22444 results about "Bus" patented technology

The invention provides a BIM intelligent management platform oriented to a whole life cycle of project construction. A building information model, Internet of Things sensing data and a block chain evidence storage mechanism are integrated through a multi-source data fusion technology, and a whole-process data chain of association planning, design, construction, operation and maintenance is associated. The platform adopts space optimization Huffman coding to realize model lightweight, combines a constraint genetic algorithm to optimize a construction path, and applies a bidirectional long-short-term memory network to analyze an equipment state. A three-chain block chain system is reconstructed on the architecture, intelligent association of engineering quantity and payment nodes is realized through cooperation of a main chain, a calculation quantity side chain and an auditing side chain, and mobile terminal offline interaction is supported based on a digital-analog separation technology. The platform covers an intelligent design management unit, a block chain investment management unit, a dynamic correction management unit, a quality safety responsibility tracing unit, an NLP risk management unit and a digital twin operation and maintenance unit. The units achieve cross-system cooperation through a unified data bus, and a closed-loop management architecture covering the whole life cycle of project construction is formed.

The invention relates to a network real-time synchronization communication system, and relates to the technical field of computer network communication. The system comprises four core modules: a hardware optical IO synchronization module which integrates a multi-wavelength optical transceiver array and an anti-jitter circuit and provides a nanosecond global clock signal, and the synchronization precision is less than or equal to 15ns; the time sequence arrangement module is used for dividing a fixed time window and a dynamic buffer window based on a time sensitive network, supporting a priority preemption mechanism of the SRIO bus and realizing deterministic data transmission; the distributed RTDATA nodes replace a traditional single-board computer, a heterogeneous computing unit and an intelligent storage controller are integrated, and protocol stack processing delay is reduced through the zero copy technology; according to the dynamic multicast routing system, a safely isolated multicast tree is constructed as required, and link load distribution is optimized in combination with machine learning. Through collaborative design of hardware optical synchronization and dynamic data arrangement, the problem of real-time performance reduction caused by multi-node communication concurrence is solved.

A diagnostic system and method for identifying and resolving vehicle Controller Area Network (CAN) bus faults is disclosed. The system connects to a vehicle's data link connector (DLC) and automatically retrieves diagnostic trouble codes (DTCs) from multiple electronic control units (ECUs). It filters the DTCs to identify those related to CAN communication errors, groups repeated DTCs across ECUs to highlight systemic faults, and assigns repair priority based on status, scope, and criticality. A user interface displays prioritized DTCs with definitions, affected systems, possible causes, and repair guidance. Upon technician input, the system re-scans the network to confirm resolution and updates the display accordingly. The invention supports semantic and conceptual recognition of communication faults, enabling robust, language-agnostic analysis. This system reduces diagnostic time, improves repair accuracy, and supports multilingual or manufacturer-specific DTC definitions without requiring external infrastructure or advanced user expertise.

The invention discloses a storage battery capacity checking method for a parallel intelligent direct-current power supply system, and relates to the technical field of storage battery capacity checking, which comprises the following steps of: respectively deploying electromagnetic sensing modules with nanosecond-level response capability at a master control end and a slave node end of a communication bus, acquiring voltage disturbance waveform signals of the communication bus in an operation process, and performing feature extraction operation on the transient high-frequency interference pulse detected each time, and constructing a multi-dimensional feature sequence of the high-energy transient electromagnetic interference. By deploying the high-response electromagnetic sensing module and combining an active suppression mechanism of interference feature extraction and risk index driving, time alignment modeling and self-adaptive regulation and control of electromagnetic interference and communication performance are realized, the communication stability, the battery state recognition accuracy and the capacity accounting continuity of the system in a strong interference environment are effectively improved, and the system reliability is improved. And the anti-interference capability and the operation safety of the parallel direct-current power supply system are obviously enhanced.

