144results about How to "Resolve delay" patented technology

The invention discloses an unmanned aerial vehicle control method and system, relates to the technical field of flight path control, and solves the problems of insufficient image acquisition precision, inaccurate routing inspection path planning and limited real-time data analysis capability. Through an image acquisition and enhancement module, a real-time image enhancement algorithm and a multi-image comparative analysis module, the focal length and exposure parameters of a camera are dynamically adjusted, the image definition in a complex environment is improved in combination with evaluation of an image enhancement effect value Enh and an effect threshold E, and a dimensionless size value Fdz, a position value Fdw and a relative distance value Fjl of a fault point are extracted; the image acquisition quality is effectively controlled; the environment modeling module is used for generating a three-dimensional model containing cable and obstacle information, ensuring that the path coverage value Qcd reaches the standard and avoiding an inspection blind area; and an airborne data processing mechanism is combined with an electromagnetic interference prediction and collision prediction model, so that real-time fault analysis and alarm are realized, the detection efficiency is improved, and the data real-time performance is ensured.

The invention relates to the field of graphic rendering, in particular to a high-efficiency graphic rendering system based on artificial intelligence core computing power, which comprises an intelligent task decoupling module for performing task decoupling on a graphic rendering task; the AI enhanced texture generation optimization module is used for learning a dynamic scene change rule to generate a texture map in real time, reducing calculation overhead in a repeated texture region by using a multiplexing algorithm, and performing super-resolution compensation on low-resolution textures by using a deep convolutional neural network; the AI driving illumination and shadow calculation module is used for predicting an illumination transmission path in a scene by using AI and reconstructing a dynamic shadow effect so as to realize high global illumination and shadow simulation; the task result synchronization module is used for synchronizing rendering data output by each subtask; according to the method, the high-quality texture map is dynamically generated, super-resolution compensation is carried out on the low-resolution texture, repeated calculation is avoided through a texture multiplexing algorithm, the calculation overhead is remarkably reduced, and the real-time rendering efficiency of a large-scale complex scene is improved.

The invention provides a micro-nano impact press-in tester operation monitoring system based on digital twinning, and is suitable for the field of precise instrument maintenance. The system realizes multi-physical field coupling modeling in a micro-nano press-in test through a digital twinning technology, and can monitor the state of an instrument in real time with high precision, predict faults and perform dynamic optimization. The system is integrated with a high-precision sensor, data such as micro force, extremely high temperature and nanoscale displacement are collected in real time, a digital twin model is constructed, and the operation state of an instrument is mapped. Historical and real-time data are analyzed by means of a machine learning algorithm, potential faults can be accurately predicted, maintenance suggestions can be provided, and the precision retentivity and the test stability of the instrument under the material service working condition are ensured. The interaction center provides a visual interface, supports real-time monitoring, dynamic adjustment and early warning functions, and remarkably improves the intelligent maintenance level of the instrument. The invention is suitable for the fields of material science, micro-nano mechanical test and the like, and provides an innovative precise instrument intelligent management scheme.

The invention discloses a general thermal power plant machine room DCS equipment data transmission method, equipment, a medium and a product, and relates to the field of data transmission, and the method comprises the steps: after a configuration file is defined, analyzing the configuration file, building a connection with general thermal power plant machine room DCS equipment according to a communication parameter and a mapping table, and based on a user request, according to a to-be-acquired data item list, obtaining a data item list; and reading data from the general thermal power plant machine room DCS equipment to obtain original data, processing the original data based on regulations of a communication protocol, and setting a retransmission mechanism and an error processing mechanism to obtain a data reading result. According to the application, the increase and decrease of the data volume become more convenient, the problems of delay and low efficiency in the big data transmission process can be solved, and the problem of data loss or damage caused by the influence of noise and interference is avoided.

