620 results about "Area network" patented technology

The invention discloses a method for generating an autonomous inspection orthoimage of an unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicle surveying and mapping and autonomous navigation. Global optimization of an air route is realized through a path optimization strategy fused by a genetic algorithm in combination with grid characteristics of an inspection area and image parameter constraints, and candidate waypoints are used as nodes; redundant waypoints are screened through leg smoothness factors, route complexity is reduced, a genetic algorithm takes flight height and waypoint spacing as constraints, a fitness function containing flight distance, turning times and overlapping rate is constructed, a global optimal path is found through population iteration, multi-target requirements are optimized and balanced, and it is ensured that the route meets the image acquisition precision requirement and also meets the requirement of image acquisition. The flight distance can be shortened, the turning frequency is reduced, the cruising ability of the unmanned aerial vehicle is adapted, efficient propelling of the inspection task is guaranteed, meanwhile, waypoint coordinates output through simulation directly adapt to a flight control system, and it is guaranteed that actual flight parameters are consistent with planning parameters.

The invention provides a double-pulse high-frequency switching power supply control method and system for precise electroplating, and relates to the field of electroplating, and the method comprises the steps: collecting area surface data through a three-dimensional scanner, and obtaining a three-dimensional model; extracting a high-curvature area grid according to the three-dimensional model, and calculating to obtain a surface concave-convex degree index; performing current field simulation, and calculating current density vector distribution; when the deviation of the current density vector distribution exceeds a preset deviation threshold value, pulse parameters are optimized through a genetic algorithm; selecting a pulse parameter which is most matched with the surface concave-convex degree index, and carrying out iterative calculation to obtain updated current density vector distribution; based on the difference between the updated current density vector distribution and the initial distribution, predicting a coating thickness value, and determining a preliminary evaluation index; and optimizing pulse parameters to obtain a final control scheme of uniform current distribution. According to the method, pulse parameters can be dynamically optimized according to the geometrical shape of the workpiece, and uniform current distribution and stable plating quality are realized.

The invention discloses a method and a system for processing route planning data for electric power line inspection. The method comprises the following steps: acquiring line distribution and topographic feature data; gridding the power network region, determining the patrol priority, and generating a region priority sequence; the overall patrol task is decomposed, a plurality of task subsets are generated, one task is allocated to each unmanned aerial vehicle, and each task subset comprises an initial position and a target line section; generating an initial route path based on the topographic features; comprehensively analyzing all initial paths, identifying potential airspace intersections and performing conflict prediction, and generating a conflict-free route path set by performing height hierarchical adjustment on related paths; and calculating predicted flight time and energy consumption of each unmanned aerial vehicle, redistributing boundary tasks according to a load balancing principle, and finally generating a balanced multi-unmanned aerial vehicle cooperative route scheme. According to the method, the safe and efficient multi-machine collaborative inspection route can be automatically generated through systematic task decomposition, conflict prediction and load balancing optimization.

The invention relates to the technical field related to automatic driving, in particular to a trajectory prediction method based on adaptive interaction and dynamic intention, which comprises the following steps: firstly, constructing a heterogeneous interaction map, dividing a traffic scene into a vehicle grid, an environment grid and a non-driving area grid, and embedding multi-dimensional dynamic features; then dynamically adjusting a region of interest based on the behavior intention of the target vehicle, and extracting a high-correlation interaction subnet; modeling an interaction relationship by adopting a heterogeneous graph convolutional network, and processing the motion characteristics of the target vehicle and the neighbor vehicle through a sub-channel coding strategy; further realizing dynamic intention perception through a double-branch parallel attention architecture, and fusing macroscopic intention and dynamic intention information; and finally, iteratively generating a future trajectory prediction result based on a decoding architecture of a message passing mechanism. The method can effectively improve the long-term prediction performance in a lane changing scene, adaptively captures a dynamic interaction relationship, and improves the adaptability of a prediction system to the behavior intention change of a driver.

