26results about How to "Real-time response" patented technology

The invention discloses an electric power-traffic collaborative balance scheduling method and system for electric vehicle charging, and belongs to the technical field of electric power systems, and the method comprises the steps: obtaining the travel charging demand information, charging station information and traffic network information of each electric vehicle in real time; constructing a power-traffic coupling operation network model which comprises a power network model, a traffic network model and a coupling network model; using a multi-agent multi-layer graph convolutional learning algorithm to perform power-traffic collaborative balance scheduling, using a preposed graph convolutional network to perform coupling feature representation and environmental state perception on the coupling network model to obtain the coupling feature of each node, and using a charging station as an agent to perform power-traffic collaborative balance scheduling; and inputting the coupling characteristics of the node where the charging station is located into the state space as a part of observed quantity of the intelligent agent, and outputting a charging scheduling decision of each electric vehicle through a target strategy network and a target value network in the intelligent agent. The electric vehicle charging routing behavior can be optimized, and real-time balanced scheduling of the electric power-traffic network is realized.

The invention discloses an intelligent charging management system and method based on edge computing, and relates to the field of edge computation.The method comprises the steps that 1, an edge computing node module is arranged, the edge computing node module comprises a data acquisition unit and a data processing unit, data of a charging pile is acquired based on the data acquisition unit and the data processing unit, and the data of the charging pile is acquired; by introducing an edge computing node, computing and control part data of the charging pile are moved to the local; step 2, the edge computing node module uploads the collected data to a central control platform; 3, the central control platform receives and processes the data uploaded by the edge computing node, and based on the reservation time of the user, the current power grid load and the real-time electricity price, cyclic charging optimization scheduling is carried out in a cyclic iteration mode; and 4, after the edge computing node detects that charging is completed or the target electric quantity set by the user is reached, charging is automatically cut off, a charging record is uploaded to the central control platform, and long-term data analysis and strategy optimization are carried out.

The invention discloses a protection method for a low-voltage power grid, the low-voltage power grid comprises a transformer area intelligent terminal and a plurality of intelligent switches, the transformer area intelligent terminal and the plurality of intelligent switches are connected through power lines, and the method comprises the following steps: establishing a longitudinal communication network between the transformer area intelligent terminal and the plurality of intelligent switches; determining a branch level of the low-voltage power grid according to the voltage, the current, the power, the electric energy and the alternating-current zero crossing point; drawing an electrical topological relation of the plurality of intelligent switches based on the branch hierarchy; establishing a transverse communication network of the plurality of intelligent switches based on the electrical topological relation; and when the power line has a short circuit or a grounding fault, the fault area is cut off through the corresponding intelligent switch, the fault information is broadcasted and the fault area is positioned through the transverse communication network, and the fault information is reported to the station area intelligent terminal through the longitudinal communication network. According to the protection method, the fault area can be accurately positioned, so that the emergency situation of the low-voltage power grid can be efficiently and quickly handled in real time.

The invention discloses a cross-protocol document approval method, system and device, a medium and a program product, and the method comprises the steps: firstly building a cross-protocol bidirectional connection relation with a rear-end server for each application end; sending the approval document to a back-end server; receipt change information pushed by the back-end server is received; and finally, dynamically updating the state of the approval document according to the document change information. The method can effectively reduce the examination and approval delay and improve the examination and approval efficiency through the persistent connection and instant notification mechanism of the WebSocket, solves the problem that different protocols or application data are difficult to synchronize through the cross-protocol support of the WebSocket, effectively reduces the cross-application data integration difficulty through the unified data interface and the WebSocket communication function, reduces the development and maintenance cost, and improves the examination and approval efficiency. By dynamically adjusting a data updating strategy and an integrated security mechanism, the reliability of data transmission updating under various network conditions is ensured, and the security and integrity of data are protected at the same time.

The invention provides AR + AI intelligent glasses for improving the safety level of electric power construction, and the AR + AI intelligent glasses comprise a rack, a high-resolution display screen, a nose pad, a head band, a detachable anti-dazzle cover, a high-quality camera, a sensor system, intelligent lenses, a microphone pickup and a data processing unit, and one side of the rack is provided with the nose pad and the head band; a detachable anti-dazzle cover, a high-quality camera, a sensor system and an intelligent lens are arranged on the other side of the rack; the intelligent glasses are further provided with an AR technology application module, an AI data processing module and a user interaction and feedback module. Through the AR + AI intelligent glasses technology, more timely and accurate power equipment information display, safety specification operation guidance and safety risk pre-judgment and early warning are provided.