The invention discloses an IT asset fault propagation prediction method and system based on dynamic evolution of a knowledge graph, and relates to the technical field of cloud computing and large-scale IT operation and maintenance management. Through an asynchronous message bus and a logic clock, the knowledge graph is updated immediately when resources are abnormal and a scheduling event occurs; the knowledge graph uniformly integrates physical connection, logic dependence and multi-copy redundancy, so that the cross-machine-room asset relationship is clear at a glance. And then, based on a weighted logistic regression model, node features and relation weights in the knowledge graph are fused, the node fault probability is accurately calculated, the limitation of traditional single-dimensional analysis is solved, self-healing operation is supported, end-to-end intelligent operation and maintenance from fault detection to prediction and early warning to closed-loop self-healing are realized, and the fault detection efficiency is improved. The problems that in a cross-machine-room and multi-live-site environment, resource topology is split, real-time state and alarm information cannot be fused with an asset dependence model, and large-scale real-time deployment of a traditional single-dimensional fault analysis and high-complexity prediction algorithm is difficult are effectively solved.

The invention discloses a tough city resource allocation method and system based on a block chain and edge computing, and relates to the technical field of city resource allocation, a federal protocol is utilized to exchange and shear a gradient abstract synchronization model version, then a prediction abstract containing fingerprints is written into a permission chain, and a time sequence is solidified through Byzantine consensus; an on-chain smart contract executes adaptive threshold evaluation based on sliding window prediction to generate a deployment intention with a verifiable path, the intention is sent to an execution subsystem through a side chain message bus in a low-delay mode, and cross-department resource rearrangement is completed through rolling optimization of an adaptive decision driver; an execution receipt is mapped into an incremental patch and written back to a local state tensor, a node trust weight is dynamically adjusted, and when the coverage degree and the weight rising range meet a triggering strategy, differential shearing training is started, and a new structure fingerprint and a model signature are generated; and efficient, credible and dynamic allocation and sustainable learning synchronous evolution of urban public resources in an emergency scene can be ensured.

The invention discloses an operation collaborative optimization method for an optical storage direct current flexible interaction system. Comprising the steps of collecting operation data such as photovoltaic output, an energy storage state, household load power and direct current bus transmission power, fusing power market price information, and constructing a multi-dimensional time series data set; then, predicting an adjustable load capacity interval of the system based on a coupled physical constraint neural network model embedded with DC bus power balance, voltage constraint and equipment operation limitation; further constructing a state-action space, solving a Pareto frontier by adopting a multi-objective optimization algorithm, and generating a light storage and home load collaborative scheduling strategy set; then combining the real-time operation state and the prediction deviation information, applying a voltage-power droop control mechanism to carry out strategy decoupling, and generating an energy storage power correction amount and a flexible load priority control instruction; and finally, a control instruction is issued to the optical storage direct flexible system, so that collaborative optimization operation with consideration of economical efficiency, safety and comfort of the system is realized.

The invention belongs to the technical field of radars, and discloses a vehicle-mounted multi-source radar converged communication system based on a FlexRay bus and a synchronization method of the vehicle-mounted multi-source radar converged communication system based on the FlexRay bus. The FlexRay communication bus supports a static and dynamic dual-channel structure and has a deterministic communication capability, and the maximum bandwidth can reach 10Mbps; the distributed radar controller is connected with each radar node and used for collecting local radar data, packaging timestamps and uploading the data through FlexRay; the time synchronization controller is used for realizing nanosecond synchronization through a FlexRay global clock mechanism and broadcasting clock signals to all radar nodes; the fusion processing unit is used for intensively receiving all radar data and carrying out target detection and data fusion based on a unified time sequence; and the main control coordination module is used for upwards communicating with the automatic driving domain controller and downwards uniformly coordinating the behaviors of the subsystems. The system has the capabilities of accurate time sequence, multi-source data fusion, fault-tolerant control and the like, and is a high-reliability communication platform supporting intelligent driving decision making.

