180 results about "Real-time database" patented technology

A system for multi-stage planning of construction processes and resource allocation, consisting of: a central planning engine configured to receive input data, including architectural design models, structural constraints, procurement schedules, and historical performance indicators; a task decomposition processor that is operationally connected to the central planning engine and configured to generate a hierarchical construction task graph by decomposing macro-level construction milestones into mid-level and micro-level subtasks, with each subtask having time estimates, location identifiers, resource requirements, and mutual dependencies; a hybrid planning processing unit configured to resolve time and resource constraints across the entire task diagram; a resource coordination controller that is operationally connected to the central planning engine, wherein the resource coordination controller includes a real-time database of work units, machines and material stocks, each resource being tagged with attributes such as availability, usage history, operating status and spatial location; a multitude of distributed execution units distributed across the construction zones, each distributed execution unit comprising an embedded controller, sensor interfaces, task status processing logic, and communication circuitry, each distributed execution unit being configured to receive planning instructions from the central planning machine, execute localized control logic for task confirmation and resource activation, and transmit task execution data back to the central planning machine; an adaptive conflict resolution processing unit that is operationally connected to the central planning engine and configured to detect conflicts in task execution or resource conflicts, simulate alternative task-resource allocation scenarios using a real-time multi-agent model, and autonomously update the task graph with revised task sequences and resource allocations; and A dashboard for the construction process, configured to visualize task progress, deviations from the planned schedule, and resource efficiency metrics, with the dashboard also being able to receive manual override inputs or approve automated conflict resolution proposals generated by the adaptive conflict resolution module.

An intelligent monitoring, inversion and prediction system for a transient process of pumped storage units is provided, including: an equipment layer including sensors for obtaining hydraulic, mechanical and electrical operation data of the pumped storage units in real time, a data layer including a real-time database, a relational database, an expert knowledge base and a file system and used for storing hydraulic, mechanical and electrical operation parameters collected by the equipment layer in different levels, a twin layer including a modeling and an application of a digital twin model and used for a three-dimensional modeling and a key information visual display of a pumped storage system with BIM technology and a service layer displaying one-dimensional time domain parameters and designing and visualizing front-end interfaces for six functions: operation optimization, online monitoring, inversion, dynamic prediction, health assessment and fault warning.

The invention discloses an urban road mobile source intelligent monitoring method and system based on multi-source data coupling, and relates to the technical field of environment monitoring and intelligent traffic. Utilizing a machine learning algorithm to construct a pollutant emission, carbon emission and energy consumption prediction model; acquiring vehicle inventory data in the city, and calculating the pollutant emission, energy consumption and carbon emission of the whole city; the method comprises the following steps of: constructing a dynamic distribution diagram of automobile emission in a city by using real-time position data of vehicles and urban road network information, introducing an atmospheric diffusion model, simulating pollutant migration by combining urban geographic information and environmental data, comparing and verifying a simulated migration result with actually measured data of a national control site, and optimizing parameters of the atmospheric diffusion model; and storing the result into a real-time database, and displaying the pollutant distribution, emission, energy consumption and carbon emission of the urban road network in real time through a visual interface. According to the invention, the temporal-spatial resolution and prediction precision of data are effectively improved.

The invention discloses a fire-fighting monitoring and generator set collaborative optimization multi-target constraint solving method, which comprises the following steps: carrying out real-time acquisition and structured processing on multi-source data, acquiring safety monitoring and equipment operation data through a sensor network, and storing the data in a distributed real-time database after preprocessing; carrying out dynamic thermodynamic field modeling and risk area division, discretizing a plant area as a grid unit, solving a heat conduction equation in combination with heat source modeling and boundary conditions, and dividing three levels of risk areas; building a multi-objective optimization model, defining three types of core constraints, building a normalized objective function, and realizing multi-objective decoupling through dynamic weight adjustment; according to an asymmetric load migration strategy, differential load adjustment is implemented according to an optimization result, an auxiliary system is linked, constraints are verified in real time, and closed-loop control is formed. According to the technology, the collaborative goals of safety risk controllability, system efficiency maintenance and equipment redundancy optimization are achieved, and the method is suitable for fire prevention and efficient operation in an energy production scene.

