59results 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 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 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 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 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 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 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 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.

The application discloses an intelligent warehouse logistics real-time goods location optimization method and system, relates to the technical field of intelligent warehouse logistics, and discloses the intelligent warehouse logistics real-time goods location optimization method and system. The disclosed intelligent warehouse logistics real-time goods location optimization method and system solve the delay and conflict problems of traditional methods in the peak period, can improve the warehouse operation efficiency and system throughput by acquiring warehouse real-time data, constructing a warehouse dynamic state atlas, generating an initial allocation scheme, inputting a distributed decision network for parallel collaborative evaluation optimization, and issuing a global instruction.

The application relates to the technical field of data processing, and discloses an interactive data real-time collection and analysis method for a smart classroom, which comprises the following steps: analyzing multi-source interactive data streams, extracting basic interactive tuple structures and distributing the basic interactive tuple structures to corresponding time slots; calculating a global safe aggregation water line according to a global maximum event timestamp and a maximum tolerance delay parameter, and outputting complete time window data blocks; calculating information entropy values of teaching behavior events, performing hysteresis interval determination in combination with historical states and high-low dispersion threshold values, and determining storage routing states; dynamically generating a compact bitmap structure or a dynamic inverted index linked list according to the states; responding to instructions to perform cross matching and time sequence constraint checking, and outputting analysis results. The application solves the problems of out-of-order and delay of data transmission, adaptively matches a bottom-layer storage structure to reduce operation internal consumption, reduces invalid memory addressing through pre-filtering, improves retrieval efficiency, and quickly and accurately outputs an academic situation analysis result.

The utility model relates to the technical field of 5G intelligent cameras, and discloses a 5G intelligent camera developed based on an ARM platform, the 5G intelligent camera comprises a mainboard, a carrier plate and a lamp panel, the mainboard comprises an ubuntu ARM Quard A55, and the ubuntu ARM Quard A55 is connected with an eMMC DATAO-DATA7 16GB through an eMMC 5.1 HS400. According to the 5G intelligent camera developed on the basis of the ARM platform, USB3.0 high-speed data transmission, gigabit network high-speed data transmission and 4G / 5G communication wireless transmission can be applied to the industrial camera for the first time, and the intelligent industrial camera with the computing power capable of achieving local computing can support a C-port lens and an M12 lens and meanwhile support a lamp source of the camera.

The application discloses an automatic focusing method, system and medium, the automatic focusing method comprises the following steps: identifying the magnification of an objective lens, screening the defocus threshold corresponding to the magnification; constructing the theoretical motion model, the measured motion model and the measured variance of the focusing process parameters in the focusing process, and predicting the focusing process parameters at the next moment; analyzing the deviation between the measured value and the predicted value of the focusing process parameters at the same moment, determining whether the deviation of at least one focusing process parameter is greater than the set deviation threshold, if there is, dynamically adjusting the theoretical motion model; if not, driving the objective lens to focus when the predicted defocus is less than the defocus threshold. The application determines whether to dynamically adjust the theoretical motion model by the deviation of the predicted and measured focusing process parameters, eliminates the error, realizes fast focusing, meets the focusing requirements of objective lenses with different magnifications, and improves the focusing efficiency.

The invention discloses a multi-level agent collaborative decision-making method and system, and the method comprises the steps: carrying out the semantic analysis of an energy-saving standard document, extracting a standard knowledge unit, carrying out the semantic matching of an urban energy consumption target and the standard knowledge unit, and generating a correlation graph; a high-competition target group is identified through target competition degree analysis, collaborative agent pairs are screened through resource complementation degree calculation, and a building-level decision network is constructed; identifying low-load high-potential equipment and performing capability activation through equipment capability scanning and load potential evaluation; conflict intention double-layer features are extracted in combination with conflict detection, a conflict root is traced through a causal chain, and a mediation rule is established; improving the consensus degree of weak consensus nodes by adopting a consensus obstacle traceability and enhancement strategy; and finally, a hierarchical decision scheduling graph is formed through decision dependency analysis, multi-level collaborative decision scheduling is performed to generate a collaborative decision instruction, and comprehensive and intelligent multi-agent collaborative decision support is provided for a city-level energy-saving and carbon-reducing system.

