216 results about "Digital transformation" patented technology

The invention discloses an electromagnetic transient simulation and mapping method and system oriented to multi-physics field coupling, and belongs to the technical field of substation digital operation and maintenance and electromagnetic simulation. Deploying multiple types of sensors in a transformer substation, preprocessing the acquired multi-physical field data, and fusing with the three-dimensional twinborn model; a coupling algorithm is adopted to carry out multi-physical field coupling analysis, multi-physical quantity display and thermodynamic diagram superposition are realized, and scene evolution change simulation under various typical working conditions is supported; a micro-service architecture is adopted to construct a digital twin system, double closed-loop verification of simulation and actual measurement is performed through actual measurement data and simulation data of a real-model test field, model optimization is completed, and real-time mapping of electromagnetic transient dynamic simulation and a transformer substation physical entity is realized. The method improves the precision of model and entity mapping, meets the requirements of real-time tracking and response of the electromagnetic transient change of the transformer substation, adapts to the digital transformation of different transformer substations, and provides a basis for the operation and maintenance of the transformer substations.

The invention provides a small and medium-sized enterprise digital transformation intelligent question answering method and device, equipment and a storage medium, and the method comprises the steps: carrying out the semantic recognition and entity extraction of a question input by a user, and generating a question semantic vector; retrieving a corresponding target text fragment in a preset vector database according to the question semantic vector; searching a sub-graph structure associated with the question semantic vector in a preset knowledge graph according to the target entity of the question semantic vector; reordering the text segments and the sub-graph structures based on correlation scores to obtain an ordering result set; and inputting the sorting result set into a retrieval enhancement generation model, and generating question and answer output content. Through the implementation of the scheme of the application, association matching of question semantics and enterprise knowledge can be realized by utilizing the text semantic information and the knowledge graph structure information at the same time in the question and answer generation process, the consistency of question and answer contents in logic structure and semantics is ensured, and the accuracy of digital transformation question and answer of small and medium-sized enterprises is improved.

The invention provides a planning analysis workflow intelligent arrangement method and device based on a natural language instruction, and the method and device can deeply understand the complex analysis intention of a plan in a natural language through a mixed analysis engine comprising a large-scale language model and a named entity recognition model. And according to the understood intention, a proper operator and a proper model are autonomously selected from a tool library in combination with a planning analysis knowledge graph, so that a complete, logic self-consistent and executable multi-step analysis workflow can be autonomously and dynamically arranged, the workflow is automatically executed, and multi-modal data is collected. According to the method and the device, the technical problems in multiple aspects from keyword matching to composite intention deep understanding, from artificial process design to knowledge-driven intelligent arrangement and from one-way instruction execution to interactive exploration analysis in the prior art are solved, and the method and the device have the advantages that the technical problems in multiple aspects from keyword matching to composite intention deep understanding, from artificial process design to knowledge-driven intelligent arrangement and from one-way instruction execution to interactive exploration analysis are solved; the planning work efficiency can be improved, the technical threshold is reduced, and industry digital transformation is promoted.

The invention provides a BIM-based 3D building digital monitoring method and system, and belongs to the technical field of building engineering monitoring, and the method comprises the steps: carrying out the digital conversion and processing of a building design drawing of a target building, extracting the geometric and attribute information of the target building, and generating a standard BIM model; verifying and calibrating the basic multi-dimensional data and the standard BIM model when the target building is completed, and generating a reference BIM model; performing spatial registration and association mapping on the acquired multi-dimensional monitoring data and the reference BIM model to generate an association data set; comparing based on the associated data set to generate a comparison result; obtaining a potential risk type and a risk evolution trend of the target building through a risk prediction model based on a comparison result, historical monitoring data and a component static attribute in the reference BIM model; and generating a target monitoring strategy based on the potential risk type and the risk evolution trend. The building operation and maintenance efficiency is improved, and the service life of the building is prolonged.