The invention relates to the technical field of industrial automation and intelligent manufacturing, and discloses an industrial big data simulation verification system based on digital twinning, and the system comprises a physical entity module which is used for deploying an industrial sensor array and collecting the real-time parameter data of production equipment; the digital twin mirror image module is linked with the physical entity module through a data mapping engine, and synchronously updates a virtual mirror image model at a millisecond level according to the parameter change of the physical entity; and the data transmission module is used for transmitting the data acquired by the physical entity module to the digital twin mirror image module and the multi-source data fusion module through a 5G or industrial Ethernet, and is used for cleaning the acquired multi-modal industrial data and eliminating noise data. Through the physical entity-digital twin mirror image real-time linkage design, the limitation that traditional simulation is disjointed with entities is broken through. The industrial sensor array is combined with the edge calculation module, so that rigid linkage of physical production equipment, a real-time database and a digital twin mirror image is realized.

The invention discloses a fire water tanker emergency intelligent scheduling method and system based on a cloud platform, and relates to the technical field of intelligent scheduling management. According to the method, based on a multi-dimensional real-time database constructed by a cloud platform, multi-disaster data and priority data in a to-be-dispatched vehicle data dynamic acquisition and classified storage process are acquired, and preliminary dispatching distribution of to-be-dispatched vehicles is synchronously completed, so that a dispatching response initial period is shortened; after preliminary scheduling distribution, candidate scheduling schemes are generated, and meanwhile, an optimal scheduling scheme is screened out so as to accurately match emergency requirements of each target area; after the optimal scheduling scheme is obtained, based on a received scheduling instruction, a driving route and task allocation are dynamically adjusted, and scheduling information is synchronously pushed to a command center and each task scheduling site, so that rescue delay caused by information lag is avoided. Full-process optimization of data processing, scheme screening and collaborative scheduling in a multi-disaster-situation concurrent scene is realized, so that the timeliness of emergency scheduling of the fire water tanker is effectively improved.

The invention relates to a battery database access system and method based on Dify and a large model question and answer mechanism, and the system comprises a front end interaction module which is responsible for carrying out information interaction with a user, receiving a natural language question of the user, and transmitting the question to a rear end for processing; the Dify agent management module is responsible for task distribution and user intention recognition; the Prompt generation and scheduling module is responsible for converting the user problem into a query request which can be understood and processed by the system; the database interface module is responsible for being connected with a new energy battery database; the large model generation module is used for generating natural language answers of the user questions through a large language model; and the context management module is responsible for storing and managing context information in multiple rounds of conversations. A user can intelligently interact with the new energy battery database through a natural language, and can easily and efficiently access information in the real-time database.

The invention discloses an atmospheric and vacuum distillation unit intelligent optimization method and system based on deep reinforcement learning, and relates to the field of oil refining and chemical engineering, and the method comprises the steps: collecting historical operation data from a distributed control unit and a real-time database of an atmospheric and vacuum distillation unit, and carrying out the preprocessing, and obtaining a preprocessed historical data set; constructing a process mechanism feature network through a graph neural network by using the preprocessed historical data set, mining an association relationship among equipment parts, extracting abstract features representing a process principle, and constructing a digital twin environment; in a digital twin environment, a meta-reinforcement learning algorithm is adopted to train a deep reinforcement learning agent, so that the deep reinforcement learning agent obtains meta-strategies adapted to different crude oil properties. According to the method, safe, stable and efficient intelligent optimization control is realized through a closed-loop operation mechanism of safe mirror image drilling and credibility driving, and the problem of optimization response lag caused by manual model adjustment due to crude oil property change in a traditional optimization technology is solved.

The invention provides a multi-energy collaborative optimization management system and method, and belongs to the technical field of collaborative optimization. The demand module is used for determining an energy object of the multi-energy collaborative optimization management system based on a target demand, and configuring a sensor to obtain real-time data of all energy types; the system design module is used for designing a multi-energy collaborative optimization management system architecture in a test environment and storing real-time data of all energy types into a real-time database; the algorithm module is used for configuring an initial model and training the initial model according to the real-time data of all the energy types and the historical data of the corresponding energy types to obtain a first model, and the first model is a system algorithm part; the packaging module is used for adding the main functions into the multi-energy collaborative optimization management system architecture to obtain a first system and packaging the first system to obtain a system packaging file; the resource efficiency is improved, the application of renewable energy sources is promoted, and the optimization improvement degree is enhanced.