The invention discloses an internet of things multi-protocol fusion limo intelligent control system, which relates to the field of limo intelligent control and comprises a hardware irrelevant layer, a multi-protocol adaptation layer, a data abstraction layer, a programmable logic layer, a security and redundancy mechanism and an edge AI module. According to the invention, a physical bus is packaged into an independent module, an MCU / SoC and a protocol transceiver are built in, hot plugging is realized through a standardized PC I e / EdgeConn backboard, a core processing board only exposes a unified backboard interface, module drive localization execution is realized, master control firmware does not need to sense protocol details, only the module needs to be replaced when a protocol is newly added, and the master control firmware or upper software does not need to be modified. The defect that the whole vehicle firmware needs to be refreshed when a bus is replaced in a traditional system is overcome, each protocol corresponds to an independent drive micro-service deployed in a containerization mode, the drive micro-service analyzes a message into a unified data model and uploads the unified data model to a data abstraction layer, a downlink control instruction is packaged and issued according to a target protocol, and it is guaranteed that the protocols are diversified and interfaces are consistent.

The embodiment of the invention discloses a multi-agent task collaboration method and device and a medium, and the method is characterized in that the method comprises the steps: registering functions corresponding to all agents to a dynamic service directory through an MCP protocol; disassembling the to-be-executed task to obtain a plurality of to-be-executed sub-tasks, matching each to-be-executed sub-task with the capability range of each agent in the dynamic service directory, and establishing a communication channel between each to-be-executed sub-task and the corresponding agent; performing dynamic routing distribution on the to-be-executed sub-tasks through the cooperative bus, and selecting an optimal execution node according to the real-time requirements of the sub-tasks and the node load state of each corresponding agent; according to a subtask dependency relationship defined by a directed acyclic graph, determining an execution mode of each subtask to be executed; and executing each to-be-executed sub-task at the optimal execution node based on the communication channel and the execution mode of each to-be-executed sub-task.

The invention provides a GNSS (Global Navigation Satellite System) anti-interference receiver system based on radio frequency front end-INS (Inertial Navigation System) combined assistance, which adopts a dual-core ARM Cortex-A9 and a programmable logic unit for layered decoupling, and realizes real-time receiving and processing of a high-bandwidth data stream, closed-loop control of an interference suppression link and quick response of a navigation path and a strategy decision. All the modules efficiently cooperate through AXI-Lite register mapping, interrupt signals, a shared state buffer area and a timer synchronization mechanism. By controlling bus and state buffer mapping to keep consistency and supporting a module-level independent debugging and system-level soft reset mechanism under hot start, the expandability of subsystem cascade debugging, fault module positioning and online updating is realized. In the aspects of module architecture, data channels and cooperation mechanisms, the structure order, efficient communication and control closed loop are realized, and an embedded multi-module cooperation anti-interference platform which is suitable for a high-interference environment, multi-channel fusion processing and navigation task real-time response is constructed.

The invention discloses a solid state disk management system and a data processing method, and relates to the technical field of solid state disk management. Flexible task scheduling and resource management are provided through a lightweight operating system module, and a computing task program defined by a user is supported to be dynamically loaded; edge computing or machine learning operators are efficiently executed in combination with a programmable hardware processing unit and a DMA channel of the computing acceleration engine module, the data preloading module is utilized to predict and preload data to DDR based on LBA access history, access delay is reduced, an NVMe protocol is expanded by means of the task unloading interface module, host task issuing and result returning are achieved, and the data processing efficiency is improved. And hardware-level memory protection is ensured through the security isolation module, so that the data calculation processing capacity of the solid state disk is remarkably improved, localized calculation tasks such as edge calculation and machine learning are supported, mass data transmission is effectively reduced, and bus and network loads are relieved.

The invention discloses a matrix layout illumination state detection method, device and equipment, and the method comprises the steps: collecting and analyzing a power supply bus current waveform and a single lamp feedback signal, and generating a node feature cluster; extracting a power consumption difference value of adjacent lamps, identifying an abnormal observation point and constructing a fault diffusion chain; marking a timestamp for the fault diffusion chain, determining a fault source, and marking current by injecting characteristics to delimit an influence domain; deploying monitoring anchor points at the boundary of the influence domain, collecting the light color parameter variation and predicting the residual life; extracting the oscillation envelope of the starting current peak, evaluating the health degree of the driver and generating a maintenance density field; and a three-dimensional detection field is constructed by fusing multi-dimensional detection data, singular points are searched, and coordinates of a fault lamp are accurately analyzed through fault positioning pulses. According to the invention, three-dimensional monitoring from electrical characteristics and optical performance to driver states is realized, a single lamp fault can be accurately positioned, a life trend can be predicted, fault propagation can be tracked, and technical support is provided for intelligent operation and maintenance of a large-scale illumination system.