The invention provides a dangerous rock mass crack monitoring system and method based on the Zigbee technology, and belongs to the technical field of geological disaster monitoring, and the system comprises a plurality of terminal nodes, at least one coordinator node, an edge computing device and a remote monitoring center. The plurality of terminal nodes comprise a crack data acquisition module for acquiring crack data of crack widths, depths and change rates of a plurality of monitoring points of the dangerous rock mass in real time; the Zigbee wireless communication module is used for wireless transmission; the self-adaptive control module is used for adjusting the data acquisition frequency and the transmission interval according to the crack change rate of the monitoring point; the coordinator node is used for receiving crack data of a plurality of monitoring points; the edge computing device is used for analyzing a danger signal in the crack data by adopting the trained machine learning model and generating a real-time early warning signal; and the remote monitoring center is used for receiving, displaying and storing the analysis result and the early warning signal. According to the method, low-power-consumption and long-distance dangerous rock mass crack monitoring can be achieved, and long-term and stable operation is achieved.

The invention discloses a smart campus management method and system based on big data, and particularly relates to the technical field of data management. The method comprises the following steps: deploying various types and numbers of sensors, collecting delay and throughput data in a peak period in real time in different monitoring areas in a campus, carrying out preprocessing and feature extraction on the data, and respectively extracting a delay abnormal fluctuation trend and a sudden reduction feature of a throughput decline rate; a machine learning model is constructed to predict a real-time response capability value of the smart campus management system, and the real-time response capability value is compared with a preset standard threshold value, so that the real-time response capability of the system is divided into high, medium and low levels, the system can take corresponding measures for different levels of response capabilities, and the real-time response capability of the smart campus management system is improved. The problems of data processing delay and unstable system response capability in a smart campus in the big data era can be effectively solved, the real-time performance, reliability and flexibility of the system are improved, and efficient operation of the campus management system in peak periods or large-scale activities is ensured.

The invention relates to the field of network security monitoring, in particular to a network security threat monitoring method based on deep learning, which comprises the following steps: collecting flow data on a network node, and preprocessing the collected flow data; constructing a deep neural network model to analyze the flow data, and adjusting model parameters through an optimization algorithm to minimize a loss function; evaluating the network security threat according to an output result of the deep learning model; determining response measures according to the threat assessment result, and taking corresponding response operations for different threat levels; according to the method, the timeliness of the response is evaluated according to the time interval from threat detection to response measure implementation, the deep neural network is utilized, the deep features can be automatically extracted from the network flow, and the recognition precision of the complex attack mode is remarkably improved. Compared with a traditional rule-based detection method and a simple machine learning algorithm, the scheme can effectively reduce the false report rate and the missing report rate, and improve the accuracy of network threat monitoring.

The invention provides a PI consistency-based secondary control method for a P / V energy storage converter, and the method comprises the steps: generating an output signal of a secondary controller through a PI consistency algorithm according to the power state variables of each distributed power supply and all distributed power supplies communicating with the distributed power supply; compensating and correcting the P / V droop control equation based on the output signal to obtain a voltage reference value and an angular frequency reference value; based on the voltage reference value, a modulation signal is obtained through an internal control loop; and on the basis of the modulation signal and the angular frequency reference value, through Park transformation and SPWM modulation, an on-off control signal of an inverter switching tube is obtained, and distributed secondary control of the converter is completed. By adopting the secondary control method based on the PI consistency algorithm, the active power sharing among the distributed energy storage units and the recovery of the voltage and the frequency of the power distribution network can be realized, and the power sharing error caused by the line impedance is eliminated.

The invention belongs to the technical field of AIGC, and discloses an AIGC side-end collaborative reasoning method based on a diffusion model, and the method comprises the following steps: S1, constructing a multi-exit U-Net network, and achieving a multi-exit mechanism; s2, designing a decision strategy of a collaborative reasoning service problem based on a learning algorithm of deep reinforcement learning; s3, designing an attention-based state embedding strategy network, and further improving the state sensing capability of the strategy network in the diffusion process; and S4, evaluating the energy consumption of the model and the quality of the generated image. According to the AIGC edge-end collaborative reasoning method based on the diffusion model, reasoning accuracy and processing time are effectively balanced, generation quality and energy efficiency are improved, content quality and energy use are optimized in a dynamic edge environment, efficient and energy-saving diffusion model reasoning on edge equipment is achieved, and the efficiency of the AIGC edge-end collaborative reasoning method based on the diffusion model is improved. And the overall performance and the user experience of the Internet of Things application are improved.

