331results about How to "Guaranteed real-time" patented technology

The invention discloses a speaker recognition method in a medical real-time speech recognition scene, and the method specifically comprises the steps: carrying out the parallel distribution of a received PCM audio stream through an audio diverter in a gateway layer, and transmitting the audio stream to an automatic speech recognition link and a speaker separation link; in the automatic speech recognition link, outputting a recognition text and Token-level timestamps corresponding to each minimum semantic unit in the recognition text; in the speaker separation link, extracting a corresponding speaker embedding vector based on a preloaded speaker embedding model, and performing online clustering processing on the embedding vector to generate a speaker identity identifier; token-level boundary adsorption labeling processing is executed based on the Token-level timestamp and an online clustering result, so that a speaker switching position is determined; and carrying out one-to-one mapping on the speaker tags and the recognition text according to the Token-level timestamps, merging Tokens with the same speaker tags continuously, and outputting a transliteration text with the speaker tags.

The invention discloses a low-delay adaptive code rate control system for a meteorological monitoring video stream, and relates to the technical field of adaptive code rate control in video stream media transmission, and the system comprises a content importance analysis module which is used for carrying out the real-time analysis of a video block to be transmitted, generating a content importance score representing the meteorological information value; and the decision arbitration module is connected with the content importance analysis module and is used for receiving the content importance score, the network state information and the buffer area state information. According to the low-delay adaptive code rate control system for the meteorological monitoring video stream, bandwidth resources can be allocated according to the difference of meteorological information values of video contents, the quality of key monitoring pictures is guaranteed preferentially when network conditions fluctuate, unnecessary code rate switching is inhibited actively through internal look-ahead simulation and risk assessment, and the quality of the meteorological monitoring video stream is improved. Therefore, balance between continuous and clear transmission of high-value information and overall watching fluency is realized in a complex network environment.

The invention discloses an electric meter intelligent communication detection method and system based on a power line carrier, and relates to the technical field of electric meter communication detection, and the method comprises the steps: collecting the communication data of an electric meter at different time periods, inputting an electric meter communication state dynamic sensing model, analyzing features, and obtaining an initial evaluation result; channel characteristic parameters are calculated by using a carrier channel characteristic dynamic estimation algorithm based on the result, and the channel characteristic parameters are input into a power carrier signal demodulation optimization algorithm to generate an optimized demodulation scheme; signals are demodulated and data are verified according to the scheme, related results are uploaded to an electricity meter communication performance optimization management platform, and the platform evaluates performance and generates optimization suggestions and fault early warning. The system comprises a data acquisition unit, a state analysis unit, a channel calculation unit, a demodulation optimization unit, a data processing unit and a performance management unit which operate cooperatively. The communication state can be dynamically sensed, the channel characteristics can be accurately estimated, the demodulation process can be optimized, the integrated management of the communication performance can be realized, and the accuracy and reliability of the electric meter communication can be improved.

The application relates to the technical field of power grid fault diagnosis, and discloses a power grid transient fault intelligent early warning method and system based on space-time data fusion, which comprises the following steps: receiving a power grid monitoring node real-time data block and extracting a waveform fingerprint vector, constructing a credible space-time island through dynamic magnetic puzzle space adsorption alignment; constructing a local dynamic causal graph through traveling wave causal verification based on the credible space-time island, identifying a disturbance source and upgrading the disturbance source into a high-risk space-time island; extracting an island-level space-time feature vector, calculating an early warning deviation index to trigger a hierarchical asynchronous advanced early warning; when data asynchronous transmission disorder reaches, the application considers the early warning real-time performance and accuracy, and realizes robust asynchronous advanced early warning of the power grid transient fault.

This application discloses a method, apparatus, equipment, and storage medium for calculating the moisture content of electrical insulation paperboard, relating to the field of transformer technology. The method for calculating the moisture content of electrical insulation paperboard includes: collecting data on the exposure time and environment of the target transformer body; calculating the moisture absorption rate of the electrical insulation paperboard of the target transformer body based on the exposure time and environmental data combined with a moisture absorption rate calculation model; calculating the stage saturated moisture content of the electrical insulation paperboard of the target transformer body based on the exposure time and environmental data combined with a stage saturated moisture content calculation model; and calculating the moisture content of the electrical insulation paperboard based on the exposure time, moisture absorption rate, and stage saturated moisture content. This method achieves accurate calculation of the moisture content of electrical insulation paperboard based on environmental information and a constructed calculation model without damaging the paperboard, improving the efficiency of moisture content calculation while ensuring real-time performance.