The invention discloses a harbor shore power system oscillation damping suppression method based on heuristic probability optimization. According to the method, sliding window preprocessing is carried out on an alternating current bus side current time domain oscillation signal, modal decomposition is carried out based on a Prony algorithm, and modal energy is calculated to judge an oscillation mode; the discriminated oscillation modes are aggregated and mapped into equivalent circuit elements, a corresponding three-order circuit state matrix is constructed, and the damping ratio of each mode is determined according to the characteristic value of the matrix; taking a damping ratio as an evaluation index, introducing an influence factor to construct a multi-objective optimization function, parameterizing the parallel adjustable impedance, and limiting an adjustable range; and searching the control parameters by adopting a heuristic probability optimization strategy to obtain final damping control parameters, and downloading the final damping control parameters to the parallel adjustable impedance device to realize online dynamic adjustment. According to the method, multi-modal identification, physical magnitude mapping and online adaptive optimization can be realized, and the suppression capability and the operation stability of the shore power system on sub / super synchronous oscillation are improved.

The invention relates to the technical field of medical equipment, and discloses a multi-head transfusion intelligent switching control system, which comprises the following modules interconnected with a control bus through a data bus: a multi-source information binding module; a multi-modal sensing data fusion module; an intelligent safety control module; an edge-cloud collaborative decision module; a human factor engineering interaction module; a system full life cycle management module; and an infusion pipeline switching execution mechanism. Through the multi-mode sensing fusion and real-time data processing technology, the whole-course automatic monitoring of the infusion progress, the flow speed and the remaining medicine amount is achieved. The nurse station central billboard and the mobile terminal synchronously display infusion states of all beds, sound-light alarm is triggered in time when abnormal conditions occur, manual patrol video frequency is remarkably reduced, an edge computing node is applied to carry out localized data analysis, and it is ensured that alarm response delay is lower than a clinical safety threshold value. And the problem of low efficiency caused by manual regular patrol traditionally is effectively solved.

The invention relates to the technical field of hybrid inverters, and discloses a hybrid inverter supporting reactive compensation and a control method thereof, and the hybrid inverter comprises a DC input unit, a three-phase full-bridge inversion unit, a grid-connected switching unit, a signal acquisition unit and a digital control unit. The direct current input unit comprises a photovoltaic interface, a battery interface and a direct current bus and is used for converging photovoltaic and energy storage electric energy; the three-phase full-bridge inversion unit is composed of a power device and an LCL filter and converts direct current into alternating current. The grid-connected switching unit comprises a static switch and an isolation transformer and is used for controlling power grid connection; the signal acquisition unit detects voltage and current signals; and the digital control unit judges a grid-connected mode or an off-grid mode according to the signal, calculates a reactive current reference value and generates a PWM (Pulse Width Modulation) control signal so as to realize reactive compensation control in the grid-connected mode and the off-grid mode. According to the invention, reactive power compensation capability is provided in both grid-connected and off-grid operation modes, and stable operation of the inverter in various working conditions is ensured.

The invention discloses a three-dimensional cutting dynamic parameter adjusting system and method based on deep learning, and relates to the technical field of application of three-dimensional five-axis fiber laser cutting machines in the automobile manufacturing industry, and the three-dimensional cutting dynamic parameter adjusting system comprises a multi-mode sensor cluster, an edge calculation unit, a closed-loop control module and an AI model library, the multi-mode sensor cluster collects cutting data, the edge calculation unit receives the multi-mode sensor data and outputs dynamic adjustment parameters, and the closed-loop control module transmits the dynamic parameters to the laser generator and the five-axis motion controller through a high-speed communication bus to form a'sensing-decision-execution 'closed loop. The cutting state and risk are sensed in real time by designing a multi-mode sensor for collaborative decision, the problems that manual experience depends on and dynamic response lags are solved, the reject ratio is reduced, and the response speed is increased.