The invention discloses an electric power measurement data management system based on cloud edge collaboration and an electric quantity distributed acquisition method, and relates to the technical field of electric power information acquisition and processing. The system comprises an intelligent electric meter terminal layer, an edge computing node layer, a regional collaborative gateway layer and a cloud data center. The intelligent terminal can dynamically adjust the sampling frequency according to the load change rate and the historical volatility, and identifies abnormity through an LSTM-ATT model; the edge nodes realize prediction caching based on Kalman filtering and RMSE judgment; the regional gateway executes dynamic time warping and consistency arbitration of topological weighting; and the cloud end completes digital twinborn modeling and exception evidence storage. According to the method, the real-time performance and accuracy of electric power data acquisition are improved, the communication bandwidth occupation is reduced, the system abnormity sensing capability and the operation stability are enhanced, and the method is suitable for an intelligent power distribution network and a distributed energy metering scene.

The invention relates to the field of vehicle-mounted bus testing, and discloses a vehicle-mounted CAN bus terminal resistor configuration method and system for node testing, and the method comprises the steps: obtaining a node identifier and a terminal resistor identifier corresponding to each test node in a vehicle-mounted CAN bus test, the terminal resistor identifier being used for identifying the terminal resistor access state of the test node; obtaining a first node position of a first test node corresponding to the first node identifier, configuring a terminal resistor for the first test node when the first node position is an end node of the vehicle-mounted CAN bus, and canceling the configured terminal resistor for the test node of a non-end node; and updating the terminal resistor identifier of each test node according to the terminal resistor access state corresponding to each test node. According to the invention, the terminal resistor can be automatically configured in the CAN bus test.

The invention belongs to the crossing field of space geodetics, satellite navigation positioning technology and atmospheric science, and discloses a real-time troposphere delay modeling method for enhancing a global forecasting system. The method comprises the following specific steps: firstly, acquiring zenith fluid static delay and zenith wet delay predicted by earth surface GFS, and constructing a regional grid difference time sequence by taking a fusion result of ERA5 data and a GNSS troposphere delay product as a reference; secondly, fitting the difference to form a GFS enhanced core model; meanwhile, a troposphere delay correction model from the grid height to the target site height is constructed based on ERA5 stratified atmosphere data, time sequence modeling is carried out on model coefficients, and finally refined troposphere delay output at different heights is achieved. The method has the advantages that (1) the real-time troposphere model is high in precision; (2) real-time application can keep robust performance without depending on a GNSS network; (3) expansion and deployment are facilitated; and (4) the real-time performance is strong, and seamless integration precision positioning application can be realized.

The invention provides a system and a method for generating CAN (Controller Area Network) mailbox configuration and data routing configuration based on a communication matrix table. The method comprises the following steps of: reading a predefined finished automobile CAN communication network signal routing information table; analyzing the whole vehicle CAN communication network signal routing information table to obtain CAN communication configuration parameters of each CAN channel; the number of receiving mailboxes and the number of sending mailboxes of each CAN channel are distributed according to the maximum number of receiving mailboxes and the maximum number of sending mailboxes supported by the whole vehicle CAN communication network hardware for each CAN channel and CAN communication configuration parameters of each CAN channel; and when the number of the messages to be processed of a certain CAN channel exceeds the allocated mailbox number, classifying the messages, and multiplexing the same mailbox by the messages belonging to the same class. According to the method, CAN mailbox resources are used to the greatest extent, and the reliability of data routing is ensured; when the whole vehicle communication network signal routing table is frequently changed, the reliability of the routing function is ensured, and meanwhile, the development efficiency is improved.

The invention provides a data transmission method and device, equipment and a storage medium. The data transmission method is applied to the controller, at least two buffer areas are arranged in the controller, and the data transmission method comprises the steps that in response to starting of a first timer, CAN data sent by external equipment through a CAN controller local area network bus is stored in the buffer area in an idle state in the at least two buffer areas; in the process of storing the CAN data through the buffer area in the idle state, forwarding the CAN data stored in the buffer area in the occupied state in the at least two buffer areas through a serial peripheral interface (SPI) bus; wherein the data transmission rate of the CAN bus is smaller than that of the SPI bus.