The present application belongs to the technical field of data analysis, and particularly relates to a high-throughput biosensing system for early warning of algal blooms and pathogens, which comprises multiple sampling units, a microfluidic chip with a multi-channel structure, and a high-throughput surface-enhanced Raman detection unit with an integrated metal nanostructure surface, and obtains the original surface-enhanced Raman spectrum of the water sample through a Raman spectrum acquisition mechanism. The system uses compressed spectrum sampling and sparse reconstruction methods to reduce the data volume and maintain the integrity of the spectrum information, constructs a pathogen Raman fingerprint dictionary through a dictionary learning method, and realizes the identification of different algal metabolites, algal toxins and pathogen-related molecular components and the concentration interval judgment thereof in combination with a sparse representation classification mechanism. Based on the type and concentration interval of the pathogens, the system further generates algal bloom risk warning and pathogen risk warning, and realizes early discovery of abnormal changes in the water body. The present application has significant advantages in stability, sensitivity, throughput and real-time performance.

This invention relates to the field of model simulation calculation, and particularly to a real-time rendering system for 3D simulation analysis results of dams. The system server, through a simulation model management module, transmits a 3D finite element mesh model, obtains calculation conditions from the system client, performs simulation based on these conditions, outputs calculation results, and transmits the calculation result data to the system client after processing it using an 8-bit compression method. A three-level indexing system is constructed. The calculation result management module manages the calculation results. The system client renders a multi-dimensional physical field cloud map. During precise queries, the system server returns lossless calculation results to the system client based on the three-level indexing system. This invention leverages the long-connection characteristics of WebSocket to achieve on-demand incremental transmission of fragmented data, resolving network congestion caused by full transmission. Through the synergy of data compression and progressive rendering, network utilization is optimized while ensuring the real-time performance and stability of the front-end visualization effects.

A kind of flow video active interaction control method, equipment and medium for the scene of helping blind, construct the hierarchical task system for the scene of helping blind, train the semantic understanding and behavior alignment of multimodal large model to specific task of helping blind;Introduce the active interaction control mechanism for flow video, under the premise of not changing the bottom model parameter, realize the trigger output of environmental perception by the dynamic suffix switching of determination mode and generation mode;Finally, the incremental context updating strategy is used to optimize the inference process, while keeping the timing consistency and reducing the calculation redundancy.The invention solves the technical problems of lack of special data, passive interaction logic and calculation redundancy of multimodal large model in flow environment through the synergistic effect of data-driven task adaptation and active interaction mechanism.The general framework proposed in the invention provides an important theoretical basis and technical paradigm for the paradigm evolution of flow video understanding from "passive analysis" to "active interaction".

The invention relates to the technical field of environment monitoring, in particular to a multi-point automatic water sampling device for an unmanned aerial vehicle, which comprises a water sampling mechanism arranged at the bottom of the unmanned aerial vehicle, the water sampling mechanism can be automatically connected with a flying platform of the unmanned aerial vehicle, the water sampling mechanism comprises a shell, a water tank and a water pumping component, the water tank is arranged at the bottom outside the shell, and a plurality of water sampling bins are arranged in the water tank in a surrounding manner; the shell is provided with a liquid inlet hole communicated with the water sampling bin; the water pumping component comprises a water pump, a turntable and a switching pipe, and a water inlet pipe is arranged at the suction end of the water pump and provided with a water sampling pipe; a drain pipe is arranged at the discharge end of the water pump; the turntable is driven by a switching motor and is provided with a through drainage hole, one end of the switching pipe is communicated with one end, far away from the water pump, of the drainage pipe through a sealing universal joint, and the other end of the switching pipe is communicated with the drainage hole. According to the invention, single-pass flight is realized, multi-point sample collection, storage, diversion and export can be completed, the water collection efficiency is improved, and the real-time performance of seawater monitoring is ensured.

The present application relates to a kind of laser radar and camera online self-calibration method and system without induction, the method includes: S1.in the process of vehicle driving, through multi-source trigger mechanism acquisition laser radar point cloud data and camera image data, simultaneously obtain vehicle motion state information and automatic driving perception system output result, the multi-source trigger mechanism includes time trigger, event trigger and cloud data mining trigger parameter degradation model;S2.the pre-processing and feature extraction of the multi-source data collected, obtain laser radar point cloud feature and camera image feature;S3.based on geometric constraint, motion consistency and perception result fusion, constructs multi-modal verification model, and carries out multi-dimensional verification to calibration parameter.The present application not only reduces the artificial maintenance cost, through automatic means maintenance vehicle state to achieve sensor calibration parameter degradation self-detection and self-calibration without induction, and improves the reliability and attendance rate of automatic driving vehicle.