The invention provides a BIM (Building Information Modeling) full life cycle splitting and cross-model synchronization method and system. The method comprises the steps that BIM model components are coded based on a full life cycle coding rule, private attributes of all engineering stages and component codes of the engineering stages are bound and stored in component extension attributes, and a BIM master model containing multi-stage attribute information is generated; setting a BIM model splitting rule based on a rule engine; the code of each component in the BIM model is analyzed, the codes are compared with screening conditions in the splitting rules according to levels, and component data corresponding to the successfully matched codes are packaged and stored as sub-models; establishing association mapping between the models; and when the source model is modified, the synchronization engine executes synchronous updating of the target model according to the association mapping between the source model and the target model associated with the source model, so that the cross-stage multi-participant cooperation efficiency is improved, and a solid technical support is provided for digital transformation of the construction industry.

The invention relates to an unmanned aerial vehicle automatic intelligent inspection method and system, and relates to the technical field of unmanned aerial vehicle inspection. A real-time environment sensing technology is adopted, environment data such as wind speed and temperature are dynamically collected, and accurate power consumption calculation is performed through a dynamic electric quantity model optimized by machine learning; and an intelligent decision algorithm is integrated to realize self-adaptive task planning, multi-unit network coordination, dynamic return point selection and automatic landing, so that a'perception-decision-execution 'closed-loop intelligent system is constructed. According to the scheme, the operation reliability and safety of the unmanned aerial vehicle in a complex environment are remarkably improved, manual intervention is greatly reduced, full-automatic efficient operation and maintenance are achieved, the inspection efficiency is comprehensively improved, the intelligent inspection requirements of multiple fields such as electric power, forestry and emergency are met, and digital transformation of infrastructure management is enabled.

The invention discloses a method for generating a text system, and aims to solve the problems of long development cycle, disjunction of requirements and technology implementation and the like of traditional software and realize automatic generation from a natural language requirement to a deployable service system based on a large language model. The method is divided into two stages: in the first stage, a system is disassembled into a logic subsystem through man-machine cooperation, core business logic is extracted, a large language model is called by adopting a divide-and-conquer strategy, and a detailed specification containing a functional process and an interface form is generated; in the second stage, a large language model is called to generate a database table structure and a DDL script, an engineering framework of a basic technology stack is initialized and integrated through a predefined scaffold, CRUD codes are generated, the codes are analyzed to generate a transformation plan for structured data, and target logic codes are incrementally integrated. According to the method, control is achieved through Python, the problem of large model input limitation is solved, and generated codes are standard and extensible. The development cycle is shortened, the requirement-design-code consistency is guaranteed, the threshold is lowered, platform locking is avoided, and enterprise digital transformation is assisted.

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 relates to a CNC machining material unified management system based on intelligent early warning and multi-dimensional fusion, and belongs to the technical field of intelligent manufacturing and industrial informatization. The invention aims to solve the technical challenges in the existing CNC processing material management. The system adopts a three-layer architecture, comprises a data layer, a business logic layer and an application layer, and realizes the functions of unified modeling, classified management, batch tracking, inventory early warning and the like of material data. Through the intelligent tool breakage prediction module, the two-stage position management module, the intelligent inventory prediction module and the like, the system can automatically identify tool breakage abnormity, optimize the storage position, predict the inventory depletion date and generate intelligent replenishment suggestions. The system improves the management efficiency, reduces the inventory cost and the stockout risk, is suitable for the fields of intelligent manufacturing and industrial informatization, and meets the requirements of digital transformation of enterprises.

The invention discloses a knowledge graph-based asset digital twin management platform data encryption method, which comprises the following steps of: determining a digital data storage position, constructing a data management knowledge graph, and performing dynamic attribute-based encryption on graph nodes according to a graph structure and an edge relation weight of the data management knowledge graph to obtain first encrypted data, and determining the data quality grade of the operation information in the platform database according to the operation access information and the statistical data, performing hierarchical encryption on the operation information in the platform database in combination with the data attribute to obtain second encrypted data, and performing dynamic searchable symmetric encryption on the second encrypted data according to the time sequence information to obtain third encrypted data. According to the method, encryption granularity can be refined from a'library level 'to a'node-edge-time sequence point level', online matching of security strength, data value and real-time requirements is realized, decryption overhead in a high-performance computing scene can be reduced, and the method has great significance in promotion of industrial digital transformation.

