5866 results about "Communication link" patented technology

The invention relates to the technical field of computing power scheduling, and discloses a heterogeneous resource computing power intelligent scheduling method and system. According to the method, real-time state monitoring is conducted on heterogeneous computing resources, and resource state parameters such as the computing unit utilization rate and the memory occupancy rate are obtained; task attributes and user request parameters of the task queue are collected, historical task data are processed based on the genetic algorithm optimization model to execute task demand prediction, and predicted demand parameters are generated. A dependency graph containing resource unit nodes and communication link roadsides is constructed through a resource topology analysis tool, predicted demand parameters are input into a scheduling priority classifier trained by a graph neural network, and an actual scheduling priority is identified. And executing resource conflict prediction based on the priority, inputting task feature vectors into a conflict resolution module of a fuzzy logic decision maker, outputting actual conflict resolution parameters, and finally integrating to generate a scheduling scheme containing a resource allocation sequence and an execution time table.

The invention relates to the technical field of tunnel power supply and distribution, in particular to a tunnel modular prefabricated cabin power supply and distribution intelligent substation self-adaptive regulation and control system based on edge calculation. Comprising an edge calculation and AI decision-making unit which is used for realizing rapid acquisition, processing and instant decision-making of tunnel power supply and distribution multi-dimensional data, generating a power supply and distribution adaptive regulation and control strategy by deploying calculation resources and a machine learning algorithm at edge nodes close to a data source, and converting the strategy into an executable regulation and control instruction; a cloud platform collaborative management unit; and an intelligent sensing and internet-of-things unit. According to the invention, hierarchical decision control of the tunnel power supply and distribution system is realized by constructing a hybrid architecture of edge computing and cloud platform collaboration and a priority judgment mechanism; according to the invention, multi-modal data are integrated through the multi-protocol communication link module and the full-scene data fusion analysis module, and data association analysis is realized through Kalman filtering, D-S evidence theory and other algorithms.

The invention discloses an intelligent substation communication link fault self-healing regulation and control method and system, and relates to the technical field of fault self-healing regulation and control, and the method comprises the following steps: constructing a link disturbance intensity sequence reflecting link quality fluctuation; performing trend fitting and mutation identification on the link disturbance intensity sequence based on a sliding window mechanism, and generating a link state transaction index; when the link state transaction index exceeds a first threshold value, identifying an affected key easy-to-disturb service set according to the service path topological data of the abnormal link; constructing a context-aware path migration cost model based on the key easy-to-disturb service set, and generating an optimal switching path sequence; and implementing hierarchical link regulation and control according to the path switching optimal sequence. According to the method, trend fitting and mutation detection are carried out by adopting an overlapped sliding window mechanism and a mutation scoring function, so that intermittent or hidden link degradation abnormity which is difficult to capture can be effectively identified, and a link state transaction index has higher judgment precision.

The invention discloses an unmanned aerial vehicle cluster intelligent cooperative control method, and the method comprises the steps: optimizing a network topology through heterogeneous unmanned aerial vehicle cluster dynamic networking and a dynamic clustering algorithm, and guaranteeing the reliability of a communication link; a layered hybrid decision architecture is designed to improve the task allocation rationality and the dynamic adaptability of the unmanned aerial vehicle cluster; a distributed control strategy network is trained by using a multi-agent near-end strategy optimization MA-PPO algorithm, and unmanned aerial vehicle cluster behavior collaboration is ensured in combination with space-time consistency constraint; an asynchronous incremental consensus protocol AICP is provided, the data transmission amount is reduced, and topology reconstruction is accelerated; real-time three-dimensional environment reconstruction and dynamic threat prediction are realized based on a neural radiation field NeRF technology; a lightweight anti-interference communication middleware is developed, and the instruction transmission stability is enhanced by adopting a space-time coding diversity technology. The method solves the problems of high delay of centralized control of the unmanned aerial vehicle cluster, poor convergence of a distributed algorithm and the like, and is suitable for high-dynamic task scenes such as urban street battle and complex terrain search.