The invention relates to the technical field of cross-border trade settlement, and discloses a cross-border trade settlement risk prevention and control system based on a block chain smart contract, and the system comprises a regional network which serves as a distributed account book infrastructure and is used for storing and sharing the transaction data of all participants; the cross-border trade settlement risk prevention and control system comprises a block chain intelligent contract, a trusted data acquisition and uplink module used for acquiring and verifying off-chain entity trade data and uploading the verified trusted data to a local area network, and the off-chain entity trade data comprises logistics information sensed by Internet of Things equipment. The problem of traditional cross-border trade settlement pain points can be effectively solved, and fraud is prevented and controlled in the whole process by means of dual verification and intelligent contracts; a sharing platform is constructed through the block chain, an information island is broken, the settlement efficiency is greatly improved, and data security and traceability are guaranteed.

Operating effectively in an increasingly prolific Internet of Things environment, one needs the ability to message, whether device status, actions taken, recommendations for actions or other information to those with a need to know and support responses to actionable messages. Texts and e-mail are limited; they can neither provide other outputs, be targeted in intelligent fashion nor selectively relayed or contain execution instructions for target devices. The present invention is an Extended-Capability Messaging Appliance (ECMA) that communicates with other IoT devices that provides these capabilities and can include AI. ECMA and non-ECMA AI elements can constitute a Hybrid AI Backbone. The Hybrid AI Integrator receives results from multiple A elements and develops one or more conclusions. An ECMA may be configured as a Body-Area Network for individuals or a Business-Area Network for industry and other commercial applications with an AI Agent called BANDIT that processes requests from a user.

The invention discloses a regional grid safety evaluation method and device based on smart gas and a medium, belongs to the technical field of gas safety supervision, and aims to solve the technical problem of how to overcome the defects of insufficient matching between grid division and gas facility characteristics and lagging leakage risk prediction in the prior art. In order to realize full-process intelligence from risk identification to closed-loop management and improve supervision efficiency and early warning precision, the technical scheme adopted by the invention is as follows: dividing a pressure sensitive grid: performing optimization division on a regional grid based on a gas pipeline pressure grade and facility distribution characteristics, and realizing accurate division of the regional grid where a pipe network is located by combining a GIS and an improved DBSCAN algorithm; acquiring three-level Internet of Things data: integrating sensor data of an unmanned aerial vehicle, a pipe network pressure device and a leakage monitoring device, and covering a full-link data system of a terminal sensing layer, an edge computing layer and a cloud storage layer; constructing a double-engine evaluation model; carrying out digital twinborn visualization; and scheduling the capability matrix.

Systems, methods and apparatus of vehicle control. For example, a vehicle includes: a multi-master serial bus (e.g., a controller area network (CAN) bus); electronic control units connected to the bus and configured to communicate with each other through the bus; a transceiver connected to the bus and configured to monitor communication traffic on the bus to generate inputs; and an artificial neural network configured to generate, based on the inputs, a classification of anomaly for the communication traffic on the bus. The vehicle is configured to apply a security measure in response to the classification of anomaly for the communication traffic on the bus.

The invention discloses an urban garbage classified collection and scheduling method based on the Internet of Things, and relates to the technical field of urban garbage classified collection, and the method comprises the steps: deploying an intelligent garbage can with the filling rate and environmental parameter perception capability in each region of a city, and uploading the collected state data to an edge gateway of the region through a low-power wide area network; the edge gateway performs localized priority evaluation based on the received real-time state data of each intelligent garbage can in combination with the capacity information, the last clearance time and the attribute of the area where the intelligent garbage can is located, and generates a dynamic priority score of each garbage can; when the dynamic priority score of any dustbin exceeds a preset response threshold value, the edge gateway triggers an event reporting mechanism and sends a clearance alarm containing position and priority information to a regional dispatching center; and on the basis of receiving the clearance alarm, the regional dispatching center combines weather forecast, festival calendar and regional people flow density data to carry out trend prediction on the garbage cans which are not alarmed yet and have high filling risks.