The invention discloses a reinforcement learning-based time rule identification intelligent unloading optimization method. The method comprises the steps of obtaining vehicle, equipment and task state information parked in a parking lot; constructing a Markov process based on parked vehicles, equipment and task state information; and carrying out intelligent calculation unloading optimization on vehicles parked in the parking lot based on the Markov process. According to the method, the time rule of the task can be accurately captured, the system service time and energy consumption cost are reduced, and calculation unloading optimization is realized.

The invention relates to an unmanned aerial vehicle-mounted investigation and rapid interference method. The method comprises the steps of searching a frequency band where a radar target is located; after the radar frequency band is successfully locked, the equipment processes the analysis and interference functions of the radar signal in parallel, and judges and executes a corresponding interference strategy according to an analysis result; interference strategies are selected step by step according to stages: a device scans radar signals at an interval of 200MHz to complete a target search stage; when the center frequency of the radar signal is locked, entering a target tracking stage; after locking, entering a target optimization stage; if the center frequency changes, entering a target re-search stage, and trying to re-lock the signal; in each stage, the equipment adopts different interference modes: a full forwarding interference mode is used in a target search stage, a slice interference mode is used in a target tracking stage, and a random interference mode is switched in a target re-search stage. According to the method, the dependence on an external independent reconnaissance system and resource scheduling is remarkably reduced, and the load requirements of miniaturization and light weight of the unmanned aerial vehicle are met.

The invention discloses a financial flow situation awareness system and method based on a multi-modal large model, and relates to the technical field of supply chain financial risk control. Aiming at the problems of data isolation, high processing delay and risk perception lagging in the existing storage pledge financing scene, the method comprises the following steps: obtaining a storage digital planar graph, dividing logic sub-regions, collecting and processing multi-source data of each sub-region in parallel, and extracting pledge stock time sequence data and warehouse receipt information by utilizing a visual and text model respectively; constructing a sub-region association map by taking the cargo identifier as a node and fusing the fund flow; and fusing all the sub-maps to construct a global association map, performing cross-regional consistency verification and anomaly recognition, generating a dynamic risk judgment result, and outputting hierarchical situation awareness information. According to the invention, accurate association and panoramic risk perception of the "object-bill-money" state are realized, and the real-time performance and accuracy of risk identification and the expandability of the system are improved.

The invention relates to the technical field of over-the-horizon remote control mobile robots, in particular to an over-the-horizon remote control mobile robot low-delay double-view-angle control system and method, and the system comprises a mobile robot end and a remote control end, and the mobile robot end comprises a fisheye lens group and an image fusion processing module; the fisheye lens group captures a 360-degree panoramic image, the image fusion processing module preprocesses image data, generates a panoramic video stream in real time through an image fusion algorithm, and transmits the panoramic video stream to the remote control end through the communication module; and the remote control end performs selective double-view-angle display, and adjusts the observation view angle in real time based on the head action of the user or a manual instruction. The data transmission quantity is reduced, the video quality is ensured, the transmission efficiency is improved, the stable transmission of the panoramic video stream is ensured, the delay and packet loss phenomena are reduced, the time delay problem is solved, and the real-time performance and comfort of control are better.

The invention relates to image processing and video monitoring, in particular to a real-time target tracking method and system based on double-camera linkage, and the method comprises the steps: initializing the system and defining a coordinate system; when the target enters the high-definition picture of the high-definition zoom camera, judging whether the target enters the field of view of the wide-angle fixed-focus camera or not in real time; if the target enters the view field of the wide-angle fixed-focus camera, guiding the high-definition zoom camera to turn to the target by using the large view field advantage of the wide angle, and carrying out picture fusion and asymmetric weight ROI video coding; if the target does not enter the field of view of the wide-angle fixed-focus camera, starting an independent closed-loop PID tracking mode for the high-definition zoom camera, and gradually switching the high-definition zoom camera from the wide-angle end to the long-focus end to realize stable locking of the target in a full-focus range; according to the technical scheme provided by the invention, the defect that the moving target is difficult to accurately track in the prior art can be effectively overcome.