The invention provides a current limiting management method, system and device applied to a real-time database and a medium, and the method comprises the steps: obtaining the performance index data of a database system and the application load information of each business process, training based on the historical performance index data and the application load information to obtain a prediction model used for predicting the working state of the database, predicting a database working state in a preset time window corresponding to the current data on the basis of the prediction model so as to perform flow limiting management on a plurality of service processes corresponding to the current application load information on the basis of a prediction result; according to the method, the current service processes are subjected to current limiting management by predicting the future working state, so that the important service processes are guaranteed to be smoothly realized, and a more stable, efficient and easy-to-maintain database environment is provided for a user through intelligent management and resource optimization.

The present invention provides a method and system for model management and collaborative analysis based on digital twin, including: Step S1: Construct a digital twin 3D model of a target object; Step S2: Collect the point position data of the target object at a fixed frequency and store it in the IHD real-time database; Step S3: Construct different business models, including: a data model and a rule model; Step S4: Select a business model according to requirements and calculate corresponding business indicators based on the point position data in the IHD real-time database; Step S5: Push the calculated business indicators to the digital twin 3D model; Step S6: The digital twin 3D model restores the inherent attributes of the target object based on the collected point position data of the target object and the received business indicators; The present invention provides a unified digital twin model management and collaborative analysis framework for complex industrial systems, aiming to solve the problems of heterogeneous complexity of tasks, dynamic changes in the environment, and real-time interaction existing in digital twin currently.

The invention relates to a dynamic intelligent stamping production line real-time monitoring strategy based on digital twinning, and adopts the technical scheme that a sensing layer acquires production total factor data related to a stamping production line in real time through multi-sensor fusion and an RFID (Radio Frequency Identification) technology, performs primary processing by utilizing edge calculation, and transmits the data to a real-time reaction layer; the real-time reaction layer quickly processes and analyzes multi-source data through edge calculation and a real-time database, detects faults in real time by using a multi-modal fusion technology, triggers an alarm mechanism, and feeds back to the interaction layer; and the interaction layer integrates intelligent production scheduling and NLP voice interaction through data interaction processing, error verification and multi-protocol adaptation to realize virtual factory visualization and equipment health real-time monitoring. Multi-modal data fusion is realized, an adaptive incremental learning and early warning mechanism is realized, an information island is broken, and millisecond-level response is realized. The strategy can improve the production efficiency, reduce the operation and maintenance cost, prolong the service life of equipment, and provide an efficient solution for intelligent transformation of the manufacturing industry.

The invention relates to the technical field of distributed database optimization, and discloses a real-time database distributed query optimization method based on memory computing, comprising the following steps: modeling query delays, the query delays comprising computing delays and communication delays; and based on the modeling result of the query delay, the query progress and the resource allocation strategy of each node are determined, each node is a single calculation unit in the distributed database, the calculation delay of the node is inversely proportional to the resource allocation and query load of the node, and the communication delay between the nodes is determined by the data transmission quantity and the bandwidth between the nodes. Through an optimal control theory, a game theory model and a self-adaptive control mechanism, dynamic allocation of calculation and communication resources, collaborative optimization of resources among nodes, self-adaptive adjustment of query loads and resource scheduling optimization driven by historical data are realized, the query execution efficiency is effectively improved, and the overall query delay is reduced.

The invention relates to the technical field of hydropower station intelligent regulation and control, and discloses a hydropower station multi-system intelligent linkage method, system and device and a medium. The method comprises the following steps: deploying sensors at key nodes of a plurality of subsystems in a hydropower station, constructing a distributed sensor network based on all the sensors, establishing a real-time database, then constructing opportunity constraint conditions for processing non-Gaussian disturbance in the subsystems, and converting the opportunity constraint conditions into CVaR-based deterministic constraints; according to the information of the whole system of the hydropower station, an optimization problem meeting deterministic constraints is constructed, and the optimization objective is to minimize the control deviation of the whole system of the hydropower station; obtaining an optimization result of the optimization problem based on an iterative solution algorithm of an interior point method; according to an optimization result, key control parameters in the corresponding subsystems are determined, and then a multi-system cooperative control strategy is generated; and executing intelligent regulation and control on the hydropower station based on a multi-system cooperative control strategy. The method realizes intelligent linkage regulation and control of multiple systems of the hydropower station.