The present disclosure relates to the technical field of intelligent driving, in particular to a vehicle driving intelligent assistance system, which includes an electronic control unit and a Controller Area Network (CAN) module, wherein the CAN module is connected with a driving detection module, a vehicle body state detection module, an engine detection module and an environment detection module, wherein the vehicle body state detection module is configured to acquire a steering angle of a steering wheel and a suspension condition, the environment detection module is configured to acquire environmental information around the vehicle and road conditions; the electronic control unit is connected with a vehicle body stabilization system, a vehicle control system and a lane departure early warning module, and the vehicle control system is configured to control acceleration, steering or braking of a vehicle to achieve assisted driving.

A system is provided for generating artificial intelligence based visualizations of computing device security and stability. In particular, the system may aggregate various types of data and metrics related to the operational performance, security, and stability of the computing devices and applications within an entity's computing environments. Based on the aggregated data, the system may use an artificial intelligence engine to determine whether a particular area, network, application, or device may be vulnerable. Based on analyzing the data, the system may generate one or more visualizations of the data that reflect the current state of the entity's computing environment as a whole. The system may further be configured to transmit notifications to one or more relevant users associated with the applications or devices subject to the vulnerabilities.

The invention provides an air-space-ground integrated network switching method, device and equipment and a storage medium, and relates to the technical field of communication, and the air-space-ground integrated network switching method comprises the steps: obtaining the movement track information of mobile equipment, the moving track information comprises the current position of the mobile equipment and the position of the mobile equipment within a first preset duration after the current time; acquiring first network state information of the air-space-ground integrated network, wherein the first network state information comprises current network state information of the air-space-ground integrated network and network state information of the air-space-ground integrated network within a first preset duration after the current time; and according to the moving track information and the first network state information, switching a connection network of the mobile equipment from the first regional network to a second regional network in a moving process of the mobile equipment. According to the invention, the seamless switching technology of the space-air-ground integrated network can be realized, and rapid and stable switching among different networks can be realized.

The invention requests to protect a network intrusion detection method based on a CKAN-BiLSTM (Content Kernel Area Network-BiLSTM). The method comprises the following steps: firstly, selecting an NSL-KDD data set widely applied in the field of network security, and performing preprocessing operation on the NSL-KDD data set to improve data quality and a model training effect; then, feature extraction is carried out on input data through a convolutional layer, size adjustment is carried out on features in combination with an adaptive pooling mechanism, and the perception ability of the model to a local mode is enhanced; secondly, inputting the extracted features into a BiLSTM network to fully capture a time sequence dependency relationship in the BiLSTM network; and finally, Kolmogorov-Arnold Network (KAN) is introduced to carry out weighted fusion on the key features, final attack type classification is completed, and efficient and accurate intrusion detection is realized.

The present application relates to a control circuit, a wake-up and sleep method, a battery management system, and a vehicle. The control circuit includes a controller area network (CAN) transceiver and a signal circuit connected to each other, and the signal circuit is connected to both an external controlled device and a controller; the CAN transceiver is configured to output a first control signal to the signal circuit according to a CAN bus message; and the signal circuit is configured to output a wake-up signal to the controlled device according to the first control signal, and output a sleep signal to the controlled device according to a second control signal output by the controller.

The invention discloses a circuit breaker performance simulation method and system based on a dynamic grid algorithm, and belongs to the technical field of circuit breaker performance simulation. Simulation is focused on a simulation area by constructing a three-dimensional model of a circuit breaker and carrying out geometric topology partitioning, redundancy calculation is reduced, and then the circuit breaker performance simulation method and system based on the dynamic grid algorithm are obtained by constructing a regional network framework. The motion characteristics of the circuit breaker are adapted through self-adaptive grading and a grid dynamic subdivision mechanism, so that the stability of a computational domain boundary can be maintained in a high-speed opening scene of the circuit breaker, and the accuracy of a final simulation result is improved; the problem that the reliability of a simulation result is low due to the fact that a high-speed opening scene is difficult to simulate accurately during performance simulation of an existing circuit breaker is solved.