The invention relates to the technical field of ship communication, in particular to a multi-link converged communication method and system for a ship. The method comprises the following steps: receiving navigation information broadcasted by other ships in a preset range, evaluating the availability of a communication frequency band, and generating sea area communication channel state data; acquiring geographic position data of each ship; space communication link potential analysis is carried out according to the geographic position data of each ship and the sea area communication channel state data, and cross-chain space communication potential data is generated; constructing a multi-link ad hoc network topological structure according to the cross-chain space communication potential data; and task adaptation communication link allocation is carried out based on a multi-link ad hoc network topological structure, and a multi-link fusion transmission strategy is constructed, so that real-time communication link safe switching management is realized. According to the invention, on the basis of communication service adaptation and a multi-link fusion transmission strategy, real-time communication safe switching and high-reliability transmission of the marine formation are realized.

This disclosure provides systems and methods for provisioning resources in a wireless network. In some implementations, an apparatus obtains, from a first station (STA) on a first communication link associated with an access point (AP) multi-link device (MLD), a request for association all communication links of the AP MLD, and provisions either a single communication link or multiple communication links of the AP MLD for communications with the first STA based on at least one of a latency, a level of interference, or a traffic load associated with each of the communication links of the AP MLD. The apparatus generates a frame indicating whether the single communication link or the multiple communication links of the AP MLD are provisioned to the first STA for communications with the AP MLD, and outputs the frame for transmission to the first STA.

The invention relates to the technical field of logistics management, in particular to an intelligent logistics terminal equipment collaborative management and control system based on AI edge computing, and the system comprises an edge data fusion and state recognition module which is deployed at an edge node, collects multi-source data of an operation state, environment perception, a communication link and the like, and generates an equipment state representation vector through fusion; the intelligent prediction and task scheduling decision module uploads the state vector to a cloud, predicts task completion capability and fault probability, and generates a task scheduling decision packet; the scheduling strategy issuing and edge execution collaboration module issues a scheduling packet through a multi-protocol gateway, and an edge node completes task distribution, communication switching and resource scheduling and caches a key strategy. According to the invention, the real-time sensing of the state of the logistics terminal equipment, the intelligent prediction and resource optimization of task scheduling, and the quick response and fault-tolerant control in a fault scene are realized, and the operation efficiency, the intelligent level and the stability of the system are remarkably improved.

The invention provides a task load scheduling optimization method and system for distributed network nodes, and the method comprises the steps: determining a task transmission path between the distributed network nodes according to historical task congestion data and a real-time link load prediction result; adjusting a modulation coding strategy in a task transmission process according to the channel quality parameter on the task transmission path to obtain an adjusted modulation coding strategy; according to an energy consumption demand corresponding to the adjusted modulation coding strategy, combining load distribution of each communication link and each node on the task transmission path to generate a voltage frequency adjustment instruction corresponding to the distributed network node; performing collaborative optimization on the task transmission path, the channel quality parameter and the voltage frequency regulation instruction to generate a task load scheduling strategy; according to the invention, through collaborative optimization of dynamic path selection, adaptive modulation coding adjustment and precise energy consumption regulation, the transmission reliability, energy efficiency balance and system stability of the distributed network in a high dynamic environment are improved.

The invention relates to the technical field of power system communication, in particular to a protocol conversion and communication adaptation system for an optical storage and charging grid-connected device. Comprising a protocol conversion unit used for dynamically analyzing heterogeneous protocols of a photovoltaic inverter, an energy storage converter, a charging pile and power grid side equipment; a communication adaptation unit; an energy collaboration unit; a power grid interface unit; and a man-machine interaction unit. According to the method, the protocol mapping rule base is dynamically updated through the plug-in type architecture module and the machine learning algorithm, self-adaptive analysis of multiple heterogeneous protocols and variant protocols is achieved, the protocol analysis accuracy and generalization ability are improved, and the problem that a traditional static rule base is insufficient in adaptability to non-standard protocols is solved; according to the invention, the distributed edge computing architecture is adopted to construct the bidirectional communication link, so that the real-time performance and security of the communication link are improved, and the defects of high data delay and incomplete security mechanism in the traditional communication architecture are improved.