The invention discloses a vertical field fine tuning optimization method based on a large model and a strip mine intelligent system, and relates to the technical field of artificial intelligence. The vertical field fine-tuning optimization method based on the large model comprises the following steps: acquiring original data of one or more data sources, and performing data distillation on the original data to construct an industry high-quality data set; determining a pre-trained large language model according to the industry scene; the large language model is continuously trained using the industry high quality data set to lightly trim the large language model and generate an industry large model. The industrial normative file is segmented into semantic paragraphs, vector embedding corresponding to each semantic paragraph is generated, and the vector embedding is stored in a real-time database; and retrieving information related to the query of the industry large model in a real-time database to enhance the output response of the industry large model. By adopting the technical scheme of the invention, the adaptation degree of intelligent deployment and control of strip mine mining is improved.

An intelligent associated hydropower station one-stop cockpit comprehensive management and control method realizes efficient comprehensive management and control of a hydropower station through four methods of exception handling comprehensive information management, cockpit large-screen information flow switching, large-screen switching page management and control and multi-source data fusion. According to the exception handling comprehensive information management method, exception handling cards are managed through a dynamic configuration algorithm, and quick response and accurate handling are ensured; according to the cockpit large-screen information flow switching method, a flexible display mode is supported through stable network connection and safe video flow transmission; according to the large-screen switching page management and control method, timely transmission of key information is ensured through real-time monitoring and an intelligent screen switching strategy; according to the multi-source data fusion method, comprehensive management and fine control of data are realized through combination of a real-time database and a historical database. Through the construction and management of the five databases, the fine management and automatic control capability of the playing content is further improved, and the efficient operation and safety of the system are ensured.

The invention provides a distributed storage method and system of a real-time database, electronic equipment and a storage medium, and relates to the technical field of power grid dispatching automation systems. The distributed storage method of the real-time database comprises the following steps: constructing the real-time database according to an electric power public information model of a monitored power grid; setting a plurality of fragments for storing data in the plurality of physical nodes; the first content in the real-time database is stored in the corresponding fragment in the multiple fragments in a fragment storage mode; respectively storing the second content in the real-time database into a plurality of fragments in a copy storage mode; and storing the third content in the real-time database into the first fragment in the plurality of fragments in a centralized storage manner. While the data fragmentation is realized, the local integrity of the on-chip power grid model is maintained, and the on-chip application can still perform efficient processing in a local shared memory mapping file mode based on the fragmentation.

The invention relates to the technical field of Internet of Things and water conservancy informatization, and discloses a water conservancy Internet of Things system and a control method thereof, and the system comprises an Internet of Things management platform, a business system, a water conservancy intelligent device, and a message queue service, a real-time database, a real-time monitoring system and an Internet of Things gateway which are in communication connection with the Internet of Things management platform. The business system is in communication connection with the real-time monitoring system and the message queue service, the real-time monitoring system is in communication connection with the message queue service, and the water conservancy intelligent equipment is in communication connection with the Internet of Things gateway. The problems of poor compatibility and the like in the prior art are solved. Through the cooperation of the protocol conversion service and the Internet of Things gateway, the plug-and-play of more than 90% of industrial equipment in an irrigation area is supported; the message queue service is combined with the MQTT protocol, so that the end-to-end delay is reduced to be less than 50ms; based on strategy optimization of data driving, manual intervention is reduced, and the scheduling efficiency is improved by more than 30%.

The invention discloses a real-time evaluation method and system for power production data quality, and belongs to the technical field of power generation industry data security. Classified data quality measurement points and overall data quality measurement points are created in a real-time database according to the types of measurement points in an I / O (input / output) list of a power production monitoring system; an evaluation rule is established on the basis of five items of data including effective measuring points, normal data quality information, non-out-of-range data, normal multi-selection measuring point data and timely data refreshing, the quality of the power production data is evaluated in real time according to the types of the measuring points, and the production data quality is comprehensively evaluated from the aspects of effectiveness, accuracy and timeliness of the data. Abnormal conditions in the production process are accurately positioned, the use value of data is guaranteed, and the requirements of power enterprises for big data analysis and data security management are met.