The invention provides an electric power marketing service event risk hierarchical identification method and system based on knowledge graph semantic modeling, belongs to the technical field of electric power marketing service event risk identification, and solves the problems of data islanding, semantic understanding deviation, poor scene adaptation and high manual dependence in the prior art. According to the technical scheme, the method comprises the steps that multi-source data including 95598 appeals, electric vehicle charging / live broadcast electricity utilization and the like are collected, a knowledge graph with entity links is constructed, and risk identification is achieved through hierarchical semantic modeling, three-level risk identification and dynamic optimization. According to the method, the data association rate and the risk identification precision can be improved, the enterprise operation cost is reduced, and the digital transformation of enterprise power marketing is promoted.

The invention discloses an enterprise digital transformation effect intelligent evaluation system based on multi-modal data fusion, particularly relates to the field of enterprise management and data analysis, and is used for solving the problems of conclusion drift and vacancy of a recheck chain caused by caliber adjustment and evidence deficiency in an existing evaluation scheme. A mapping windowing module establishes mapping from an intervention event number to an object instance identifier and defines an event window, and an evidence entry module generates an evidence entry in the event window, adds an identifier and writes the evidence entry into an evidence account. The recalculation judgment module executes caliber contrast marking and calculates influence intensity and consensus degree synthesis playback trigger value to determine a recalculation range output conclusion, and the check write-back module reads subsequent check results, revises window boundaries and rules and writes the window boundaries and rules into a version management table to drive the next period, so that unified anchoring and dynamic recalculation of multi-source evidences are realized. And the traceability and consistency of evaluation are ensured.

The invention belongs to the technical field of oxygen content detection and dynamic calibration, and particularly relates to a dynamic calibration method for the oxygen content in a boiler air and flue gas system. The method comprises the steps of multi-working-condition data acquisition and standardization processing, failure feature extraction and feature library establishment, reference oxygen calculation model construction, data driving model construction, anomaly detection and calibration, parameter self-updating and the like, and a calibration effect real-time evaluation link is newly added. The core of the method is that a mechanism + data dual-drive mode is adopted, a reference model is constructed on the basis of a zirconia sensor Nernst equation, an improved bidirectional LSTM network is fused to construct a data drive model, and an adaptive threshold algorithm and a multi-stage calibration strategy are combined to realize accurate recognition and dynamic calibration of abnormal signals. The method is adaptive to a complex flue gas environment and a variable load operation scene, the oxygen content measurement precision is remarkably improved, low-nitrogen combustion and environmental protection compliance are guaranteed, coal consumption and operation cost are reduced, and reliable data support is provided for intelligent power plant digital transformation.

The invention discloses an intelligent substation secondary equipment remote operation and maintenance method and system, and relates to the technical field of power system automation. According to the method, an integrated remote operation and maintenance system is constructed by deploying an intelligent remote operation platform at a master station end and deploying a secondary equipment intelligent terminal at a station end. The system automatically configures communication based on an SCD file, and acquires operation data of secondary equipment of the whole station; and the master station subscribes data as required, so that hierarchical and scenarized panoramic monitoring is realized. Three independent channels of operation and maintenance management, remote operation and maintenance and data acquisition are set, and white list, work order approval and SM2 / SM4 encryption authentication strategies are adopted, so that four types of remote operation of pressing plate operation, fixed value operation, device resetting and equipment emergency operation are safely realized. According to the method, the problems of low efficiency and high safety risk of a traditional on-site operation and maintenance mode are solved, the operation and maintenance quality is improved, and digital transformation of operation and maintenance of the secondary equipment of the transformer substation is promoted.

The invention discloses an explosion view and fault positioning method and system based on drag-and-drop configuration of digital twin equipment component coordinates, and relates to the technical field of industrial digitization and equipment intelligent operation and maintenance. Through a series of technical innovations such as integration of a high-precision model, drag-and-drop configuration, data linkage and interactive query, an equipment digital twin operation and maintenance system which is efficient in development, accurate in positioning and intelligent in interaction is constructed, and finally normal form transformation of equipment operation and maintenance from experience driving to data and visualization driving is achieved. And a key technical support is provided for digital transformation in the industrial field.