The invention relates to an intelligent cerebrovascular stent based on polymer short fibers and a preparation method thereof. The method comprises the following steps: carrying out electrostatic spinning on a polymer spinning solution to obtain polymer long fibers, freezing the polymer long fibers in liquid nitrogen, and carrying out low-temperature shearing dispersion to obtain polymer short fibers; a polymer in the polymer spinning solution is at least one of polycaprolactone, polylactic acid, gelatin, cellulose, fibroin, collagen and chitosan; uniformly mixing the temperature response high-molecular polymer and the polymer short fiber to obtain a 4D printing raw material; and designing a 4D printing model of a spider-leg-imitating structure, and performing 4D printing on a 4D printing raw material to obtain the intelligent cerebrovascular stent. According to the preparation method, the intelligent cerebrovascular stent with the spider-leg-imitating structure is prepared, the spider-leg-imitating structure design and the introduction of the polymer short fibers can endow the cerebrovascular stent with better shape adaptability and intelligent responsiveness, and the mechanical property and the anti-skid property of the cerebrovascular stent are effectively improved.

The present invention relates to the technical field of financial systems, and in particular to a method and system for detecting financial and tax data, comprising the following steps: S1: acquiring business management data based on the system; S2: performing document recognition management of each business based on hardware equipment according to the business management data; S3: improving the accuracy of document recognition data using a character separation positioning module; S4: performing business management based on the document recognition results; S5: archiving and storing documents and sorting them, and automatically issuing warnings based on the sorting results. The present invention integrates the document flow, approval flow, image flow, capital flow, and voucher flow into one through a document design platform, image management, and process management, thereby realizing business-finance integration and intelligent tax burden warning; through invoice recognition, intelligent form filling is realized to reduce the error rate of form filling, and through intelligent accounting, the work efficiency of financial personnel is improved and the business information of the enterprise can be reflected in a more real-time manner, thus safeguarding the business development of the enterprise.

The present invention discloses a data call link restoration analysis system based on big data, including: a data acquisition engine, including a scheduled task acquisition unit and a flume real-time acquisition unit; a data analysis engine, for receiving data in kafka, and converting it into a set data structure, and then using rds audit log, sls audit log, and arms application stack information as analysis entrances, respectively, to perform full-link tracking process analysis; a data storage engine, for hierarchical storage of collected source data, cleaned and converted data, and data processed by a data analysis engine; a data display component, for obtaining data processed by a data analysis engine, and displaying full-link analysis results from three dimensions: data, microservices, and application systems. The present invention can solve the problem that current link tracking cannot obtain information such as the application to which the service belongs, what data in the database the service specifically calls, and the data flow link from the data center to the database.

The present invention provides a method and system for estimating the state of charge of a power lithium battery, establishes a third-order RC equivalent circuit model of a power lithium battery, determines the equation group of the model; transforms the equation group of the third-order RC equivalent circuit model to obtain a transfer function, converts the transfer function into a differential equation, and uses a forgetting factor recursive least squares method to derive the circuit parameters of the third-order RC equivalent circuit model; and in the derivation process, uses a simulated annealing algorithm to optimize the forgetting factor; based on the obtained circuit parameters, uses an adaptive H infinite unscented Kalman filter algorithm to estimate the state of charge of the power lithium battery. The present invention can significantly improve the accuracy of online parameter identification.

The invention discloses a BIM-based traffic engineering construction progress management system, and relates to the technical field of BIM. When the system runs, a feature vector FV1 is formed through a condition acquisition module, an influence factor IF of a construction progress is calculated, a preset construction plan progress PO is dynamically corrected, and a corrected predicted construction progress PD is generated; and the construction plan can be continuously optimized according to the actual situation. A feedback feature vector FV2 is formed by using field feedback, external and feedback conditions are combined to generate an influence sorting list WLB, the influence sorting list WLB and a preset condition influence progress threshold TZ are combined to generate a multi-level construction field progress evaluation strategy, and coping schemes under different scenes are provided. According to the method, the defect that traditional progress management is insufficient in response to emergencies is overcome, and through dynamic progress correction and automatic decision generation, the coping capacity of a traffic construction project facing complex external conditions is greatly improved.