The invention provides a fault repair and task unloading optimization method under a space-air-ground fusion vehicle-mounted network framework, and belongs to the technical field of Internet of Vehicles. According to the first stage, the optimal deployment point location of the unmanned aerial vehicle is searched globally based on the wolf pack algorithm, the flight path is planned dynamically in combination with the near-end strategy optimization algorithm, and network connectivity repair of a fault area is achieved; and in the second stage, a task unloading decision initial population is generated through multiple deep reinforcement learning agents, and a Pareto optimal solution set is obtained through optimization of a non-dominated sorting genetic algorithm II, so that multi-target balance of energy consumption, cost and time delay is realized. According to the method, the fault self-healing capability and task processing efficiency of the SAGVN can be remarkably improved, and the method adapts to the high-dynamic and high-reliability requirements of intelligent traffic.

The invention discloses a leakage monitoring method based on an LNG fuel gas system. The leakage monitoring method comprises the steps that a self-adaptive frequency modulation continuous wave active acoustic scanning network is established; blind source separation is carried out on mixed signals in acoustic scanning network abnormal events by adopting self-adaptive kernel independent component analysis; constructing a leakage feature mapping model of the physical information neural network; leakage source accurate positioning and quantification based on acoustic tomography and Bayesian reasoning are carried out; multi-modal decision fusion is carried out based on the multi-dimensional data sources received in parallel, a false alarm suppression mechanism is set, and time continuity verification and space consistency verification are carried out; establishing a reinforcement learning model for autonomously optimizing a monitoring strategy according to environment change and system state, and realizing adaptive optimization; the strategy network after self-adaptive optimization is deployed at the cloud, actions are generated regularly according to the current state, the actions are issued to the regional gateway and the edge node for execution, and iterative updating is carried out, so that the monitoring accuracy in a complex environment is improved, and the false alarm rate is reduced.

The invention discloses a power distribution area energy storage-photovoltaic oscillation cooperative suppression method based on impedance remodeling, and belongs to the technical field of power system stability control. According to the method, the impedance characteristic of the system is scanned online in real time, the virtual impedance controller parameters of the photovoltaic inverter are dynamically optimized, and the impedance frequency characteristic of the zone area network is actively remodeled, so that the zone area network is always far away from a stable critical point, and oscillation is prevented from occurring from the source. When it is detected that the oscillation energy exceeds the standard, the system immediately triggers the energy storage device to be switched to a virtual synchronous generator mode, phase information of a plurality of energy storage units in a fiber channel synchronization cluster is used, anti-phase damping current opposite to the oscillation trend is injected, and the oscillation energy is rapidly consumed. The invention provides a double-layer suppression strategy based on impedance remodeling and energy storage cooperation, the cooperation of photovoltaic impedance active prevention and energy storage instantaneous suppression is realized, the problem that a traditional fixed parameter damper loses efficacy due to frequency drift is solved, and the operation stability of a high-proportion renewable energy power distribution network is improved.

A synchronized wireless network includes a root coordinator and any number of other coordinators that are synchronized with the root coordinator, e.g., according to a communication schedule established by the root coordinator and transmitted to the other coordinators in one or more beacons. The other coordinators coordinate operations of individual area networks by establishing communication schedules for the respective area networks, and transmitting beacons including such other schedules to any number of nodes of such networks. Upon detecting a loss of connectivity with the root coordinator, coordinators or nodes of area networks monitor channels and timeslots for beacons transmitted by other coordinators of the synchronized wireless network, and elect one of their own to serve as a root coordinator, or select one of the other coordinators for synchronization, based on contents of such beacons.

Various implementations include audio systems and related approaches for providing road noise cancelation (RNC). Certain implementations include a method of training a machine learning (ML) based road noise cancelation (RNC) system for a vehicle, the method including: providing inputs to the ML based RNC system, the inputs obtained from: a set of ear-mounted microphones on a user of the vehicle, at least one transducer, an accelerometer, a set of cabin microphones in the vehicle, and a controller area network (CAN) bus, wherein the inputs from the set of ear-mounted microphones on the user approximate detected road noise by the user; adapting a set of parameters defining noise cancelation signals in the ML based RNC system based on the inputs; and generating noise cancelation signals for output by the at least one transducer based on the adapted set of parameters.