The invention discloses an intelligent substation communication link fault accurate positioning method and system, and the method comprises the steps: obtaining a configuration file and equipment state data, carrying out the processing of the configuration file and the equipment state data, and generating a standardized link feature vector and a marking data set; constructing a hybrid deep learning model, and optimizing parameter configuration of the hybrid deep learning model by adopting an optimization algorithm to obtain a parameter-optimized hybrid deep learning model; training by using a real fault sample in combination with a virtual fault sample generated by a generative adversarial network, optimizing a time sequence prediction capability through an echo state network, and generating a fault positioning model; in combination with the link state data, outputting a fault link positioning result and confidence evaluation through multi-stage confidence evaluation and topological correlation analysis; and carrying out virtual-real corresponding verification in combination with the configuration file, carrying out parameter optimization on the fault positioning model, and outputting a fault positioning system. The problems that the fault positioning precision is low, the response speed is low, and complex fault scenes cannot be processed are solved.

The invention relates to the technical field of communication, in particular to an airborne Tiantong phased-array antenna and an application method thereof. According to the method, phased-array antenna beams are driven to perform electronic scanning according to a geometric azimuth angle, beacon signal blind acquisition is performed in a preset airspace in a wide beam mode, and when an initial signal is detected, the mode is immediately switched to a narrow beam scanning mode; dynamically adjusting a phase weighting coefficient to realize pointing adjustment, so that a signal quality parameter is continuously converged in an optimal threshold interval; carrying aircraft maneuvering acceleration feedback is introduced, beam pointing offset is dynamically compensated based on a pre-constructed interference feature library, and signal fluctuation caused by a multipath effect is suppressed; and continuously checking a data validity flag bit of the main inertial navigation system, seamlessly switching to an antenna built-in inertial navigation data stream when a failure threshold is triggered, and activating a rapid recapture program to maintain zero interruption of a communication link. Through dual-source inertial navigation data fusion and intelligent beam control, rapid and accurate tracking of Tiantong satellites in an airborne environment is realized.

The invention relates to the technical field of intelligent fusion terminal communication, and discloses an intelligent fusion terminal multi-protocol communication method and system based on edge computing. According to the method, a protocol adaptive engine is deployed at an edge node, an original data stream of a communication link is collected and analyzed in real time, and a current protocol type is dynamically identified in a fuzzy matching mode. And based on an identification result, the system dynamically loads a corresponding protocol analysis module, generates an adaptive instruction set, and realizes standardized data frame encapsulation through a protocol conversion intermediate layer. And meanwhile, the system monitors the link state, triggers incremental updating of the protocol feature library, and realizes seamless protocol switching. According to the invention, the communication compatibility and reliability are improved, and the requirements of high-reliability scenes such as the industrial Internet of Things are met.

The invention relates to the technical field of intelligent power grids, in particular to an intelligent design method and system for electric power engineering cloud resources based on distributed computing. Comprising the following steps: constructing an electric power engineering multi-dimensional resource modeling system, dividing calculation nodes into three types of heterogeneous resource units including a real-time processing core, a data analysis core and a disaster recovery backup core, and establishing a dynamic attribute matrix containing time delay sensitivity, an energy consumption coefficient and a risk assessment value; the real-time processing core is configured with a hardware acceleration instruction set and supports microsecond response; a self-adaptive dynamic clustering algorithm is adopted, elastic resource clusters facing task requirements are generated according to the spatial topological relation of resource units and the load change trend, a quantum genetic optimization mechanism is introduced in the clustering process to dynamically adjust the inter-cluster coupling degree, and a cross-cluster communication link based on credibility evaluation is established; according to the design, the problems of low resource utilization efficiency and service quality degradation caused by a static allocation mode can be fundamentally solved.