This invention relates to the field of multimedia data processing, and discloses a multimedia end-to-end optical-digital collaborative processing system and method, including an optical correction device, a discretization encoding device, and a synchronous playback device. The optical correction device monitors the status of the physical execution module, calculates the digital transformation matrix and physical limit markers, encapsulates them as correction metadata, and outputs it synchronously. The discretization encoding device extracts images based on differences between adjacent frames to generate discrete visual sequences, uses synchronization pulse markers in the audio stream to perform spatiotemporal mapping on the discrete data, and encapsulates it as a multimedia file for output. The synchronous playback device parses the file, extracts the synchronization pulse markers as a global clock to calculate timing deviations, performs rendering compensation based on the physical limit markers, and generates a reverse feedback signal based on the timing deviations, sending it to the front end to trigger closed-loop adjustment. This invention solves the problems of rendering misalignment and multi-track timing deviation accumulation caused by physical truncation, maintaining end-to-end stability.

The invention provides a tool, method and product for standardized drawing of territorial space detailed planning achievements, and belongs to the technical field of territorial space planning drawing, and the tool comprises a standardized file module which is used for establishing a standardized control and regulation achievement file layer system and generating a standardized control and regulation achievement file; the splitting module is used for splitting the standardized control and regulation result file according to a planning unit range to obtain a split unit file; the extraction module is used for automatically extracting information in the control and regulation achievements according to the split unit files; the map table module is used for generating a map table and presenting various indexes and information of the regulation and control achievement; and the map module is used for generating standardized planning maps in batches through an automatic process. The method can efficiently and accurately complete the standard drawing of the territorial space planning result, improves the intelligent level of planning, and accelerates the promotion of the digital transformation of planning.

The invention relates to an adjustable potential analysis method for adjustable load resources in a building park. The method comprises the following steps: constructing an adjustable load resource adjustment power model in the building park; calculating the dynamic carbon emission of the adjustable load resource; establishing an adjustable load resource multi-target aggregation model; and calculating the comprehensive adjustment potential of the adjustable load resources in the building park. The low-carbon contribution of each adjustment behavior of the park is accurately quantified, and the load resources are promoted to be upgraded from one-way economic response to multi-dimensional collaborative response; the accuracy and credibility of potential evaluation are remarkably improved, the problem of deviation caused by extensive aggregation is solved, and a reliable data basis is provided for power grid demand response and marketization transaction; a key decision basis is provided for the park to participate in power grid interaction, the transformation of the building park to a flexible resource polymer is powerfully promoted on the premise of ensuring the safety and comfort of energy consumption, and a solid support is provided for the construction of a novel power system and the digital transformation of park energy.

The invention relates to the technical field of industrial internet and digital transformation, and discloses a modular digital technology deployment system and method based on dynamic adaptation, and the system comprises a data collection layer, an edge calculation layer, a dynamic adaptation module library and a cloud platform layer, the data collection layer is in communication connection with the edge calculation layer, and the edge calculation layer is in communication connection with the dynamic adaptation module library. The edge computing layer is in two-way communication with the dynamic adaptation module library, and the dynamic adaptation module library is in two-way communication with the cloud platform layer; the data acquisition layer is used for acquiring production data in real time and preprocessing the production data; and the edge calculation layer is used for deploying a lightweight algorithm to execute a local real-time decision. On-demand calling and combination of technical components are realized by constructing a dynamic adaptation module library, and in combination with an edge-cloud collaborative optimization mechanism, the problems of resource waste and insufficient real-time performance in a traditional architecture are effectively solved. Wherein the dynamic adaptation algorithm dynamically generates an optimal module combination scheme based on a fuzzy entropy evaluation model, and the edge layer lightweight algorithm ensures that local real-time decision response delay is remarkably reduced.

This application pertains to the technical field of enterprise data analysis and provides a method and system for constructing a risk prevention and control system based on enterprise digital transformation. The method involves first acquiring multiple access request information and access permission information, then generating authentication result information based on this. If the total number of authentication failures exceeds a conventional threshold, risk event information is generated. This application can promptly detect abnormal behavior during monitoring periods, such as a large number of users attempting unauthorized access to the power supply bureau's core system data. It accurately identifies potential risk events such as privilege abuse, brute-force attacks, internal personnel violations, or external penetration attacks. It provides real-time alerts and decision support for security management personnel, facilitating rapid deployment of countermeasures and effectively preventing the leakage of sensitive electricity consumption information, power grid operating parameters, and user privacy data. This significantly enhances the reliability and proactive defense capabilities of the power supply bureau's data security risk prevention and control system.