The application belongs to the field of aero-engine design, and is a gas turbine combustor outlet temperature real-time calculation method and system. By analyzing the oil-gas ratio calculation formula, the corresponding relationship between the combustor outlet temperature and the currently measurable parameters during the whole machine test is obtained, the combustor outlet temperature is realized in real time online evaluation, the inlet temperature change and component performance of the high-pressure turbine component can be evaluated in real time; by combining the application of the power turbine inlet exhaust gas temperature test measurement value and the combustor outlet temperature calculation value in the control system, the problem of the delay of the single use of the power turbine inlet exhaust gas temperature limit in the transition state process of the current various gas turbines can be solved, the delay time of the transition state process over-temperature control can be obviously shortened, thereby the working life of the hot end component is improved, and the problems of inaccurate grasp of the existing low-emission gas turbine combustion mode switching point, poor generality of the calculation method and poor effectiveness are solved.

A kind of new water level measurement environmental monitoring operation system of port, including data acquisition module, data processing module, data display module, early warning control module and operation equipment;The data acquisition module is electrically connected with data processing module, the data processing module is respectively connected with data display module, early warning control module, the early warning control module is connected with operation equipment communication;The data acquisition module includes weather monitoring part and radar liquid level meter;The weather monitoring part is used to collect the wind speed, temperature, humidity, PM2.5 concentration data of wharf site;The radar liquid level meter is used to collect the real-time distance data with water surface, and the real-time water level of wharf is calculated in combination with the preset "design highest water level point" and "transfer station layer height distance".The utility model aims at overcoming the problem that environmental monitoring data is dispersed in field production operation, early warning is not timely, and is disjointed with operation process, realizes the real-time acquisition, processing, display, early warning of water level and multidimensional environmental data, and links control operation equipment, improves the safety and reliability of wharf production operation.

The invention relates to the technical field of identification, and discloses an intelligent identification method based on dynamic display, which comprises the following steps: S1, a data acquisition step: acquiring scene environment data and user state data in real time through a deployed environment sensor and a user positioning module; according to the invention, through an environment sensor and a multimode positioning module, multi-dimensional data such as illumination, temperature and humidity, a user position and a moving track are collected in real time, and in combination with a demand classification model driven by deep learning, user demands are accurately divided into three core scenes of navigation guidance, information query and activity reminding. And meanwhile, the priority of the identification content is determined by matching the scene state through the priority ranking model, so that irrelevant information interference of the user can be effectively avoided, the core demand matching accuracy is improved by more than 40%, the method is particularly suitable for complex scenes such as shopping malls and transportation hubs, the user information acquisition cost is remarkably reduced, and the individuation and accuracy of the identification service are improved.

The application discloses an intelligent quality monitoring system in a sesame paste production process, and belongs to the technical field of food processing quality monitoring; the system comprises, in sequence, a roasting machine, a grinding machine, a blending tank and a filling machine, and further comprises: a heat accumulation detection device, a temperature sensor and a timer connected with the roasting machine, and an integral electric signal output; a first electric signal comparison trigger compares the integral signal with a first set value and then drives a gap adjustment motor to automatically change a grinding gap; a multi-channel signal combiner combines and outputs a prediction signal by weighting the grinding temperature, the motor current and the integral signal; and a second electric signal comparison trigger compares the prediction signal with a second set value and then controls an additive electromagnetic valve. The application adopts a pure analog circuit to realize roasting-grinding-blending cross-section feedforward control, does not need programming, has low cost, fast response, and can effectively improve the quality consistency of the sesame paste.