The invention relates to the technical field of operation identification, in particular to a medium-voltage power distribution network transfer operation identification method, system and device. The method comprises the following steps: acquiring feeder line real-time data and transformer area real-time data; performing data preprocessing on the feeder line real-time data and the transformer area real-time data to generate a transformer area feeder line processing data set; acquiring a power grid historical data set; performing two-dimensional curve fitting analysis on the power grid historical data set and the area feeder line processing data set to generate area feeder line two-dimensional fitting data; carrying out abnormal and disharmony area judgment on the two-dimensional fitting data of the feeder line in the transformer area, and generating load fluctuation voltage abnormal data; therefore, through a data-driven multi-level analysis and judgment method, the problems of dependence on artificial experience, response lag and the like in the traditional power grid transfer operation are solved, and the intelligent level and decision accuracy of the medium-voltage power distribution network transfer operation are improved.

The invention discloses a method for processing MIPI D-PHY receiving end signal delay difference, and belongs to the field of high-speed serial buses. One FIFO is placed behind the PPI at the receiving end of each data channel in the MIPI D-PHY; rxSyncHs signals are respectively used for resetting, and RxValidHs signals are respectively used as conditions for writing data into FIFO (First In First Out). According to the invention, the delay problem of the MIPI D-PHY interface in data transmission can be effectively solved, the reliability and stability of the MIPI D-PHY interface are improved, and the MIPI D-PHY interface has great market potential and application value.

The embodiment of the present invention is about a method and device for processing a workflow, a storage medium, and an electronic device, and relates to the field of computer technology. The method includes: receiving a processing request including a workflow to be processed, responding to the processing request to determine whether there is process definition information corresponding to the workflow to be processed in a local cache pool; when it is determined that there is a process definition corresponding to the workflow to be processed in the local cache pool, executing the workflow to be processed according to the process definition information; when it is determined that there is no process definition information corresponding to the workflow to be processed in the local cache pool, obtaining the process definition information corresponding to the workflow to be processed from a distributed cache cluster, and executing the workflow to be processed according to the process definition information. The embodiment of the present invention improves the efficiency of executing the workflow to be processed.

The application discloses an unmanned vehicle motion control method and system based on an electronic and electrical information architecture, relates to the technical field of automatic driving, and comprises the following steps: acquiring vehicle state information and vehicle parameters of an unmanned vehicle; establishing a kinematic model of the unmanned vehicle according to the vehicle state information; establishing an adaptive three-loop collision detection model of the unmanned vehicle according to the vehicle parameters; based on the kinematic model, the adaptive three-loop collision detection model and an electronic and electrical architecture model, adopting a multi-hop loop delay analysis method to estimate the cumulative loop delay of multiple nodes and links in the electronic and electrical architecture, and obtaining boundary numerical values of loop delay; and based on the boundary numerical values of loop delay, adopting an improved double reinforcement learning algorithm to control and train the unmanned vehicle, and obtaining a motion control model of the unmanned vehicle. The application solves the problem of loop delay of the heterogeneous topology of the electronic and electrical architecture, and ensures the control stability and high efficiency of the unmanned vehicle in path tracking and safe obstacle avoidance.

The invention provides a new energy system operation state monitoring analysis method and device based on a multi-level structure and a storage medium, and relates to the technical field of data monitoring analysis. The method comprises the following steps: dividing acquired data of a new energy monitoring system according to a preset hierarchical structure to obtain hierarchical structure data; constructing the hierarchical structure into a hierarchical data model through a dynamic time sequence modeling algorithm; constructing a cross-regional panoramic monitoring graph, and performing optimization scheduling of regional hierarchical data in combination with a dynamic network optimization algorithm; and collecting real-time data of the new energy access point through an incremental data synchronization algorithm, performing data analysis on the new energy access point, and generating an analysis result. By introducing hierarchical data modeling, dynamic data synchronization, incremental data processing and panoramic modeling, the data management flexibility, the real-time monitoring precision, the cross-regional data synchronization and scheduling efficiency and the risk assessment and abnormal response capability of the new energy monitoring system are remarkably improved.

The invention discloses a method for processing delay difference of data sent by an MIPI D-PHY sending end, and belongs to the field of high-speed serial buses, an FIFO is placed in front of a PPI of the sending end of each data channel, and a TxReady HS signal is used as a condition for reading the FIFO; when all the FIFOs are not full of the previous-stage circuit, a new group of data can be written into the FIFOs at the same time, so that the D-PHY upper-layer circuit can process the data of each data channel at the same time, and the circuit is simple and convenient to use. According to the invention, the delay problem of the MIPI D-PHY interface in data transmission can be effectively solved, the reliability and stability of the MIPI D-PHY interface are improved, and the MIPI D-PHY interface has great market potential and application value.