The invention relates to the technical field of traffic communication control, and discloses a vehicle-road cooperative communication optimization system for intelligent traffic. The system comprises a multi-source data sensing module for collecting multi-source heterogeneous data; the communication feature extraction module is used for analyzing the multi-dimensional features; the space-time fusion modeling module is used for constructing a combined space-time feature space; the double-layer resource scheduling library is used for storing an optimization strategy; and the dynamic collaborative decision module is used for generating a real-time scheme and instruction. The method also relates to the functions of abnormal track detection, path re-planning, communication link stability prediction and the like. According to the system, deep fusion and efficient processing of multi-source data are realized, communication resource scheduling and traffic flow regulation and control are optimized, abnormal behaviors of vehicles can be processed in time, the stability of a communication link is guaranteed, the operation efficiency, safety and communication reliability of an intelligent traffic system are effectively improved, and intelligent traffic development is promoted.

The invention discloses a multi-device cooperative control method applied to deployment of an embedded real-time operating system, and relates to the field of embedded real-time operating systems, which comprises the following steps of: S1, constructing a real-time dependency relationship graph of a task link, a multi-device cooperative task is disassembled into sub-task link units including an execution path, a real-time constraint threshold and a cross-device communication dependency relationship. According to the multi-device cooperative control method applied to the deployment of the embedded real-time operating system, the problems of task priority conflict and resource utilization imbalance in a multi-device heterogeneous environment are effectively solved through a dynamic priority transmission mechanism and a distributed resource elastic perception model. The system can sense equipment load, communication link stability and task real-time requirements in real time, dynamically adjust sub-task weights and execution paths, ensure conflict-free transmission of end-to-end delay constraints, optimize the global resource utilization rate and avoid the problem of equipment overload or idle caused by traditional static scheduling.

An apparatus to facilitate lossless and lossy automatic hardware compression in graphics-to-graphics network links is disclosed. The apparatus includes compressor / decompressor circuitry (CDC) integrated with physical layer (PHY) intellectual property (IP) hardware circuitry for a graphics processor unit (GPU)-to-GPU communication link communicably coupling a first GPU to one or more other GPUs, the CDC to: receive a data message from the first GPU, wherein the data message is in an uncompressed format; determine that a compression process is to be applied to the data message; apply the compression process to the data message to generate a compressed data message; and cause a GPU link IP hardware circuitry that comprises the PHY IP hardware circuitry to transmit the compressed data message over the GPU-to-GPU communication link.

The invention discloses a forestry ecological environment real-time monitoring and management method based on big data, and belongs to the technical field of forestry ecological environment management, and the method comprises the following steps: S1, multi-source heterogeneous data collection and sensor network deployment; s2, multi-modal data fusion and intelligent transmission: developing an adaptive communication protocol dynamic switching module, and automatically switching to a satellite communication link in a 4G / 5G network blind area; s3, mass data storage and distributed calculation: constructing a hybrid cloud storage architecture, and storing real-time monitoring data into a Redis cache queue; s4, intelligently extracting ecological environment indexes; s5, dynamically evaluating the ecological bearing capacity; s6, performing multi-level early warning and emergency response; s7, making a precise forestry management decision; and S8, carrying out system self-optimization and closed-loop management. According to the method, the air-space-ground integrated monitoring network is constructed, so that the comprehensiveness and the real-time performance of forestry ecological environment perception are remarkably improved; multi-source data of the unmanned aerial vehicle, the satellite remote sensing and the ground sensor are complementary.

The invention discloses an electronic seal management and control method and system, and belongs to the technical field of electronic seal management, and the method comprises the steps: carrying out the identity verification of a seal use request; dividing a private key of the electronic seal into a plurality of key shares; a digital signature of the electronic seal is generated through cooperative calculation of a threshold signature mechanism; managing electronic seal key access in a trusted execution environment, and executing global signature calculation in a hardware encryption module; adopting a zero-knowledge proof algorithm to generate verifiable calculation proof data in the digital signature calculation process; and establishing a quantum communication link and generating a transmission key, and managing key transmission. According to the invention, the distributed storage private key is calculated through multi-party security, so that the risk of single-point leakage is eliminated; zero-knowledge proof is adopted to ensure that signature calculation is verifiable, and signature credibility is improved; secret key access is dynamically managed and controlled based on the trusted execution environment, and safety and flexibility are enhanced; quantum key distribution is utilized to ensure key transmission safety, and quantum attacks are resisted.

