152 results about "Industrial software" patented technology

The invention relates to the fields of computer graphic processing, industrial software technology and the like, discloses a Cocos engine-oriented pipeline loop perception linear decomposition method, and aims to solve the problem that a complex topological graph which cannot be effectively processed and comprises a high-density nested loop in the prior art. The structure is completely and accurately decomposed into a linear drawing instruction sequence which can be accepted by a Cocos engine, and lossless conversion of original topological information is ensured; comprising the steps that after undirected topological graph data are input, a ring detection algorithm is called to recognize and record all independent ring structures in an undirected topological graph and nodes and edges contained in the independent ring structures; judging whether at least one ring is detected in the previous step, and if the at least one ring exists, assigning a determined traversal direction for each detected ring according to a preset ring direction rule; and if the ring does not exist, skipping, and directly performing depth-first search traversal on the undirected topological graph data.

The invention discloses an industrial software cloud base intelligent operation and maintenance and fault self-healing method based on digital twinning, and relates to the technical field of digital twinning. According to the method, the hierarchical digital twinborn model is constructed and dynamically updated, and the operation state of the cloud base is accurately mapped and visually displayed in combination with independent visual modules of a physical layer, a logic layer and an application layer; the method comprises the following steps: calibrating a reference value in real time through a dynamic reference library, quickly identifying abnormity of each layer, generating graded early warning, improving abnormity response timeliness, constructing a dynamically updated fault knowledge graph based on historical fault data, integrating a multi-dimensional correlation analysis and confidence coefficient verification mechanism, positioning a unique fault reason, greatly shortening a fault diagnosis period, and improving fault diagnosis efficiency. And a strategy library is constructed based on a fault knowledge graph and historical self-healing cases, simulation verification is carried out on candidate strategies through a digital twin model, the effectiveness of the self-healing strategies is ensured, and then the self-healing strategies are issued and executed, so that intelligent and automatic fault repair is realized, and stable operation of the cloud base is ensured.

The invention discloses an industrial software intelligent building system and method based on a plug-in mechanism, and relates to the technical field of industrial Internet of Things, and the method comprises the following steps: defining a standardized format and an interface of a plug-in, and ensuring the compatibility and the expandability of the plug-in; establishing a plug-in library, and analyzing and recording a dependency relationship between plug-ins; performing semantic similarity matching on the user demand and the plug-in function, and screening plug-ins in combination with a plug-in historical success rate to form a plug-in combination; conflict analysis is carried out on the plug-in combinations, CPU occupancy rate detection is carried out on feasible plug-in combinations based on the conflict analysis, and plug-in combinations with unqualified CPU occupancy rates are removed; and activating the plug-ins according to the plug-in combination selected by the user to complete software function implementation, and executing dynamic updating of the plug-ins.

The invention belongs to the technical field of business process analysis, and discloses an agent-based industrial software demand acquisition and analysis method and system, and the method comprises the steps: constructing a multi-agent-based demand analysis system; converting user multi-modal input into a structured industrial software demand by using a multi-agent-based demand analysis system; and generating a business flow chart conforming to the BPMN standard according to the requirements of the structured industrial software. According to the invention, the multi-agent system is combined with the demand analysis task, so that efficient and accurate demand analysis is realized, and powerful support is provided for project planning and implementation in the new industrial era.

The invention provides a process digital collaborative management method and system based on a data unified exchange platform, and belongs to the technical field of industrial software and intelligent manufacturing, and the method comprises the steps: constructing the data unified exchange platform, so as to achieve the data exchange among a process management system, a PLM system and a production management system; in the process management system, based on the EBOM obtained from the PLM system, constructing and managing a multi-state process BOM including a basic PBOM, a trial-production PBOM and a production PBOM; and a collaboration mechanism is constructed through a data unified exchange platform, so that business collaboration based on the multi-state process BOM is realized. According to the method, the problems of data consistency and flow collaboration which troubles the manufacturing industry for a long time are solved, and key technical support is provided for enterprises to realize digital transformation and intelligent upgrading through efficiency improvement, quality guarantee, cost control and knowledge precipitation.