The invention discloses a laser diameter measuring instrument lens self-cleaning device and method based on multi-mode cooperation, and belongs to the technical field of cigarette manufacturing. The device comprises a pollution sensing unit for acquiring the pollution area P, the oiliness index Q and the particle density G of the surface of the lens; the annular ion air curtain unit is used for generating ion airflow flowing by being attached to the surface of the lens; the piezoelectric ultrasonic unit transmits high-frequency vibration to the surface of the lens; the ultraviolet laser unit is used for emitting pulse type ultraviolet laser; and the controller is electrically connected with each unit. The method comprises the following steps: acquiring pollution characteristic parameters in real time; determining a pollution level; generating a time sequence control instruction; and all the cleaning units are cooperatively controlled to work. According to the invention, self-adaptive, non-contact, non-stop and efficient cleaning of composite pollutants such as tobacco dust, tar and sugar is realized, the real-time cleaning requirement of a high-speed production line is met, and the measurement precision and the operation stability are guaranteed.

The invention discloses a battery maintenance method based on a dynamic sparse neural network and a large language model, and belongs to the technical field of battery management. The method comprises the following steps: acquiring sensor time sequence data and an operation and maintenance text maintenance log of a battery pack, and respectively carrying out standardized preprocessing on the sensor time sequence data and the operation and maintenance text maintenance log; extracting time domain and frequency domain features of the preprocessed sensor time sequence data to obtain sensor features; carrying out semantic coding on the preprocessed text maintenance log by adopting a large language model subjected to battery domain knowledge fine adjustment to obtain text semantic features; performing feature fusion on the sensor features and the text semantic features based on a cross attention mechanism to generate fusion features; and inputting the fusion features into a dynamic sparse neural network which adaptively adjusts the sparseness of each layer of network according to the real-time health state of the battery, and outputting a battery fault probability and a fault root cause weight.

The invention provides a power grid dispatching method, a control device and a storage medium, and belongs to the technical field of power grids. The method comprises the following steps: inputting acquired operation data into a multi-objective optimization model to output an optimization scheduling variable; performing constraint condition verification on the optimal scheduling variable, when the optimal scheduling variable meets a preset constraint condition, generating a scheduling scheme of the target power grid, and issuing a scheduling scheme instruction; in the process that the target power grid executes the scheduling scheme instruction, monitoring an operation index of the target power grid; and calculating the deviation between the monitored operation index and the optimization target, and when the deviation exceeds a preset threshold value, adjusting the scheduling scheme of the target power grid. Through a technical path of offline training and online reasoning of the neural network, the generation time of the scheduling scheme is greatly shortened, and real-time response to dynamic change of the power grid is realized.

This invention relates to the field of expense reimbursement management technology, and in particular to a centralized management system and method for expense reimbursement documents based on financial sharing. The management system includes a financial sharing module, an interaction management module, and an expense reimbursement document interaction module. The financial sharing module pushes expense reimbursement document data to the interaction management module in real time. The interaction management module controls and monitors the entire interaction process of expense reimbursement documents. The expense reimbursement document interaction module implements the entire interaction process of expense reimbursement documents. A first machine learning model is established in the financial sharing module as its generator network; a second machine learning model is established in the interaction management module as its generator network; a discriminant network for the interaction management module is established in the financial sharing module; and a discriminant network for the financial sharing module is established in the interaction management module. This management system and method effectively solve the problems of risk and time-consuming / labor-intensive processes in expense reimbursement document interaction.

The invention relates to the technical field of power equipment monitoring and early warning, and particularly discloses a substation three-dimensional operation crane external damage prevention early warning system which comprises an environment sensing module, a dynamic early warning and collision prevention module, a data fusion and decision module, a man-machine interaction operation module and a system self-diagnosis and maintenance module. The environment sensing module is responsible for sensing the surrounding environment of the crane and collecting and analyzing surrounding obstacle information. According to the invention, a mode of fusing various sensor data is adopted, the system can accurately sense the surrounding environment and make a response in a three-dimensional space, especially in a complex and narrow environment such as a transformer substation, the sensor fusion can significantly improve the comprehensiveness and precision of environment sensing, the system can carry out danger prediction and intelligent decision making, and the system has a wide application prospect. And the system not only can make a response in real time, but also can carry out self-learning and optimization according to historical data and environmental changes, so that an optimal early warning strategy is provided under different operation conditions.

The invention discloses a method and system for displaying the remaining driving range of an electric vehicle and the vehicle. The method comprises the steps that the normal-temperature energy consumption and the normal-temperature driving range of the electric vehicle are obtained; based on the real-time environment temperature and the first fitting curve, a real-time temperature correction coefficient corresponding to the electric vehicle is obtained; obtaining a real-time health degree correction coefficient corresponding to the electric vehicle based on the real-time driving mileage and the second fitting curve; acquiring a second battery discharge capacity and a second driving mileage of the electric vehicle within a preset time range before the current moment, and calculating an energy consumption correction coefficient corresponding to the electric vehicle based on the second battery discharge capacity, the second driving mileage and the normal-temperature energy consumption; based on the SOC information, the normal-temperature driving mileage, the real-time temperature correction coefficient, the real-time health degree correction coefficient and the energy consumption correction coefficient, the remaining driving mileage of the electric vehicle is calculated; and controlling an instrument of the electric automobile to display the remaining driving mileage in real time. The display accuracy of the remaining driving range of the electric vehicle is effectively improved.