The invention specifically relates to the technical field of edge computing, and discloses a multi-platform concurrent transmission edge computing data acquisition method, which comprises the following steps: S1, concurrent access of multi-platform equipment: establishing a mapping relationship between equipment identity and a communication link; s2, data concurrent collection and preprocessing: obtaining a preprocessed data stream; s3, concurrent transmission priority scheduling: allocating a transmission bandwidth for each data stream; s4, edge node parallel computing: distributing the subtasks to a plurality of computing nodes; s5, cloud collaboration and global optimization: generating a global optimization strategy; s6, carrying out full-link monitoring and dynamic regulation and control; concurrent access of heterogeneous equipment is realized by generating data streams in a uniform format, multi-platform compatibility is effectively enhanced, bandwidth is dynamically allocated to the data streams according to priority weight indexes by calculating the priority weight indexes of the data streams, data transmission efficiency is improved, and the data transmission efficiency is improved by allocating sub-tasks to a plurality of computing nodes. And the resource utilization rate of the edge computing gateway is improved.

The invention relates to the technical field of Internet of Things, in particular to a multi-protocol conversion Internet of Things terminal communication method. Comprising the following steps: monitoring a communication data packet sent by Internet of Things terminal equipment in real time through a protocol sniffing module, and extracting a protocol feature field; matching the protocol feature field based on a dynamic protocol library, and identifying a native protocol type of the equipment; generating a protocol conversion strategy according to a target platform protocol demand, and calling a corresponding protocol analysis engine to perform semantic analysis on the data packet; the analyzed data content is reconstructed according to a target protocol format, and a unified communication interface packaging layer is added; and an optimal communication link is selected through an adaptive routing algorithm, and cross-protocol data transparent transmission is completed. The invention provides an integrated communication method capable of realizing efficient protocol dynamic identification, high-reliability semantic conversion, intelligent link optimization and safe packaging, so as to break through the technical barrier of multi-protocol Internet of Things terminal interconnection.

The invention provides a laboratory equipment access and configuration method and system based on dynamic protocol analysis, and the method comprises the steps: firstly, monitoring a physical connection signal of a port, automatically triggering communication link configuration, calling a preset protocol parameter based on an interface type, and obtaining first identification information of equipment; then, based on a preset protocol mapping table or a dynamic matching rule base, determining a protocol type, and based on the protocol type, performing segmented analysis on the original data stream, identifying an effective frame and checking integrity to obtain a field definition, an instruction template and a communication parameter for binding storage with the unique identifier of the equipment; and finally, automatically generating an instruction according to the communication configuration, performing communication interaction with laboratory equipment, and triggering retransmission or link recovery operation when the communication state is abnormal by monitoring the communication state in real time. In addition, the communication condition of the laboratory equipment is displayed in real time through the interaction platform. According to the method, the deployment cost is reduced through full-automatic identification configuration, and the communication stability is improved through communication link optimization and exception handling.

The invention discloses a personalized federated learning optimization method and system, and mainly solves the problem of poor performance of an existing personalized federated learning model. The method comprises the following steps: establishing a communication link between a client and a server; each client receives a current global sharing model parameter broadcasted by the server, loads the current global sharing model parameter to a local model, and introduces a total loss function of a dynamic alignment strength definition model; training and optimizing local model parameters, and updating shared parameters by using the parameters; the client side calculates a self-adaptive aggregation weight based on the parameter updating quantity norm, the data volume weight and the synchronous frequency weight of the client side, and uploads the self-adaptive aggregation weight and the updated shared parameters to the server; and the server receives the parameter and weight information uploaded by the server, executes global model aggregation to obtain an updated global model, and outputs the global model reaching accuracy convergence or a preset training round on the verification set. According to the method, local personalization and global consistency can be balanced, the robustness and efficiency of global aggregation are improved, and the method can be used for processing scenes of high data isomerism and dynamic change of client participation states.