The invention discloses a bus duct full life cycle health management system based on digital twinning, and relates to the technical field of health management. The multi-source sensor collects operation parameters and static information, the digital twin modeling and mapping module constructs a physical model and associates real-time data, and a thermal-electric coupling equation is used for simulating temperature; the state monitoring and fault diagnosis module compares data to judge states and diagnoses faults by means of methods such as a fault tree, the health assessment and decision making module constructs an index system to assess health and makes a maintenance decision, the data management and interaction module stores data and realizes visual interaction and system integration, and the intelligent optimization module performs intelligent optimization based on operation and maintenance data. And optimizing model parameters and a decision strategy. According to the invention, intelligent health management of the bus duct is realized, multi-source data acquisition is accurate and comprehensive, fault diagnosis is more accurate and prediction is more timely through combination of digital twinning and an algorithm, and intelligent assessment assists scientific maintenance decision; and the operation and maintenance efficiency and the power transmission stability are improved through system integration and edge calculation.

The invention relates to the technical field of data acquisition, in particular to a multi-source heterogeneous bus data acquisition protocol configuration method, which realizes protocol identification and structure analysis of CAN (Controller Area Network), Modbus and Ethernet / IP (Internet Protocol) bus data by dynamically compiling protocol source codes and registering analysis classes, and comprises the following steps of: extracting protocol feature information from a data stream; the method comprises the following steps of: calling a corresponding protocol analysis class to perform recursive analysis, and executing parameter analysis and mapping, in addition, defining a new protocol semantic feature and dynamically generating a protocol analysis plug-in through an XML (Extensible Markup Language) configuration file to realize protocol semantic-level custom extension, adopting source code level dynamic compilation and plug-in design, supporting a new protocol plug-and-play mode, and being high in practicability. System codes do not need to be modified and redeployed, and the flexibility and expandability of the system are effectively improved.

The invention provides an urban construction and traffic engineering investigation and design enterprise product quality management system and method. The system comprises a cross-project type quality data fusion module, a dynamic defect evolution prediction module, an intelligent layered spot check engine, a three-dimensional quality situation deduction module, a conference knowledge graph construction module, a result influence evaluation module and a self-adaptive file management system. All the modules are connected through a unified data bus to form a closed-loop management process of quality data acquisition, analysis, decision and feedback. According to the system, through the functions of multi-modal data fusion, defect prediction, intelligent spot check, situation deduction, knowledge precipitation, achievement evaluation, file management and the like, the whole-process intelligent management and control of the project quality are realized, and the management efficiency and the decision scientificity are improved.

An electronic hardware wallet for conducting cryptocurrency transactions, blockchain transactions, or other secure communications is embodied on a monolithic integrated circuit (IC) die supported on a single substrate. The monolithic semiconductor device can include a non-volatile data store for storing application software executable by the multi-core processor, and the secure element can include a secure data store for storing secret data (e.g., a private key) for use in a secure electronic transaction. In some embodiments, the secure element can include hardware logic embodying a cryptocurrency algorithm associated with executing the secure electronic transaction and can have a limited and selective communication bus between the secure element and the multi-core processor. The electronic hardware wallet can communicatively couple with one or more other devices to facilitate a multi-party computation (MPC) algorithm for authenticating the cryptocurrency algorithm and validating the secure electronic transaction.

The invention discloses an output conversion system and method for a UPS (Uninterrupted Power Supply), and the system comprises a main power input end which is connected with a bridge rectifier through a first electromagnetic relay; the energy storage module comprises a super capacitor group and a parallel lithium battery group, and is coupled with the bus capacitor through a bidirectional DC / DC converter; the input end of the multi-path regulation and control module is connected with the bus voltage sensor, and the output end is connected with the switching execution unit through a second electromagnetic relay group; the dynamic switching unit comprises an I-GBT matrix and a reverse blocking diode array which are respectively connected with the inverter and the bypass circuit in parallel; and the real-time monitoring module is provided with a current harmonic analysis unit and a load break variable detection unit, and the output end of the real-time monitoring module is connected with the ADC port of the central processor. According to the invention, systematic improvement is realized in three dimensions of electric energy quality guarantee, equipment reliability and dynamic response capability through an original multi-path regulation and control architecture and a deep cooperative intelligent control strategy.

