi-head attention mechanism, and fused text and image features are generated; a loss function based on comparative learning is adopted, and the alignment effect of the image and text features in the semantic space is optimized; and inputting an innovative design concept, extracting feature representation of the innovative design concept, calculating the matching degree of the feature representation and patent data based on cosine similarity, and pushing related patent abstracts and attached drawings to designers according to similarity sorting. According to the method, the limitation in existing image-text matching and cross-modal information fusion can be solved.