The invention discloses a multi-level service orchestration method for industrial software, which is particularly suitable for integrated development, deployment and management of industrial software application. The method focuses on arranging codes through dragging of a low-code page of a cloud platform, and performing automatic micro-service packaging and on-demand arrangement on the generated codes to form industrial software application. Constructing a mirror image for the micro-service application and carrying out containerization arrangement to form an application service capability; and finally, performing API-level arrangement on the atomic APIs provided by the service deployed by the container to form aggregated API capabilities. According to the method, each link from demand definition to final API service capability provision is integrally covered, especially for the field of industrial software, manual intervention is reduced, and the method is suitable for diversified application scenes.

The invention discloses a heterogeneous fuzzy and game-based double-layer adaptive evolution CAD modeling command generation method, and belongs to the technical field of artificial intelligence and computer-aided design intelligent modeling. The method solves the technical problems that in an existing natural language driven CAD command generation technology, fuzzy semantics are difficult to quantify and map, heterogeneous commands are poor in adaptability, the executable performance of generated commands is low, and the reasoning process is black-box-shaped. According to the method, a semantic analysis-game generation-evolution refinement-verification backtracking-knowledge precipitation full-process closed-loop architecture is constructed, the method can be applied to the fields of industrial software, three-dimensional modeling, intelligent design systems and the like, the engineering performability, generalization ability and reasoning interpretability of command generation are improved, the generation diversity and feasibility are balanced, and the method is suitable for popularization and application. And the model iteration cost is reduced, and technical support is provided for industrial landing of the text-driven CAD modeling technology.

The invention relates to the technical field of industrial software, and particularly discloses a three-dimensional model lightweight processing method and system in industrial software. The method comprises the following steps: associating data of a three-dimensional model to loadable parameters and reconfigurable parameters to execute differentiation processing on the three-dimensional model so as to generate a to-be-verified model, verifying the to-be-verified model through a verification port, and verifying the to-be-verified model according to three-dimensional parameter information causing a verification failure state. And regenerating a lightweight data packet for replacement operation or node data for reconstruction operation, and repeatedly executing the operation and verification process until lightweight is completed. While light weight processing is completed through replacement operation, high compression ratio is achieved through reconstruction operation, necessary model details are reserved, balance between light weight and model fidelity is achieved, errors in the processing process can be recognized and corrected, flow interruption caused by failure of single-time processing is avoided, and the processing efficiency is improved. And the functional integrity and availability of the output three-dimensional model are ensured.

The invention discloses a large-scale language model software operation and maintenance log analysis method based on meta-context learning, and the method comprises the following steps: S1, original log preprocessing, S2, log clustering and representative data set construction, S3, meta-context training data construction, S4, large-scale language model meta-context training, and S5, analysis reasoning data set construction. And S6, analyzing and reasoning a large language model log. By means of the method, an efficient, accurate and fast-adaptive solution combining offline element context training and online log analysis is provided for the log analysis task in the field of software operation and maintenance, the method is suitable for the log analysis task in an industrial software system, and the method has the remarkable advantage in analysis accuracy.

This invention discloses a phased anomaly detection method for ultra-large-scale industrial software supply chains based on graph neural networks. It divides the software anomaly detection task into two stages. In the rapid contamination stage, a simple model is used to quickly learn global anomaly patterns and filter out potential anomaly nodes and regions. In the precise detection stage, a more complex model is used to detect anomaly nodes. Furthermore, this invention defines the "disorder level" of nodes on the graph based on the Lyapunov coefficients in chaos theory and utilizes the "defect" of rapid oversmoothing in graph neural networks to rapidly propagate the behavioral patterns of anomaly nodes on the graph, simulating the propagation process of the entire chaotic system. In this way, this invention can quickly learn the global node anomaly patterns and quickly and accurately filter out candidate anomaly nodes and regions.