The invention discloses a multi-satellite network converged communication link optimization and anti-interference method, which belongs to the technical field of wireless communication networks, and comprises the following steps: acquiring Doppler frequency shift parameters of satellite nodes, adjacent satellite radiation quantity parameters and preset geographical shielding coefficients, and generating a link dynamic quality coefficient; constructing a dynamic topological graph according to the link dynamic quality coefficient; performing radio frequency fingerprint extraction and frequency domain waveform phase reversal processing on the detected interference signal to generate an anti-interference compensation signal; and when the link dynamic quality coefficient is greater than or equal to a preset quality threshold value, selecting a target transmission path according to the dynamic topological graph, and injecting the anti-interference compensation signal into the target transmission path. According to the invention, a mechanism of cooperation of dynamic link quality evaluation, interference fingerprint feature matching and multi-path fragmentation transmission is adopted, and real-time optimization selection of communication paths, accurate suppression of interference signals and efficient distribution of network resources can be realized in a complex air and space environment.

The invention relates to an electrical equipment fault monitoring and positioning method and system based on data analysis, and belongs to the technical field of electrical equipment monitoring. The method comprises the following steps: sensing a transient traveling wave signal of a fault current by adopting a traveling wave detection technology to determine an initial fault area; acquiring state data of the secondary equipment in the fault area through mapping of the secondary equipment in the fault area; constructing a secondary loop connection model based on the configuration file, and designing an action sequence rule base to verify the action logic and time sequence matching of a regional data centralized protection device, a circuit breaker and a communication link in real time; based on logic verification, action triggering conditions are extracted to be fused with the regional data set; and inputting the fault feature vector into a classification model for fault identification by obtaining the classification model. According to the invention, through traveling wave detection, EEMD decomposition, data synchronization and logic verification, feature information related to the fault is accurately extracted, and through data fusion and real-time learning, the fault identification precision and efficiency are improved.

The invention relates to the technical field of intelligent control, in particular to a barrier gate remote monitoring system and method based on the Internet of Things, and the method comprises the steps: building a dual-channel communication link through a 4G module and a Bluetooth / WiFi module, achieving the synchronous collection and uploading of the current of a barrier gate motor, a position sensor and environment data, deploying an LSTM model at an edge calculation layer, and carrying out the remote monitoring of a barrier gate. Time sequence prediction and abnormal deviation quantification are carried out on the operation state, video acquisition is triggered, vehicle retention and rod body deformation are identified in combination with a lightweight YOLOv5 model, abnormal event grading judgment is realized, spare part inventory is associated according to event types, and a maintenance scheme is dynamically generated. An intelligent work order including a thermodynamic diagram, a video frame and a prediction curve is constructed by using a three-dimensional visualization template, evidence storage processing is completed through a block chain module, and finally optimal personnel scheduling and order dispatching are executed according to a maintenance scheme. According to the method, multi-source data fusion modeling, visual linkage anomaly recognition and full-link credible operation and maintenance are realized.

The invention relates to the technical field of equipment collaborative operation of the Internet of Things, in particular to a transit hub equipment collaborative operation method and system based on the Internet of Things technology. According to the method, original attitude motion data of a target ship are collected in real time through an attitude sensor network of the Internet of Things, and a real-time attitude drift vector of the target ship relative to a geodetic coordinate system is calculated; constructing a dynamic coordinate transformation matrix according to the real-time attitude drift vector; acquiring an expected operation track control instruction preset by the quay crane control system according to the geodetic coordinate system; performing coordinate transformation operation on the expected operation track control instruction through a dynamic coordinate transformation matrix to obtain a compensated cooperative control instruction; the compensated cooperative control instruction is transmitted to a quay crane control system in real time through an Internet of Things communication link, and a quay crane lifting appliance is driven by the quay crane control system to conduct lifting operation according to the compensated track instruction; and the safety and efficiency of the hoisting operation between the ship and the quay crane can be effectively improved.