The invention relates to a power distribution network project whole-process technical-economic intelligent management method and system based on artificial intelligence and big data, and a medium. The system comprises a dynamic technical-economic knowledge base module which automatically repairs and compiles a typical cost base and automatically and dynamically updates knowledge base contents; the feasibility research initial intelligent review module is used for verifying the integrity of the design file and estimating or roughly calculating the compliance of the file, the quota application accuracy and the probability exceeding risk through a knowledge base, and generating a structured review report; the settlement intelligent review module is used for identifying material quantity deviation and price abnormity; and the closed loop feedback and optimization module forms a'typical problem library iteration-review auxiliary optimization 'closed loop. According to the method, the data barrier of a department is broken, the review process is promoted to be converted from manual spot check to intelligent full coverage, the review quit rate and the review subtraction rate are remarkably reduced, the investment balance rate is optimized, the material balance efficiency is improved, standardized and extensible intelligent support is provided for technical and economic management of a power distribution network project, and digital transformation of the power industry is assisted.

This invention provides a digitally intelligent multi-terminal device collaborative unmanned self-service hotel system, comprising: an access control terminal integrating a multimodal information collection unit, which classifies visitor types into guests, authorized visitors, service personnel, and unauthorized personnel according to preset classification rules, and generates encrypted electronic vouchers with attribute tags; based on the attribute tags of the electronic vouchers, it opens exclusive service ports according to visitor type; it generates dynamic and time-limited access vouchers for authorized visitors and service personnel; and it uses intelligent monitoring equipment deployed in the hotel's public areas to perform visual recognition and trajectory tracking of unauthorized personnel. This invention simplifies the overall hotel management process and achieves a comprehensive improvement in operational efficiency, security, and customer experience through intelligent and unmanned design, providing reliable technical support for the digital transformation of the hotel industry and possessing significant practical application value.

The invention discloses a precise generation and computing power cooperation technology based on an AIGC platform, and relates to the technical field of AI application in the building industry. According to the technology, by constructing an enterprise-level AI comprehensive platform integrating an AI technology forum, an AI tool resource library, a computing power dynamic scheduling module and a multi-level authority control module, the problems of resource dispersion, uneven computing power, extensive authority and low knowledge sharing efficiency are solved. The core of the method comprises the following steps: realizing three functions of creative oasis, model ocean and inspiration sky, and supporting picture uploading, AI same-style generation, model management and text drawing operation; a reinforcement learning-based computing power dynamic scheduling algorithm is adopted to intelligently allocate computing power resources; and designing a three-dimensional permission cube model to realize refined permission control of roles, scenes and operations. According to the method, the resource searching efficiency can be improved by more than 60%, the hardware resource utilization rate can be increased to 85%, the enterprise cost is effectively reduced, the data safety is guaranteed, and large-scale collaboration and digital transformation of AI application in the building industry are promoted.

The invention discloses a supply and service telephone voice analysis and work order whole-process intelligent circulation method, which comprises the following steps of S1, converting dialect voice of a user into a standard text in a high-precision manner by utilizing a high-precision dialect voice recognition model, and providing a reliable basis for subsequent processing; s2, intelligently identifying user appeal types by using the knowledge-enhanced brilliance large model, accurately extracting key information, and performing logic verification through a business rule engine to ensure that the information is accurate and compliant; s3, automatically matching a template according to the type, filling information, desensitizing sensitive data in real time, and finally automatically distributing the sensitive data to an execution unit through an encryption interface to realize full-process automatic closed loop; according to the method, the work order processing time can be greatly shortened, the labor cost is reduced, the fault processing accuracy and the service satisfaction degree can be improved, and core business support is provided for digital transformation of the state grid.