The invention relates to the technical field of industrial internet, artificial intelligence and human-computer interaction, in particular to an industrial internet software intelligent customer service interaction method based on multi-modal deep fusion. According to the method, an intelligent customer service system integrating natural language processing, a voice technology, computer vision and augmented reality (AR) is constructed aiming at the characteristics of complex operation, multiple user groups, high problem speciality and the like in an industrial scene. The core of the method is that operation questions, interface states and potential faults of engineers in software use are accurately understood through multi-modal input; an accurate solution is generated in combination with the knowledge graph of the industrial software and the real-time data of the equipment; a 3D virtual expert image is driven, and immersive and scene-based guidance is provided by fusing voice explanation, interface marking guidance, AR superposition demonstration and operation demonstration videos. The method has the working condition self-adaptive capability, can identify the professional level (such as a green hand / expert mode) of a user, and adjusts the explanation depth; and cross-region collaboration is supported, a plurality of users are allowed to synchronously share a guidance picture of a virtual expert, and efficient remote collaboration troubleshooting is realized. The method solves the technical problems that traditional industrial software is slow in customer service response, abstract in guidance, difficult to process complex problems on site and the like, and operation and maintenance efficiency and user experience are remarkably improved.

The invention discloses a gadget polishing process intelligent decision system applied to CAM industrial software. The gadget polishing process intelligent decision system mainly comprises the following steps: establishing a set of instance expressions which can be identified and used by a computer; establishing a small tool polishing instance database according to the instance expression; performing standardization and anomaly detection on the data in the instance library; establishing a process reasoning module for realizing static mapping from multiple input features to multiple output parameters; training a process reasoning module by using data in the instance library; a new small tool polishing process problem is imported into the process reasoning module; inputting the optimal prediction process parameters into industrial software with a CAM function; the industrial software generates a tool path and a machine code; the numerical control machine tool or the robot completes actual machining of the workpiece according to the machine code; and new data introduced by the new problem is recycled and classified into an instance library according to the instance expression requirements.

The present application relates to the field of industrial software, and provides a chemical process automatic generation method, system and medium. The chemical process automatic generation method comprises the following steps: receiving a natural language description about an industrial process, wherein the natural language description comprises design constraints of the industrial process; starting a multi-agent collaboration system, converting the natural language description into an intermediate representation of the design process through closed-loop interaction among the multi-agents, wherein the multi-agent collaboration system utilizes a semantic entropy index to monitor the logical determinacy of each generation node in the process of generating the design process and triggers a real-time correction mechanism according to the uncertainty quantification result; mapping the intermediate representation into executable instructions of a heterogeneous simulation engine through an adaptation interface to drive the heterogeneous simulation engine to perform physical simulation calculation; and asynchronously extracting the calculation result of the heterogeneous simulation engine to realize closed-loop verification of the design process.

The application discloses an industrial full-link through implementation method based on unique identification and double contract anchoring, and belongs to the technical field of intelligent manufacturing informatization. The method takes a plan number as a unique and unchangeable identification throughout the full life cycle from raw material warehousing to finished product warehousing, takes a contract hash value as a cross-table association anchor point, adopts a step-by-step anchoring mechanism of sales contract priority binding and procurement contract subsequent binding, and combines batch processing, transaction safety control and full-chain backtracking synchronization technology to realize bidirectional synchronous updating of procurement and sales contract information in full life cycle data tables such as raw material inventory tables and production process quality inspection record tables. The application breaks the strong coupling of the procurement and production processes, supports cost information post-recording, solves the pain points of data disconnection, untraceability, low efficiency and maintenance difficulty of traditional industrial software, has a simple architecture, high performance and stable operation, and is suitable for various intelligent manufacturing systems such as MES and ERP. The application has been applied in actual industrial scenes and has industrialization popularization capability.

The invention provides an industrial software user auxiliary system and a construction method, and the system comprises a data collection and preprocessing module which is used for obtaining an industrial software user document; wherein the user document comprises image data and text data; the image analysis module is used for converting the image data into a semantic text; the vectorization coding module is used for carrying out vectorization coding on the semantic text and the text data to obtain a semantic feature vector; the vector index database construction module is used for determining the topological information of the engineering entities according to the topological relation between the engineering entities corresponding to the semantic feature vectors; constructing a vector index database according to the semantic feature vectors and the engineering entity topological information; and the intelligent retrieval and question-answer generation module is used for performing similarity search in the vector index database under the condition of receiving information input by the user and outputting a query result.

