11results about How to "Overcoming real-time" patented technology

The invention provides a ship remote real-time early warning system based on cloud computing, and relates to the technical field of data processing, and the system comprises a data collection module which is used for collecting ship operation data, environment state data and external interaction data; the data preprocessing module is used for generating standard processing data; the data grouping module is used for dividing a priority data group and a common data group; the data transmission module is used for transmitting the data to the cloud analysis module; the cloud analysis module is used for carrying out multi-source data aggregation processing on the priority data set and the common data set, carrying out real-time evaluation on the ship operation state, identifying abnormal behaviors and predicting emergencies, and generating corresponding final early warning instructions including an avoidance operation instruction and an air route adjustment suggestion; the early warning feedback module is used for sending the early warning instruction to the ship terminal; the local response module is used for executing instant triggering operation on the instruction classification data; according to the invention, autonomy and accuracy of remote real-time early warning of the ship are improved.

The invention discloses a wired insulation on-line monitoring method and system based on digital intelligent power supply storage, and the method comprises the steps: firstly collecting and preprocessing a power interference signal, extracting feature information from the signal through a wavelet transform technology, and then carrying out the classification and prediction of a cable insulation state through a Transform model. The method not only can effectively identify the health state, the slight aging state and the severe aging state of the cable, but also is high in detection precision and good in real-time performance, overcomes the problems that an existing monitoring method is insufficient in real-time performance and low in detection precision in a complex electric power environment, and remarkably improves the reliability and efficiency of cable insulation monitoring.

The present invention provides a ship remote real-time early warning system based on cloud computing, which relates to the technical field of data processing, and comprises: a data acquisition module, which is used for acquiring ship operation data, environmental status data and external interaction data; a data preprocessing module, which is used for generating standard processing data; a data grouping module, which is used for dividing into a priority data group and a common data group; a data transmission module, which is used for sending to a cloud analysis module; the cloud analysis module, which is used for performing multi-source data aggregation processing on the priority data group and the common data group respectively, performing real-time evaluation on the ship operation status, identifying abnormal behavior recognition and emergency event prediction, and generating corresponding final early warning instructions, including avoidance operation instructions and route adjustment suggestions; an early warning feedback module, which is used for sending the early warning instructions to a ship terminal; and a local response module, which is used for performing an immediate trigger operation on the instruction classification data. The present invention improves the autonomy and accuracy of the ship remote real-time early warning.

The application provides an intraoperative real-time optical coherence imaging guided laser ablation treatment system, which comprises an optical guiding module, a laser treatment module and a real-time monitoring and feedback module; high-resolution three-dimensional information and blood vessel function information obtained by the optical coherence imaging guiding module are used to accurately segment the region of a tumor site, and the power and irradiation time of a radiation laser light source are accurately controlled according to the information; meanwhile, a temperature sensor monitors the tissue temperature at any time, and the system pauses laser diagnosis and treatment when the temperature exceeds the set threshold range, so that precise laser ablation treatment is realized; the application aims to overcome the problems that the current laser ablation treatment lacks real-time and accurate segmentation of tumor regions and lacks real-time monitoring and feedback of the tissues around the tumor during the operation, so that real-time and accurate laser ablation treatment of the tumor site during the operation is realized.

The present application relates to the technical field of automatic driving and unmanned driving, and particularly provides a vehicle positioning method, computer equipment, a server, a storage medium and a vehicle, aiming to solve the problem of reducing the real-time performance and reliability of positioning caused by too long loading time and large memory resource occupation. The method provided by the present application comprises loading a serialized file formed by serializing a data structure of a point cloud probability distribution map, the data structure being formed by encapsulating a voxel index of a point cloud map and normal distribution parameters of point clouds in the voxel; performing deserialization processing on the serialized file to obtain the data structure; and using a positioning method based on an NDT algorithm to perform point cloud registration on a laser radar point cloud frame collected by the vehicle according to the data structure, so as to determine the pose of the vehicle. Through the above method, the data loading time can be greatly reduced, and after the loading is completed, too much memory resource will not be occupied, and finally the real-time performance and reliability of vehicle positioning are improved.