The present invention relates to the field of data management technology, and in particular to a platform data processing management method and system based on big data. A platform data processing management method based on big data, comprising the following steps: S1: using NLP to obtain a unique semantic label for each data item field in a data warehouse, and adjusting the usage quantity of each data item in all downstream systems according to the unique semantic label; S2: based on the adjusted usage quantity in the downstream system, using a comprehensive weight formula to obtain the comprehensive weight of each data item, using a weighted time calculation formula according to the comprehensive weight, obtaining a weighted average waiting time, and obtaining a cache adjustment formula according to the weighted average waiting time. The present invention adapts to the complex needs of different scenarios by adjusting the cache size and data management rules in real time according to the dynamic needs of the downstream system, while providing good support for future system expansion.

The invention relates to the technical field of risk perception, in particular to an underground space disaster perception and risk intelligent decision analysis method and system. The method comprises the following steps: performing data acquisition on an underground space by using a sensor to generate underground space data; preprocessing the underground space data to obtain standard underground space data; performing multi-parameter feature extraction on the standard underground space data to obtain underground space multi-parameter features; performing underground space key disaster information identification on the underground space multi-parameter features to obtain key disaster information; therefore, through systematic data acquisition and analysis, the information processing efficiency and evaluation precision in underground space management are remarkably improved, and the problems of information delay, environmental restriction and insufficient evaluation in a traditional method are effectively solved. The innovation improves the disaster sensing ability, optimizes the timeliness and scientificity of risk decision, and provides more accurate decision support for managers.

This invention provides a method for transmitting railway Building Information Modeling (BIM) model files based on distributed storage. The method includes: lightweight decomposing the railway BIM model file into multiple sub-files; distributing these sub-files across edge server nodes using a cloud server; transmitting the sub-file list to a gateway; constructing a BIMdex index model; training the BIMdex index model using a training dataset; deploying the trained BIMdex index model locally on the gateway; and when an end device sends a file request carrying a file identifier to the gateway, the BIMdex index model in the gateway queries the sub-file list based on the file identifier, obtains the corresponding BIMdex address index, and returns it to the end device. This invention significantly improves data transmission efficiency by distributing sub-files of the same railway BIM model across multiple physical nodes and combining this with load balancing technology.

The invention discloses a galvanometer system and a light beam adjusting method, and the galvanometer system comprises a laser generating device which is used for emitting a laser beam; the light beam adjusting module is used for adjusting the light beam diameter of the laser beam; the galvanometer module is used for adjusting the light beam position of the laser beam; the F-theta mirror is used for focusing the laser beam into a light spot; the upper computer is provided with a multi-axis galvanometer motion control card, and the multi-axis galvanometer motion control card is in communication connection with the light beam adjusting module and the galvanometer module; the upper computer is used for receiving a light beam adjusting instruction and inputting the light beam adjusting instruction into the multi-axis galvanometer motion control card, so that the multi-axis galvanometer motion control card sends instructions to the light beam adjusting module and the galvanometer module at the same time. The multi-axis galvanometer motion control card sends instructions to the light beam adjusting module and the galvanometer module at the same time so as to correspondingly adjust the laser beams, and therefore the time delay problem in the galvanometer system is solved, and the machining precision of the galvanometer system is improved.

This application discloses a speech synthesis method, apparatus, storage medium, and electronic device. The method includes acquiring text data; obtaining speech audio data synthesized from the text data through a preset NAT processing model, wherein the preset NAT processing model includes an encoder, a Gaussian upsampling module, and a decoder; the encoder employs a unidirectional long short-term memory network and a recurrent neural network with controllable inverse delay; the Gaussian upsampling module performs Gaussian upsampling according to preset blocks; the decoder includes a Mel vocoder based on a neural network and an LPL vocoder based on a neural network; and obtaining the synthesized result of the text data based on the processing results of the Mel vocoder and the LPL vocoder based on the neural network. This application solves the technical problems of latency and inability to synthesize speech in the overall speech synthesis system.