The invention discloses an industrial software service combination method based on an improved multi-objective grey wolf algorithm, and the method comprises the following steps: building an industrial software resource service combination optimization problem framework, and completing the evaluation of QoS indexes including service time, service cost, service reputation, service delivery quality and the like and availability indexes; an SCOS model with optimal service quality (QoS) and availability as targets is constructed; tent chaotic mapping and a Levy flight improved differential evolution strategy are fused into a multi-target grey wolf algorithm model, the improved multi-target grey wolf algorithm model is used for solving an SCOS model, and the effectiveness and feasibility of the method are verified through algorithm performance verification and example testing. According to the improved multi-target grey wolf algorithm model, the convergence speed can be effectively increased, manual combination is liberated, and the problem of local optimization of industrial software combination is effectively solved.

This invention discloses a method and system for processing the entire lifecycle of procurement contracts based on a unified stored procedure with multiple TVPs and AI protection verification, belonging to the field of industrial software MES / ERP technology. This invention uses three sets of table-valued parameters (TVPs) as a unified data entry point, integrating six core operations—adding, modifying, deleting, appending details, modifying details, and deleting details—in a single stored procedure, and returning unified exception information through a single output parameter. The system incorporates a two-level centralized parameter verification mechanism. The first level performs a one-time empty table check on the three sets of TVP tables; if any table is empty, the transaction is immediately rolled back and an exception is returned. The second level performs centralized integrity and legality verification on all business parameters, achieving security protection for AI and external calls, effectively intercepting dirty data and illegal requests. This invention features a simple architecture, high execution efficiency, and comprehensive business coverage. The transaction mechanism ensures strong consistency of master-slave table data, supports compatible operation with both SQL Server and GaussDB databases, and can securely integrate into the AI ​​ecosystem without business restructuring. It is particularly suitable for the high-stability and high-security procurement contract business processing of complex factories with more than 11 production lines. This invention has been fully implemented in a real industrial ERP system and can run stably in a real production environment for a long time, demonstrating mature engineering value and industrial promotion capabilities.

This invention discloses a design-oriented multiphysics industrial software model integrated development system, comprising a hardware layer, a runtime environment layer, a service layer, an interface layer, a view layer, and an application layer. The hardware layer includes high-performance computing nodes; the runtime environment layer includes simulation software, a solver, and HPC scheduling for simulating industrial cloud software and scheduling HPC; the service layer includes geometric model data preprocessing services, mesh model data preprocessing services, mesh data post-processing services, and simulation task scheduling services for data processing before and after simulation and simulation task scheduling; the interface layer provides a unified interface; the view layer provides a 3D rendering engine for geometric model rendering, mesh model rendering, mesh boundary picking, and post-processing and rendering of the mesh; the application layer provides evaluation and analysis software for analyzing and evaluating the simulation results of the industrial cloud software. This invention realizes the integrated development and simulation of industrial cloud software.

This invention relates to the fields of computer graphics processing and industrial software technology, and discloses a pipeline loop-aware linearization decomposition method for the Cocos engine. It aims to solve the problem of complex topological graphs containing high-density nested loops, which cannot be effectively processed by existing technologies. The goal is to completely and accurately decompose such structures into a sequence of linear drawing instructions acceptable to the Cocos engine, ensuring lossless transformation of the original topological information. The method includes: after inputting undirected topological graph data, calling a loop detection algorithm to identify and record all independent loop structures in the undirected topological graph, as well as the nodes and edges contained in each independent loop structure; determining whether at least one loop was detected in the previous step; if a loop exists, assigning a definite traversal direction to each detected loop based on predefined loop direction rules; if no loop exists, skipping the loop and directly performing a depth-first search traversal on the undirected topological graph data.