This invention relates to the field of electric motor control technology and discloses an electric motor control method for compressor drive, comprising: acquiring stator current signal and DC bus voltage signal; extracting voltage ripple characteristics based on DC bus voltage signal and determining initial value of quadrature axis current compensation; calculating the amplitude of stator current signal; when the amplitude crosses the linear magnetization current threshold, retrieving the inductor magnetization characteristic table to determine the inductor drop ratio; correcting the initial value of quadrature axis current compensation using the inductor drop ratio; and injecting the corrected compensation command into the current regulating loop. This invention, by integrating voltage ripple sensing and magnetic saturation correction mechanisms, synergistically cancels the pulse load interference of the compressor's single-cycle, fills the torque output gap under magnetic circuit saturation, suppresses stator current oscillation under low-frequency operation, and maintains torque response stiffness under all operating conditions.

The application provides an agent collaborative decision optimization method and system based on a multi-source heterogeneous knowledge graph, and relates to the technical field of knowledge graph intelligent decision-making. The application extracts a time-effect feature set from entities of a multi-source heterogeneous knowledge graph, generates a knowledge new-old evaluation matrix containing time decay characteristics and credibility weights, analyzes policy document version numbers, academic literature citation relationships and news event transmission chains to obtain a dynamic time-effect vector, labels the time-effect level of the knowledge graph nodes according to the dynamic time-effect vector, iterates through nodes with different time-effect levels to identify conflict node pairs, generates a directional retrieval rule set according to the contradiction type and the dynamic time-effect vector characteristics, then schedules three types of intelligent agents for parallel retrieval, exchanges intermediate results to optimize the strategy, aggregates the retrieval results to form a cross-platform evidence chain, and further generates a knowledge node update recommendation report. Based on the multi-source heterogeneous knowledge graph, the multi-agent collaborative retrieval and analysis can optimize the knowledge node decision and generate an update recommendation.

The application discloses an energy storage control method and device and an energy storage system. The energy storage system comprises a first energy storage unit and a second energy storage unit, and the first energy storage unit and the second energy storage unit are connected to a load. The second energy storage unit is a lithium ion battery. The energy storage control method comprises the following steps: detecting a load current in real time; determining an energy storage unit for supplying power to the load and controlling an output current of the energy storage unit according to the load current, an upper limit value of an output current of the second energy storage unit and a load current change rate, so that the second energy storage unit limits power output and the first energy storage unit responds to load power change in real time. The first energy storage unit and the second energy storage unit are combined, the second energy storage unit constantly outputs power according to requirements, the first energy storage unit changes the output power to respond to the load power change in real time, the real-time response to the load power change is realized, the economy of energy storage is realized, the two energy storage units are used to supply power, and the overall operation life of the energy storage system is prolonged.

The present invention discloses a method and system for intelligently evaluating the safety of ship structures. The method calculates the stress responses of key structural areas of a hull under different load conditions, different wave conditions and different speeds based on hydrodynamics and finite element software, establishes a basic stress response database, and establishes a data model to calculate and analyze the stress of key nodes of the hull in real time during actual ship operation. The above results are corrected through stress data of a stress monitoring system, and finally the stress state of the structure and fatigue life of key areas of the whole ship are diagnosed and predicted in real time, thereby realizing a comprehensive evaluation of the safety performance of the ship structure. The method also has corresponding early warning / alarm functions, etc., and can provide objective and reliable information to the crew in a timely manner, enhance the active prevention capability of the hull structure risk, improve the safety of ship operation, reduce maintenance costs and frequency, extend the service life of the ship, perform dimensionality reduction processing on data, and improve the real-time performance of stress calculation results.

This application discloses a multi-parameter fusion-based dynamic optimization method for SDC industrial control parameters, belonging to the field of parameter optimization technology. The method includes: predicting the predicted coal seam dip angle sequence and the predicted coal mining speed sequence within a future preset time zone; predicting the roof pressure of the working face and obtaining the predicted roof pressure field sequence; analyzing and determining the suitable safe time zone and the suitable efficiency time zone; optimizing the hydraulic support parameters of the hydraulic support group, outputting a queue of adapted support parameter commands, and executing hydraulic support within the preset time zone. This solves the technical problems of existing hydraulic support parameters being unable to respond in real time to complex and changing underground environments, leading to insufficient roof pressure prediction accuracy, untimely support, insufficient initial support force, or excessive pressure relief.