The invention relates to the technical field of public transportation systems, and particularly discloses a bus departure scheduling method, which comprises the following steps of S1, integrating multi-dimensional data; s2, a dynamic prediction model containing machine learning parameters is adopted to calculate the passenger demand in the future period; s3, calculating the number of required vehicles according to the predicted demand, the vehicle capacity and the dynamic load coefficient; s4, constructing a multi-objective function including energy consumption optimization, and solving the optimal departure interval and route; and S5, according to the real-time data, correcting a scheduling scheme, collecting real-time feedback data through a passenger mobile application, analyzing the emotion and demand of the passenger by using a natural language processing technology, based on feedback intention recognition of an emotion analysis model, constructing a passenger demand knowledge base in combination with historical complaint data, and optimizing a dynamic prediction model and a scheduling strategy. Through technology integration and system innovation, the static and single bottleneck of traditional scheduling is broken through, and an intelligent solution considering efficiency, low carbon and user experience is provided for urban buses.

The invention relates to a real-time power grid topology analysis method based on a graph neural network, and the method comprises the steps: firstly, carrying out the electrical topology analysis at a substation level through constructing an optimized power system physical connection model, carrying out the electrical topology analysis in combination with a label propagation algorithm (LPA), precisely recognizing a calculation region, optimizing the division of the calculation region through employing the graph neural network (GNN), and enhancing the topology adaptability, mistaken division is reduced; and the robustness of equipment state change is improved. Besides, according to the method, the real-time performance, the accuracy and the intelligent level of power grid topology analysis are further improved by predicting the influence of the state change of the circuit breaker and the disconnecting switch on the power grid topology and training a GNN model and reinforcement learning (RL) optimization region division strategy through historical data. And finally, bus-branch connection is optimized through depth-first search (DFS), the topology integrity is ensured, and the efficiency of electrical island analysis, power supply area division and fault recovery is remarkably improved. The real-time performance, the accuracy and the intelligent level of power grid topology analysis are effectively improved.

The invention discloses a ship mobile energy storage system CAN communication protocol automatic test system and method, and the system comprises a protocol modeling and test configuration module, a simulation node behavior simulation module, a CAN bus interaction and power closed loop module, and a test analysis and result evaluation module. A CAN communication protocol specification of the ship mobile energy storage system and parameters of tested equipment can be obtained, a protocol analysis model and a test configuration file are constructed for format verification and logic consistency verification, meanwhile, a corresponding test case sequence is automatically generated, and the message sending time is controlled to generate a time sequence simulation message flow; and sending the time sequence simulation message flow to the tested equipment, simulating energy interaction behavior acquisition to generate a power feedback data set, testing to obtain a signal consistency deviation and a power execution error to construct a protocol conformity evaluation matrix, and generating a visual test report. According to the invention, the high coverage rate and automatic closed-loop test of the CAN communication protocol can be realized.

The invention discloses a CAN bus intrusion detection method based on adaptive unscented Kalman filtering, and the method comprises the steps: obtaining real-time message data, and carrying out the preprocessing of the real-time message data, and obtaining a time sequence feature vector; constructing a nonlinear state space model based on the time sequence feature vector; performing unscented Kalman filtering state prediction based on the nonlinear state space model; inputting the time sequence feature vector as an actual observation value, calculating a Kalman gain to correct an unscented Kalman filtering state prediction result, and outputting a state estimation residual error; dynamically updating a process noise covariance matrix through exponentially weighted moving average based on the state estimation residual, and adjusting a measurement noise covariance matrix according to the measurement innovation sequence; calculating the mahalanobis distance of the state estimation residual error, comparing the mahalanobis distance with a self-adaptive anomaly detection threshold value, and judging whether an intrusion behavior occurs or not; and if the abnormal score exceeds a threshold value, triggering a multi-level alarm mechanism, recording a suspicious message and executing a safety protection operation.