The invention provides a pavement height difference adjusting device for a paver, which comprises a paving main body, a first ironing mechanism arranged on one side of the paving main body, and a monitoring mechanism, the monitoring mechanism comprises a fixing piece arranged on the first ironing mechanism, an induction plate arranged at an interval with the fixing piece and used for making contact with a paving pavement, and an adjusting rod arranged between the fixing piece and the induction plate, a controller is arranged in the fixing piece, and the controller is connected with the controller. And the controller is configured to be capable of judging the height difference of a paved pavement formed by the paving main body and the first ironing mechanism through an included angle formed by the induction plate and the adjusting rod.

The invention provides a directional neighbor discovery method and device based on asynchronous scanning and electronic equipment, and belongs to the technical field of communication, and the method comprises the steps: obtaining node cluster neighbor information; the neighbor information of the node cluster is input into a target function, the optimal solution of the target function is iteratively calculated based on constraint conditions, target configuration parameters corresponding to the optimal solution are obtained, and the target configuration parameters comprise a sector selection strategy and a listening time strategy of each node in the node cluster; the target function is used for minimizing the average neighbor discovery time of the neighbor discovery process or minimizing the average energy consumption of the neighbor discovery process; and controlling the node cluster to execute neighbor discovery based on the target configuration parameters. According to the directional neighbor discovery method based on asynchronous scanning provided by the invention, the technical problems of delay and relatively high energy consumption of a node cluster in a neighbor discovery process in a directional neighbor discovery method based on asynchronous scanning in related technologies are solved.

The invention belongs to the technical field of power equipment safety monitoring and intelligent sensing, and particularly relates to an overhead line bird repelling device and method based on multi-mode sensing dynamic fusion and edge calculation. The system comprises a sensing layer which is used for sensing the activity of birds around the overhead line and the ambient brightness in real time; the edge calculation layer is used for processing the data of the sensing layer by adopting a prediction model, outputting bird behavior prediction, and outputting a corresponding bird repelling strategy by adopting a self-adaptive bird repelling decision model according to the bird behavior prediction; the execution layer is used for executing bird repelling operation according to the bird repelling strategy and the ambient brightness; the power supply layer is used for supplying power. According to the bird repelling system, through combination of the microwave radar unit, the camera unit and the photosensitive sensor, multi-mode sensing dynamic fusion is formed to capture bird activities, a prediction model and a self-adaptive decision model are locally operated in combination with an edge calculation layer, bird behaviors are predicted in advance, response delay is compressed, and the bird repelling effect is improved. The delay problem caused by a traditional scheme depending on the cloud is solved.

The application discloses a self-adaptive multi-modal data fusion bridge health monitoring method and system, generates a response sample database through establishment of a bridge nonlinear dynamics equation, pre-processes bridge sensor data and trains a deep learning model to extract damage features, and self-adaptively optimizes model parameters; based on model output, real-time and historical data are combined to perform bridge health evaluation, and a monitoring strategy is dynamically adjusted or early warning is triggered; an edge computing device is deployed to perform pre-processing and damage identification, and long-term trend analysis is realized in cooperation with a cloud platform; macro-structure damage and micro-crack data are fused through cross-scale feature extraction; an artificial intelligence algorithm is used to generate a bridge health evaluation result, a bridge maintenance and repair scheme and a decision-level early warning signal. The application combines nonlinear dynamics modeling, self-adaptive deep learning, edge cloud collaborative computing and cross-scale analysis, improves complex damage identification precision and monitoring intelligent level, and is suitable for large-scale traffic network bridge monitoring management.

This utility model discloses a two-piece diving suit, relating to the field of diving suit technology. It includes a diving suit and diving pants, both with an inner protective layer. This protective layer comprises, from the inside out, a skin-friendly layer, a carbon nanotube heating film, a graphene textile fabric, a thermal insulation layer, microcapsules, a rubber layer, an air bladder, an inner lining, a mounting groove, and an outer layer. During use, the diver quickly puts on the two-piece diving suit and diving pants via a waterproof zipper. A water-sealed collar and waist seal form a sealed protective structure. A battery then powers the carbon nanotube heating film and graphene textile fabric, generating heat. This heat, combined with the microcapsule phase change material, regulates body temperature. During diving, the skin-friendly protective layer ensures comfort, and the graphene textile fabric assists in heat conduction. This device actively combats cold water environments, solving the problem of delayed insulation caused by traditional diving suits relying on heavy, passive materials.