The invention relates to a process safety control device and method based on wall thickness online monitoring. The device comprises a plurality of sensors, a central control system, a linkage safety device and a power supply module. Each sensor is used for monitoring the change condition of the wall thickness of a flow pipeline in real time and transmitting wall thickness data to the central control system in real time through the Zigbee wireless communication module; the central control system is used for judging the erosion degree of the pipeline according to the received wall thickness change data, giving an alarm when the wall thickness of the pipeline is reduced to a preset danger threshold value, and meanwhile sending an interlocking signal to the linkage safety device. The linkage safety device closes a corresponding flow pipeline valve according to the received interlocking signal and automatically switches to a standby flow pipeline; the power supply module is used for supplying power. The method can be widely applied to the field of petroleum and natural gas exploration and development.

This invention provides an imidazole terpyridine ruthenium complex or its salt, or its solvate. This invention also provides a method for synthesizing the imidazole terpyridine ruthenium complex. This invention further provides a probe. This invention further provides the use of the above-mentioned imidazole terpyridine ruthenium complex or its salt, or its solvate, and / or the above-mentioned probe in the detection of dissolved oxygen. This invention provides an imidazole terpyridine ruthenium complex dissolved oxygen detection probe, its preparation method, and its application. Utilizing imidazole terpyridine as an optical signal reporter group, a molecular fluorescent probe is designed to detect dissolved oxygen. It has a large Stokes shift, which is beneficial for distinguishing the analytical signal from the excitation light, avoids the self-absorption of the compound, and enables in-situ, real-time response to dissolved oxygen.

The application relates to the field of silicon-based optoelectronic integration, and particularly discloses an on-chip adaptive combining method and a feedback system for polarization diversity MZM, which comprises the following steps: optical coupling and mode conversion, polarization diversity electro-optical modulation, optical power collection and photoelectric conversion, signal processing and feedback control, and a tunable combining module; after the coupling conversion and modulation, two-way optical power is collected and photoelectrically converted, a power difference voltage is obtained through an analog circuit, a control voltage is generated by superimposing a bias voltage, and a tunable combiner is driven to dynamically adjust a beam splitting ratio to complete combining. The application solves the problems that the output power of the polarization diversity MZM randomly fluctuates with the polarization state, the existing polarization control scheme has slow response, a complex structure and is difficult to integrate with a silicon-based process, realizes real-time and accurate compensation of power fluctuation, guarantees stable combining output power, and has a simple system structure, low power consumption, is easy to monolithically integrate with a silicon-based chip, and improves the performance and compatibility of an integrated photonic link.

The present invention relates to a mine dry mix terminal filling system, which belongs to the technical field of mine equipment, and includes a stirring and conveying component for stirring and conveying materials; a hopper component for storing materials stirred by the stirring and conveying component and discharging the materials; and an electrical control mechanism for controlling the stirring and conveying component and the hopper component. The present invention adopts dry high-quality premixes, and the material ratio (cement, sand, gravel) is uniform and stable; the material supply is taken as needed without any waste; when the underground material warehouse needs materials, a request can be quickly sent to the upper buffer warehouse through the electrical control system, and the materials can be automatically replenished to achieve real-time response; the material composition and ratio are not affected by environmental factors, ensuring the high quality of concrete; fewer operators are required, and the labor cost is low; the labor intensity of workers is small, the closed operating environment is less polluted, and the safety and health risks are small.

The invention provides a pre-training language model retrieval method and system based on knowledge graph enhancement, and the method comprises the steps: carrying out subgraph division processing on a domain knowledge graph, and generating a subgraph index matched with a user retrieval type; updating the domain knowledge graph and the sub-graph index by adopting an incremental training method of a graph neural network; user query is decomposed into an entity set and a relation path through entity recognition, entity disambiguation, entity linking and relation extraction operation; positioning a corresponding sub-graph index based on the entity set and the relation path, and extracting a related sub-graph from the domain knowledge graph; and respectively coding the head entity, the relationship and the tail entity in the related sub-graph triad into basic vectors, and performing semantic fusion processing on the basic vectors to generate knowledge prompt vectors. The method has the advantages of accurately capturing domain structured association logic and responding to domain dynamic iteration knowledge in real time.