The invention discloses a method for processing an uncorrectable error of bus equipment and a server, relates to the technical field of servers, and aims to reduce the reporting frequency of the uncorrectable error by setting a suppression identifier of the uncorrectable error of the bus equipment and a time window of uncorrectable error statistics, and improve the reporting efficiency of the uncorrectable error when the uncorrectable error is triggered for the first time. According to the method, uncorrectable errors are reported, the uncorrectable errors are captured, it is ensured that initial errors are not missed, and when the error count of a time window is larger than a reporting threshold value, reporting is carried out again, error missing processing of error aggravation is avoided, redundant error reporting is reduced, an error reporting storm is inhibited through an inhibiting identifier, and the error reporting efficiency is improved. Therefore, the influence of frequent error triggering on the availability of a server system and normal operation of other services is reduced, the reliability of the server is improved, and the technical problems that frequent error triggering cannot be corrected, other service requirements are covered and the availability of the server system is influenced in the related technology are solved.

The invention discloses an AGV (Automatic Guided Vehicle) scheduling system based on a soft bus protocol of a swan gap system and star flash wireless communication, and relates to the technical field of AGV scheduling planning, the AGV scheduling system comprises an AGV scheduling management center, and the AGV scheduling management center is in communication connection with a task management module, a communication connection management module, a global task collaborative planning module and a visual interaction module; and the task management module is used for receiving task requests, classifying, sorting and distributing tasks, and dynamically adjusting task priorities according to real-time production requirements and AGV states. According to the invention, low-delay and high-reliability communication between AGVs and between the AGVs and the scheduling management center is realized by the AGV scheduling system through a soft bus protocol of the swan Mongolian system and a star flash wireless communication technology, the communication delay is effectively reduced, the communication interruption caused by electromagnetic interference is avoided, the real-time performance of task scheduling and path planning is ensured, and the service life of the AGV scheduling system is prolonged. A solid guarantee is provided for stable operation of the AGV, and the overall response speed and reliability of the system are remarkably improved.

The invention discloses a coal mine power supply system multi-scene modeling method, system, device and medium, and belongs to the technical field of power system scene modeling, and the method comprises the steps: building a main circuit topology, and constructing a simulation model containing a user-defined module; configuring equipment parameters, and importing field survey data to construct a dynamic load matrix; setting a fault scene, and accurately simulating various power grid faults through a circuit breaker time sequence; parallel simulation is started, and bus and key node data are collected in the simulation process; performing multi-dimensional index analysis on the collected data, and extracting key indexes; a verification report is automatically generated, and evaluation is completed in combination with a manual checking mechanism; and visually outputting a simulation result. According to the method, real-time adaptation of load impedance characteristics is realized, historical load curves can be imported in batches, a dynamic load matrix can be generated, and time-varying characteristics of coal mine loads can be accurately reproduced. On the fault simulation level, circuit breaker opening and closing logic is adopted, superposition simulation of bilateral voltage loss and multi-source faults is supported, and the seamless switching performance of the energy storage system is verified.

The invention relates to the technical field of intelligent power distribution, in particular to an optical storage and charging integrated system based on a distributed soft bus, which comprises hardware equipment: a photovoltaic module, a wind driven generator, an energy storage module, a charging pile, acquisition equipment, a photovoltaic controller, a DCDC module and a mains supply / thermoelectric generator; communication and control: a distributed soft bus, a time sensitive network (TSN) and an intelligent control unit (EMS); according to the scheme, photovoltaic, wind power, energy storage, charging piles and other hardware equipment are connected through a distributed soft bus, real-time transmission of control instructions is achieved through a TSN, data are analyzed through intelligent algorithms such as a charging and discharging model and a multi-task learning model, an optimization strategy is generated, multi-energy cooperative control (including photovoltaic direct supply and energy recovery in the case of faults) is executed through an EMS, and the energy efficiency is improved. A user can set priorities through a terminal to participate in scheduling, and finally model parameters are corrected based on feedback data to form a light storage and charging integrated system of data acquisition, prediction optimization, intelligent control, user interaction and closed-loop evolution.