This invention discloses a vehicle-mounted drone video automatic shooting and generation system and method, belonging to the field of drones. The system includes: a vehicle-side component, comprising a main control unit, a data communication gateway, a vehicle and environmental status perception module, an interactive interface, and a cabin power supply interface; a drone-side component, comprising an airborne controller, a communication module, a drone status perception module, and a shooting and flight module; and a cloud-side component, comprising a cloud server. Both the main control unit and the cloud server have built-in AI engines. The main control unit is connected to the data communication gateway, the vehicle and environmental status perception module, the interactive interface, and the cabin power supply interface; the airborne controller is connected to the communication module, the drone status perception module, and the shooting and flight module; and the data communication gateway is connected to the communication module and the cloud server. This invention enables fully automatic generation of high-quality videos in outdoor mobile scenarios.

The invention provides a new energy unit transient stability optimization method and system based on active feed-forward, and belongs to the field of new energy power generation. The system includes a current command generator and a current controller. The method comprises the steps of collecting terminal voltage and current of a unit, calculating active power and detecting a transient fault; when a fault is detected, generating an active current instruction through active feed-forward control based on power grid voltage information obtained by an active power signal, a fault voltage amplitude signal and phase locking; meanwhile, a reactive current instruction is generated; a current reference instruction is synthesized, and a converter is driven through closed-loop control to provide power support. According to the method, an active feed-forward mechanism is introduced, so that the new energy unit can respond to the power shortage of the power grid in advance, active and reactive support is quickly provided, frequency drop and power oscillation in the transient process are effectively inhibited, and the transient stability of the power system under the access of high-proportion new energy is remarkably improved.

The invention provides a paving pavement segment difference adjusting device. The paving pavement segment difference adjusting device comprises an ironing main body and a first telescopic main body arranged at the side end of the ironing main body, and a first ironing plate in contact with a paving pavement is arranged on the first telescopic main body; the monitoring mechanism comprises a first monitoring piece arranged on the ironing main body, a second monitoring piece arranged on the first telescopic main body, and a controller for recording an initial difference value between the first monitoring piece and the second monitoring piece; the controller is arranged on the ironing main body and connected with the first ironing plate, and the adjusting mechanism is arranged on the ironing main body and connected with the first ironing plate, when the difference value of the first monitoring part and the second monitoring part is changed, the controller can change the position of the first ironing plate through the adjusting mechanism, and the position of the second ironing plate is adjusted through the adjusting mechanism. Therefore, the height difference of the paved pavement formed by the ironing main body and the first telescopic main body is eliminated.

The application discloses a method for controlling the stop of an electric regulating valve and related devices, and relates to the technical field of nuclear power plant automation control. The method comprises the following steps: when a system-level command is received, a short-pulse stop command and an open command are synchronously output; a priority processing module is used to preferentially execute the short-pulse stop command, so that the electric regulating valve immediately terminates the current stroke and is kept at the current position. The method avoids the delay problem that, in a traditional control mode, the valve needs to complete the full-range action in the original direction to respond to a new instruction, significantly shortens the response time of the valve to the reverse safety instruction, and ensures that the safety action can be quickly executed under the accident working condition of the nuclear power plant. Meanwhile, after the stop, the full-opening action is directly executed in the reverse direction, the unnecessary full-stroke reciprocating motion of the valve is greatly reduced, the mechanical structure wear is effectively reduced, the service life of the equipment is prolonged, and the operation reliability of the electric regulating valve and the nuclear safety guarantee capability are improved.

A listen-before-talk random access method using adaptive energy detection threshold selection is performed by a device. A plurality of component units, such as code block groups (CBGs), in a transport block are determined to be retransmitted via a contention-based random access operation. An energy detection threshold (EDT) based on the component unit is selected. The EDT is associated with the determined component units to be retransmitted. Energy detection is performed in an initial contention-based random access operation using the selected component unit-based EDT.