The present invention discloses an item recommendation method and device, and relates to the field of computer technology. A specific implementation of the method includes: obtaining an intent recognition result and extracting entity information according to the conversation content input by the first user in the current conversation; judging whether the intent recognition result is the target intent; if so, generating an item push list according to the entity information; wherein the item push list includes at least one item. This implementation can solve the technical problem of poor accuracy and real-time performance.

The invention discloses a robot multi-layer cooperation method and system for grotto cultural relic protection and guide, and the method comprises the steps: collecting the multi-dimensional data of grotto cultural relics and surroundings through distributed sensing nodes, carrying out the classified storage, and calling a cultural relic defect hierarchical recognition and evaluation model to complete the preliminary screening and type judgment of defects, the method comprises the following steps: scheduling a detection robot to execute refined detection and defect level quantitative evaluation based on a multi-layer cooperative dynamic task allocation mechanism of the robot, starting a style migration model for a wall painting fading defect to carry out color reconstruction and style adaptation, and planning an optimal path through a dynamic avoidance algorithm based on environment obstacle information; and integrating various data to generate personalized navigation content and transmitting the personalized navigation content to the navigation robot to execute a task. Through multi-step cooperation and model algorithm support, intelligent linkage of defect identification, fading repair, path planning and navigation service is realized, and the cooperation efficiency of grotto cultural relic protection and navigation is improved.

The invention provides a railway bridge construction operation and maintenance method and system based on carbon emission optimization, relates to the technical field of traffic infrastructures, and aims to construct a bridge digital twin model in a construction stage to simulate and predict carbon emission dynamics. And carrying out correlation analysis on the carbon emission influence factors by using a space-time diagram network. The carbon emission is globally optimized through a quantum annealing algorithm, construction scheduling is optimized in combination with a quantum decision tree, dynamic regulation and control of the carbon emission are achieved, and meanwhile the influence on bridge material attenuation is determined. And an operation and maintenance stage: inputting the bridge structure attenuation information and the bridge structure data obtained in the operation and maintenance stage into a convolutional neural network, predicting a bridge structure state, and generating a dynamic maintenance decision according to the bridge structure state. The method can accurately monitor and optimize the carbon emission in the construction, operation and maintenance stages of the railway bridge, and provides technical support and decision basis for the industry to realize low-carbon and sustainable development targets.

The invention discloses an electric wheel slippage rate estimation method based on adaptive filtering, which comprises the following steps of: 1, acquiring running parameters of a vehicle on a current road surface, including a tire rotating speed, a vehicle running speed, a vehicle steering wheel rotating angle and a hub motor driving torque; 2, acquiring an original slip rate estimated value of an electric wheel of the vehicle under a linear driving condition; 3, estimating the inherent frequency of an electric wheel system, and calculating the low-pass cut-off frequency of a filter; 4, acquiring a torque ripple order instantaneous frequency of the hub motor, and selecting a filter type and a cut-off frequency in combination with a low-pass cut-off frequency; and 5, carrying out preset adaptive filtering processing on the original slip rate of the electric wheel to obtain an accurate estimated value of the slip rate of the electric wheel. The method comprehensively considers the influence of the torque fluctuation of the hub motor in the electric wheel and the deformation of the tire body during the estimation of the slip rate, and effectively improves the estimation precision of the slip rate of the electric wheel while guaranteeing the safety.

The invention discloses a multi-tense power grid trajectory analysis method based on digital twinning, and belongs to the technical field of power grid analysis, and the method comprises the following steps: S1, carrying out the feature reduction of an original power grid sample set; s2, constructing a power grid digital twinborn model based on the original power grid sample set after feature reduction; s3, constructing a multi-tense power grid track deduction model based on the original power grid sample set after feature reduction; and S4, generating trajectory data based on the power grid digital twin model, and inputting a mixed data set formed by the trajectory data and real-time data into the multi-tense power grid trajectory deduction model for analysis and diagnosis. Through comprehensive analysis of multiple tenses, the operation state of the power grid can be comprehensively known, and a scientific basis is provided for power grid dispatching and decision making.