1. The name of this design product: Intelligent Logistics Access Controller (IAC1050). 2. Purpose of this design product: as a server, a hardware device used to host industrial software systems. 3. The key design point of this design product lies in the combination of shape and pattern. 4. The picture or photo that best illustrates the design points: Stereoscopic drawing 1.

The invention relates to the technical field of intellectualization and industrial software, in particular to a radio frequency circuit programming method and system based on artificial intelligence collaborative design, and the method comprises the steps: generating an initial schematic diagram and codes; training a circuit generation model; predicting candidate code snippets; simulating and screening the accepted fragments; displaying the accepted fragment and counting the operation frequency; adjusting the model based on the operation; performing loop iteration to target generation, and training a circuit generation model by using preprocessed data through close combination of a design index, an initial circuit schematic diagram and a structured code so as to realize intelligent prediction of a radio frequency circuit code snippet; high-quality code snippets are dynamically screened in combination with performance simulation results, and then a self-adaptive feedback mechanism is formed based on dragging frequency and parameter modification frequency data in user interaction. The problems of low design efficiency and high error rate caused by weak generalization ability of a circuit design result due to model static training and lack of performance closed-loop verification are effectively solved.

The invention discloses a simulation model code automatic restoration method and device based on deep learning and a medium, and the method comprises the steps: S1, carrying out the preprocessing of an original model file, and forming a structured abstract syntax tree AST and a component dependency graph; error detection and repair code generation are carried out by using an improved LLM model, the error detection stage is realized by an improved CodeBERT, and the repair code stage is generated by adopting a GPT decoder; in the error detection stage, auxiliary information is used for enriching fine adjustment, and a multi-modal fusion mechanism is introduced to integrate serialized code texts and structured auxiliary information into a model training process at the same time, so that the error detection capability of the model is enhanced, and defect positions of deep relationships such as component dependence and equation logic are captured; in the code repairing stage, reinforcement learning fine tuning is used. According to the method, an automatic detection and repair scheme for common errors of Modelica model codes is provided for a user, and the development efficiency and reliability of a complex simulation model in industrial software are improved.

The embodiment of the invention provides a heat meter process design method and device based on large-scale industrial software, computer equipment and a medium, and relates to the technical field of aeronautical manufacturing, the method comprises the following steps: after a process system publishes a design EBOM of a component, determining a process route according to process division information, the process route is sent to the heat meter node; before process nodes in the preorder of the heat table nodes issue respective process instructions, the heat table nodes determine heat table process tasks according to the process routes and the three-dimensional models of the components; and designing a heat meter process instruction according to the part information and the design information of the three-dimensional model and the delivery specification. According to the scheme, the problems that nodes are lagged and information cannot be quickly and accurately transmitted to a production site in a traditional heat meter manufacturing process are solved.

1. Name of the product in this design: Intelligent Control Console (for training room use). 2. Purpose of this design: For teaching and demonstrating industrial software. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model. 5. The left view is the same as the right view, so the left view is omitted; the rear view is the same as the front view, so the rear view is omitted.

The application discloses an industrial scene-oriented low-code application construction method, system and product, and relates to the technical field of industrial software development. The method comprises the following steps: receiving a natural language business requirement description, performing semantic analysis and intention recognition by using an industrial vertical large model engine, and automatically generating an adaptive basic system template; responding to a user's drag operation in a visual configuration interface, configuring a business form and a production process by using a form engine and a process engine, and generating a customized industrial application system; establishing a communication connection with a physical device by configuring a device access protocol through an Internet of Things engine, and constructing a digital twin model to map real-time operation data of the device; after starting the system, collecting production data and business data, analyzing the data by using the industrial vertical large model engine, and generating optimization suggestions or early warning information. The application can shorten the industrial software development cycle, realize flexible adaptation and seamless integration of devices in complex industrial scenes, and improve the intelligent level.