The invention relates to a rice transplanter steering automatic lifting control system based on a geomagnetic principle, and the system comprises a geomagnetic sensor which is disposed on a frame of a rice transplanter, is used for detecting the steering angle of a vehicle body, and is connected with a transplanting part lifting controller through a CAN bus; the sensitivity adjusting knob is electrically connected with the transplanting part lifting controller and is used for setting a steering action triggering angle; the lifting motor is connected with the transplanting part lifting controller through a full-bridge circuit; the planting part lifting controller is used for receiving a steering angle signal of the geomagnetic sensor and controlling the positive and negative rotation of the lifting motor according to a trigger angle set by the sensitivity adjusting knob; and the intelligent instrument is communicated with the transplanting part lifting controller through a CAN (Controller Area Network) bus and displays the working state of the system in real time. The system is simple, easy to install, low in cost, wide in application scene and good in compatibility, is not only suitable for rice transplanters, but also can be popularized to other agricultural machines, realizes related automatic actions during steering, and has a good application effect and a good market prospect.

Apparatuses and computer-implemented methods for implementing a message-based protocol interface with a communication bus are provided. An example apparatus for implementing a message-based protocol interface with a communication bus may include message handler core circuitry having a transmit message buffer, wherein the transmit message buffer is configured to store a portion of a transmit message. The apparatus may further include receive handler circuitry configured to store a portion of a received message. The apparatus further includes a message handler processor comprising a processor and an instruction memory including program code, the instruction memory and program code configured to, with the processor, cause the message handler processor to transmit at least the portion of the transmit message from a transmit data memory to the message handler core circuitry and receive the received message from the receive handler circuitry into a receive data memory.

The invention relates to the technical field of data processing, in particular to an agricultural space function zoning planning system which comprises a plot division module, a function association module, a matrix arrangement module, a function suitability acquisition module, a function zoning module and an agricultural space planning module. Mapping the agricultural resource data to generate an agricultural functional plot; performing weighted fusion on the internal constraint vector and the external demand vector of the land parcel to obtain a function correlation degree, constructing a dynamic coupling relation matrix, and calculating suitability indexes of various preset agricultural functions according to the function correlation degree; the method comprises the following steps of: initializing a partition agent to form an initial agricultural space function partition scheme by taking maximization of overall suitability of a region and meeting of space connectivity as targets, and iterating by taking space compactness, function homogeneity and adjacent unit coordination as optimization targets to finally generate an agricultural space planning map; according to the invention, the zoning planning efficiency of agricultural space functions can be improved.

The present invention relates to a workshop monitoring arrangement (1) for vehicle localization and service monitoring, comprising: a) at least one service area network anchor (2) in a service area (7) for communication with at least one vehicle network anchor (3) in a vehicle (4), b) a control unit (5) for controlling the at least one service area network anchor (2) and for communication with the at least one vehicle network anchor (3), c) a data transfer unit (6) coupled to the control unit (5) and configured to transmit the location of the vehicle (4) and / or the service progress to the vehicle owner (10), wherein the workshop monitoring arrangement (1) is configured to track the location of the vehicle (4) in real time and to monitor service progress, the network being configured as a BLE and / or UWB network. The present invention further relates to a workshop monitoring method.

Various implementations include a method of training a road noise cancelation (RNC) system for a vehicle, including: providing inputs to RNC system, the inputs obtained from: a set of ear-mounted microphones on a user, at least one transducer, an accelerometer, a set of cabin microphones in the vehicle, and a controller area network (CAN) bus, the inputs from the set of ear-mounted microphones on the user approximating a signal detected by the ears of the user; adapting a set of parameters in the RNC system defining an estimated signal detected at respective ears of the user based on the inputs; and generating at least one of the following for input during an operating mode of the RNC system: estimated ear microphone signals based on the adapted set of parameters, or a set of projection filters for use in determining an estimated ear signal at the respective ears of the user.