The invention relates to the technical field of mine safety early warning, and particularly provides a mine risk early warning method based on multi-parameter fusion and trend prediction, and the method comprises the steps: collecting multi-dimensional safety parameters including mine environment, equipment operation and production working condition parameters in real time; acquiring mine historical data, and generating a parameter association feature set through time sequence analysis in combination with real-time multi-dimensional parameters; inputting the multi-dimensional parameters and the feature set into a trained risk trend prediction model, and outputting a current risk level and an evolution trend; according to the risk level, the evolution trend and the real-time parameters, early warning information and a response strategy are dynamically generated; and the communication link is adapted based on the risk level, and the early warning information and the strategy are pushed to the target terminal. The method breaks through single parameter monitoring limitation, breaks through traditional alarm hysteresis through multi-parameter fusion and trend pre-judgment, constructs a perception-pre-judgment-response-transmission complete closed loop, solves the problems of early warning and disposal disjunction, transmission failure and the like, and improves the active prevention and control capability and management and control accuracy of mine risks.

The invention provides an unmanned aerial vehicle cluster dynamic topology communication network construction method and system. The method comprises the following steps: acquiring real-time spatial position information and environment obstacle distribution information of each unmanned aerial vehicle; predicting the change trend of the real-time space position information and the environment obstacle distribution information, generating a space trajectory prediction result between the unmanned aerial vehicles, inputting the space trajectory prediction result into a preset path decision unit to predict a collision risk, and generating an optimized flight path instruction; based on the change event of the optimized flight path instruction and a preset communication link quality parameter, screening out stable relay nodes from a preset relay node set, and generating a relay node update list meeting a preset stability condition; and performing topology reconstruction on the communication connection relationship between the nodes of the unmanned aerial vehicle cluster to generate a communication topology reconstruction instruction. According to the invention, cross-domain cooperation of physical path obstacle avoidance and communication topology stability of the unmanned aerial vehicle cluster in a high-speed motion scene is realized, and the cluster anti-interference capability and task continuity in a dynamic environment are significantly improved.

The invention discloses a charging method and system based on battery dynamic health state evaluation and learning prediction, belongs to the technical field of electric vehicle charging, and aims to solve the technical problem of how to break through a traditional BMS information barrier, realize deep perception and accurate prediction of a microcosmic dynamic health state in a battery, and improve the charging efficiency. According to the technical scheme, when the electric vehicle is connected to a charging pile, the charging pile establishes a communication link with a BMS (battery management system) of the vehicle through a standard protocol; a current or voltage disturbance signal with a specific frequency spectrum is injected into the battery, a response signal of the battery is measured synchronously, and dynamic health state parameters of the battery of the electric vehicle are collected in real time; and analyzing the dynamic health state parameters of the battery of the electric vehicle by using a pre-trained deep learning model, predicting the health state evolution trend of the battery, and generating a multi-target charging parameter optimization scheme.

The invention relates to the technical field of intelligent power supplies, in particular to an intelligent power supply for an unattended station. Comprising a multi-source power supply scheduling unit; an intelligent energy storage management unit; a double-link communication unit; the double-link communication unit is used for constructing a multi-redundancy communication link of wired, wireless and power line carriers, and the double-link communication unit is based on link quality data, adopts an automatic switching strategy to guarantee data transmission continuity, preprocesses monitoring data by using an edge side data clustering algorithm, and realizes offline data caching and transmission flow optimization. Through a multi-source energy dynamic scheduling strategy, according to photovoltaic real-time output, commercial power time-of-use electricity price and load electricity demand, power supply paths of photovoltaic, commercial power and a storage battery can be dynamically optimized, the consumption proportion of clean energy is improved, the dependency degree of high-cost commercial power is reduced, a complex energy structure of photovoltaic, commercial power and storage battery multi-energy complementation is effectively adapted, and the energy utilization rate is improved. And power supply flexibility is enhanced.