This invention discloses a method and system for monitoring industrial power consumption anomalies based on multi-source data fusion, belonging to the intersection of the Industrial Internet and smart grids. It solves the problems of false alarms, missed alarms, and inability to identify hidden anomalies in traditional monitoring systems. The method includes holographic acquisition of multi-source heterogeneous data on power parameters, production conditions, and environmental status; spatiotemporal alignment and preprocessing; fusion calculation of real-time anomaly scores and dynamic thresholds corrected for operating conditions and environment; and continuous verification followed by graded anomaly determination based on relative deviation, enabling early warning and fault alarms. The system includes acquisition, preprocessing, dynamic threshold calculation, and determination units. This invention achieves adaptive dynamic monitoring based on operating conditions and environment, accurately distinguishes between normal fluctuations and faults, captures hidden anomalies, has low deployment costs, and is suitable for industrial digital transformation.

This application relates to a method and apparatus for digital transformation of ODN facilities. The method includes: obtaining a character array of box names and a character array of port names based on an actual box image; identifying the box under maintenance and installing box tags and fiber optic cable segment tags directly connected to the box; obtaining a port status array based on a box image after all fiber optic cable segment tags have been installed; locating and identifying each installed fiber optic cable segment tag, and obtaining a port name-bound tag object array based on the located and identified box image, port name character array, and port status array; constructing a meter-length pairing structure object array between box ports based on the meter-scale image of the fiber optic cable segment; and constructing a tag pairing relationship between box ports based on the box topology connection table, the meter-length pairing structure object array between box ports, and the port name-bound tag object array. This application allows a single person to quickly assemble tags for boxes or fiber optic cable segments and complete the digital transformation, with high efficiency and low construction difficulty.

The invention discloses a green digital high-voltage-class current transformer design method and a current transformer, and the design method comprises the steps: deducing a measurement error theoretical calculation formula of the current transformer, and determining the relation between digital load output and an electromagnetic unit according to the measurement error theoretical calculation formula; determining a secondary side rated capacity value according to digital load output requirements; determining parameters of an electromagnetic unit and an electromagnetic winding by combining a measurement error theoretical calculation formula of the current transformer and a relation between digital load output and the electromagnetic unit; the measurement error of the current transformer obtained through design is verified; if the verification is passed, the structure composition of an electromagnetic unit and an electromagnetic winding of the current transformer is completed, and non-SF6 insulating gas is adopted. Current measurement is achieved at the secondary side output end of the current transformer, the digital load output requirement is met, and digital transformation is promoted; and meanwhile, theoretical support is provided for large-scale application of clean air in measuring equipment insulating media and green development of high-voltage metering equipment.

The invention discloses a power customer demand prediction method and system based on deep learning, and relates to the technical field of power system operation and power service intellectualization, and the method comprises the following steps: constructing a customer side equipment-behavior mutual identification decoding module, a power grid side constraint dynamic feedback module and a three-dimensional symbiosis prediction module; according to the invention, through the client-side equipment-behavior mutual identification decoding module, the demand essence is accurately identified, a three-dimensional scene gene label containing the equipment state, the behavior intention and the like is output, and demand misjudgment is avoided; through a power grid side constraint dynamic feedback module, a power grid bearing capacity dynamic curve and a constraint transfer suggestion are automatically generated, and the feasibility of a prediction result is guaranteed; a client side and power grid side double data link bidirectional interaction closed loop is constructed, self-iteration reinforcement learning of a three-dimensional symbiotic prediction module is combined, an isolated analysis framework is broken, collaborative decision is realized to support electric power service digital transformation, and meanwhile, an equipment hidden fault early warning function is derived.

This invention discloses a knowledge graph-based method for identifying enterprise digital transformation needs. It constructs a multi-dimensional business operation knowledge graph; extracts a semantic subgraph representing pain point obstacles in enterprise business flow; constructs a high-order semantic representation matrix of pain points; extracts a set of corresponding matching candidate digital transformation need nodes; obtains a comprehensive need feature graph; and generates a set of target digital transformation need paths with a quantified execution priority sequence. This invention ensures the establishment of a globally optimal mapping relationship with extremely high confidence between different modal features, significantly improving the fusion depth and lossless alignment capability of underlying business data.