The invention relates to the technical field of computer graphic processing, and discloses a method for automatically drawing a DCS (Distributed Control System) picture into a real-time database picture, which comprises the following steps of: firstly, identifying a DCS source file format, directly analyzing a public text format or intercepting a bottom layer rendering instruction for a private binary format, and extracting standardized discrete data; constructing an intermediate vector model, and performing coordinate normalization and curve smoothing processing on the static primitives by using an affine transformation matrix; meanwhile, syntactic analysis is conducted on the control script to construct an abstract syntax tree, and dynamic logic is converted; then recombining a composite object based on spatial semantics, and repairing pipeline topology connection by utilizing automatic adsorption and an orthogonal routing algorithm; and finally, calling a target system interface to complete object instantiation and persistent storage. According to the invention, the automatic high-fidelity migration of the DCS picture to the real-time database is realized, the labor cost is reduced, and the consistency and accuracy of the monitoring picture are ensured.

The invention discloses a wind power plant monitoring method and system based on a real-time database, and relates to the technical field of wind power plants, and the wind power plant monitoring method comprises the following steps: storing obtained real-time operation characteristic data in the real-time database; identifying operation fault data of the current wind power plant; based on the identified operation fault data of the current wind power plant, key factors influencing the operation fault of the wind power plant are obtained; and dynamically adjusting operation parameters of wind power plant equipment and optimizing real-time monitoring. According to the method, the real-time operation characteristic data is analyzed based on the fault diagnosis algorithm, the current operation fault data of the wind power plant can be quickly identified, the fault can be found more quickly and accurately, the abnormal condition of equipment can be mastered in time, and the equipment damage risk caused by delayed detection is reduced.

The application provides a power common information model-based sharding parallel maintenance method and device and electronic equipment. The method comprises the following steps: dividing a power common information model into multiple shards according to a maintenance range division and a hierarchical relationship of the power common information model, each shard containing a complete hierarchical structure of the power common information model; generating an offline maintenance copy corresponding to each shard from a real-time database storing the power common information model according to the divided shards, the offline maintenance copy containing data of a model object in the power common information model; performing an add, delete, modify and query operation on the offline maintenance copy corresponding to each shard, and publishing the maintained shard offline maintenance copy to the real-time database.

The application provides a smart environmental protection large model desulfurization scene identification interaction method, system, medium and product, which comprises the following steps: firstly, the desulfurization role scene is matched through multi-modal instructions, and a graphical sand table and a global conversation state are initialized; after a diagnosis report generation instruction is received, multi-dimensional operation parameters of equipment associated with a role ID and a space-time context are obtained from a real-time database; a diagnosis result is obtained through analysis of a diagnosis large model and is mapped to a corresponding equipment graph element of the sand table; fault keywords are extracted to match a three-level differentiated solution scheme of quick solution, medium-term optimization and long-term upgrade; in response to a target scheme selection instruction, a quantitative evaluation result is generated through an efficiency estimation model combined with real-time working condition data, and finally, the result is visually presented to an interaction terminal. The whole process realizes a closed-loop intelligent interaction from intention recognition to decision support, and improves operation and maintenance efficiency and precision.

Techniques are provided for copying data from a source database to a target database in a database replication system which includes a database event mining system, an event interceptor process and an event receptor process. In one aspect, the event interceptor detects a failure in the event receptor and switches to a mode in which it rejects new database events from the database event mining system. The event interceptor can also request that the database event mining system resend the event after a specified delay. The event interceptor can also shut itself down for a specified period of time, then restart and listen for a pairing request from the event receptor. In another aspect, the event receptor can request that the database event mining system send event data from a specified system change number.