This application provides a method for generating an embedded instrument display settings interface, an embedded instrument, a product, and a medium, relating to the field of display technology in industrial software. The model layer generates a linked list structure to manage menus and pages; the controller layer parses key events into logical instructions; the model layer updates IDs and retrieves page information accordingly; and the view layer fills display units to complete the interface refresh. Each layer has clearly defined responsibilities, separating data, logic, and display. Modifying a page only requires adjusting the content of the corresponding layer, without affecting other parts. This avoids high code coupling, reduces the workload and error rate for developers in identifying relationships and modifying code, improves development efficiency, enhances the flexibility and maintainability of interface development, and achieves system-level optimization.

The application discloses a kind of double-layer adaptive evolution CAD modeling command generation methods based on heterogeneous fuzzy and game, belong to artificial intelligence and computer aided design intelligent modeling technical field.This method solves the technical problems of fuzzy semantics difficult to be quantified in existing natural language driven CAD command generation technology Mapping, heterogeneous command poor adaptability, low command executable generated and reasoning process "black box" technology.This method constructs semantic analysis-game generation-evolution refinement-verification backtracking-knowledge precipitation whole-process closed-loop architecture, the application can be applied to industrial software, three-dimensional modeling, intelligent design system and other fields, improves the engineering executable of command generation, generalization ability and reasoning explainability, balances the generation diversity and feasibility, reduces model iteration cost, provides technical support for text-driven CAD modeling technology industrialization landing.

The invention discloses a steel wire rope tension acquisition system which comprises automatic steel wire rope tension balancing suspension devices and a high-speed pressure transmitter, a tension balancing oil cylinder is arranged in each automatic steel wire rope tension balancing suspension device, and a plurality of tension balancing oil cylinders are connected with high-pressure rubber pipes. The plurality of high-pressure rubber hoses are connected with the connecting pipes to form a closed loop; the high-speed pressure transmitters are connected to all the high-pressure rubber hoses, the multiple high-speed pressure transmitters are connected with the industrial computer, and the model of the high-speed pressure transmitters is Germany Weika S-20; a high-speed pressure transmitter is adopted to measure the pressure of a balance oil cylinder of each rope of the lifting steel wire rope of the multi-rope friction type lifting machine and collect data in real time, the data is subjected to graphical processing through special industrial software, a roller gasket is corrected according to a graph, and the pressure of the balance oil cylinder is measured. Therefore, the purpose that the difference between the tension of any steel wire rope for multi-rope lifting and the average tension does not exceed + / -10% is achieved.

The invention relates to a dynamic resource management method and device oriented to industrial software. The method comprises the steps that configuration loop information and system hardware resource information of an industrial site are collected; based on the configuration loop information and the system hardware resource information, through a pre-trained prediction model, generating a memory demand prediction value and a CPU core number configuration suggestion in a period of time in the future; according to the memory demand prediction value and the CPU core number configuration suggestion, the memory allocation and CPU resource utilization strategy of the industrial software is dynamically adjusted, so that the future resource demand can be predicted based on the configuration loop information and the system hardware resource information of the industrial site, and the prospective resource allocation is carried out according to the future resource demand, so that the service stability of the software is guaranteed, and the resource utilization rate is improved. And the resource utilization efficiency is maximized.

The present application relates to the technical field of intelligent and industrial software, and particularly relates to a method and system for collaborative design and programming of a radio frequency circuit based on artificial intelligence, which comprises: generating an initial schematic diagram and code; training a circuit generation model; predicting candidate code segments; simulating and screening admitted segments; displaying the admitted segments and counting the operation frequency; adjusting the model based on the operation; and iteratively generating a target until the target is generated, wherein the design indicators are closely combined with the initial circuit schematic diagram and the structured code, the circuit generation model is trained using preprocessed data, intelligent prediction of the radio frequency circuit code segments is realized, high-quality code segments are dynamically screened in combination with the performance simulation results, and an adaptive feedback mechanism is formed based on the drag frequency and parameter modification frequency data in the user interaction. The present application effectively solves the problem of low design efficiency and high error rate caused by weak generalization ability of the circuit design result due to static training of the model and lack of performance closed-loop verification.