The present invention is applicable to the field of intelligent factory cutting processing technology, and provides an intelligent factory application method and system based on a real-time database, the method comprising: obtaining the initial cutting speed of the target tool for the target workpiece, and extracting the historical processing log of the target tool in the intelligent factory, and at the same time identifying the surface coating type of the target workpiece in real time through visual detection technology, and obtaining the current surface coating roughness value; parsing the historical processing log, screening out the historical workpiece processing records that are consistent with the target workpiece type and have the same surface coating type, and extracting the load data of the target tool under different coating thickness conditions from the screened historical workpiece processing records. The present invention effectively integrates macro trends and local characteristics to form a global and local collaborative processing optimization mechanism. By comprehensively correcting the cutting speed, the tool load adaptability is significantly improved, the tool life is extended, and the stability and surface quality of workpiece processing are improved.

The invention discloses a security test method and device for an industrial real-time database and a storage medium, and relates to the technical field of industrial internet. The method comprises the following steps: based on a three-security partition architecture, realizing security test on the industrial real-time database by verifying the transmission security of each interval. The logic isolation test between the first security zone and the second security zone emphatically checks access control strategies, industrial protocol transmission integrity and abnormal traffic filtering. The physical isolation test between the first security area or the second security area and the third security area comprises the steps of verifying one-way transmission and data integrity of the forward isolation device and verifying formats and security policies by the reverse isolation device. The cross-three-zone linkage transmission test covers end-to-end data transmission security verification, a simulation attack penetration test from a third security zone to a first security zone, and an emergency mechanism test under an isolation device fault. According to the method, the safety of the industrial real-time database can be improved through a three-partition testing method.

The application discloses a kind of based on deep reinforcement learning's atmospheric and vacuum distillation unit intelligent optimization method and system, it is related to oil refining chemical industry, including, from the distributed control unit of atmospheric and vacuum distillation unit and real-time database collection historical operation data, and pre-processing, obtain the historical data set after pre-processing;Using the historical data set after pre-processing, process mechanism characteristic network is constructed by graph neural network, the correlation between equipment components is mined and abstract feature representing process principle is extracted, and digital twin environment is constructed;In digital twin environment, meta-reinforcement learning algorithm is used to train deep reinforcement learning agent, so that deep reinforcement learning agent obtains meta-strategy suitable for different crude oil properties.The application realizes safe, smooth, efficient intelligent optimization control through safety mirror image drill and trust degree driven closed-loop operation mechanism, solves the optimization response lag problem caused by manual adjustment model due to the change of traditional optimization technology crude oil property.

The invention discloses a three-level storage method suitable for industrial control data, which is based on cache storage, real-time storage, historical storage, cache monitoring object service and data dump object service, and comprises the following steps of: acquiring latest industrial control data from each data measurement point by an industrial control system data acquisition module; pushing the collected latest industrial control data into a system cache storage in real time according to a cache storage rule, and updating and identifying data measuring points with changed industrial control data; the cache monitoring object service scans the industrial control data of all the data measuring points in real time, reads the changed industrial control data, stores the changed industrial control data into a real-time database in batches in real time, and identifies the data measuring points as updated; and the data dump object service reads the industrial control data conforming to the rule in the real-time database according to the configured dump rule, stores the industrial control data in the historical database according to the dump rule, and deletes the dump industrial control data in the real-time database at the same time to complete the three-level storage processing process of the industrial control data.

Embodiments of the present disclosure provide a data updating method, medium, device and computing device. The method comprises: obtaining authorization information from a message queue, the authorization information comprising change information of authorization data; obtaining first target authorization data from a real-time database; extracting authorization data calculation logic from the authorization information; updating the first target authorization data by using the authorization data calculation logic, and storing the updated first target authorization data to the real-time database. According to the above scheme, the authorization information is obtained in real time through the message queue, and the authorization data in the database is updated, so that the data is updated in real time.

The application discloses a kind of ship painting workshop field environment monitoring systems, including field detection unit, control center and data acquisition network, field detection unit is installed in the integrated monitoring point of ship painting workshop field, for measuring the environmental parameter of integrated monitoring point;Control center is connected with field detection unit by data acquisition network, receives the data collected by field detection unit;The control center at least includes real-time database and and software management system, and software management system includes eight functional modules of system management module, real-time display module, prediction analysis module, alarm management module, interface module, report management, basic data management and green evaluation system etc..The application precisely monitors and traces the environmental quality of painting workshop, realizes targeted management;It can also carry out multi-dimensional analysis on monitoring data, provide decision support for environmental pollution prevention and control, and enhance the rapid response and disposal capacity of environmental emergencies.