This invention discloses a low-light pedestrian detection method based on multimodal fusion, comprising an image input end, an image processing end, and an image output end. The image input end inputs RGB and infrared images through an external imaging device to the image processing end. The image processing end outputs the detection result based on the fused features to the image output end for displaying the final detection result. This method can improve the accuracy of pedestrian recognition in low-light conditions, while ensuring the model's real-time performance and superior performance compared to traditional algorithms.

The invention discloses a low-altitude general airport rapid building system and method based on modular splicing, and the system comprises a twinborn model management module which is used for managing a multi-dimensional digital twinborn model of a low-altitude general airport assembly; the three-dimensional scene building module is used for realizing quick assembly and component butt joint of a low-altitude general airport scene through modular dragging, wireframe type connection and a process expression mode; the multi-source data docking module integrates a multi-protocol interface library and a data unified service, and is used for accessing an external data platform and a simulation model to realize data analysis and driving; and the visual operation platform is used for loading the twinborn model and the multi-source data and driving three-dimensional scene operation and real-time monitoring. According to the method, geometric, physical, behavior and rule fusion is realized through a multi-dimensional twin model pedigree; through interconnection and intercommunication of multi-source data, real-time performance is guaranteed through a general interface library, and then visual simulation and one-key preview scene operation are realized.

The application relates to the technical field of aerial video analysis, and discloses a large-scene multi-modal analysis system and method based on a UAV. The method acquires an original video frame sequence from aerial equipment, extracts a scene change period and an object motion trend by calculating an inter-frame motion feature vector, and judges whether a scene is in a stable or dynamic state by means of a state classification model. In the dynamic state, a tracking target position is calculated according to preset parameters, and an analysis target area is adjusted in combination with the motion trend; a camera parameter adjustment instruction is generated according to a deviation amount of the analysis target area from an actual object position, and is output to an executing mechanism; a complexity value is acquired through a scene complexity feedback signal, and when the complexity value exceeds a preset range, an adaptive algorithm is used to update an analysis strategy and output an adjustment signal; the output timing of control and strategy adjustment signals is optimized, the frame sequence and analysis parameter change trend are monitored in real time, preset parameters are dynamically updated to match user requirements, and efficient video analysis processing is realized.

This invention discloses a method and system for real-time data synchronization of multiple target libraries for power metering, belonging to the field of power metering data processing technology. Edge node devices collect and preprocess real-time data from power metering terminals, generating an energy consumption and resource status matrix before uploading it to the cloud. The cloud automatically detects the target library type and determines the adaptation priority through dynamic format conversion and hierarchical analysis. Based on the status matrix and priorities, a five-dimensional objective function is constructed, including business priority, cross-library adaptation success rate, system energy consumption, network load balancing, and data time-series consistency. An optimal scheduling scheme is generated using the DDPG algorithm. Transmission is completed by combining LSTM prediction, sliding window differential, and lightweight compression. After SHA-256 segmented verification, the hash value and device ID are written into the power industry consortium blockchain. This invention achieves multi-library collaborative adaptation, low bandwidth consumption, low energy consumption, and high time-series consistency, ensuring real-time, accurate, and secure synchronization of metering data.

The application relates to the technical field of power systems, and discloses a new energy power source virtual equivalent modeling method, a new energy power source virtual equivalent modeling system, a storage medium and equipment, the method comprising the following steps: establishing a virtual equivalent model of a new energy station, wherein the virtual equivalent model is composed of an equivalent potential and an equivalent impedance in series; determining parameter constraint conditions of the virtual equivalent model, wherein the parameter constraint conditions comprise: setting the amplitude of the equivalent potential to be the same as the amplitude of an AC system potential on the opposite side of a power grid line; setting the impedance angle of the equivalent impedance to be equal to the impedance angle of the power grid line; collecting measured voltage and measured current at a power grid protection point in real time; establishing a variable relationship equation group in polar coordinate form based on the parameter constraint conditions of the virtual equivalent model; and solving the variable relationship equation group to obtain dynamic parameters of the virtual equivalent model. The application can realize accurate equivalent modeling of the new energy station, thereby accurately reflecting the dynamic characteristics of the new energy power source.

The invention discloses a transmitter system based on multi-sensor fusion and edge AI and a self-diagnosis method, and belongs to the technical field of industrial process control instruments, and an industrial intelligent transmitter system comprises a multi-sensor unit, a signal acquisition unit, a microcontroller, an AI coprocessor and a dual-mode communication unit. The multiple sensing units are used for synchronously collecting original data; the signal acquisition unit is used for converting original data into digital signals; the microcontroller is used for processing the digital signal and carrying out environment adaptive compensation to obtain compensated sensor data; the AI coprocessor is used for performing feature extraction and fault probability reasoning on the compensated sensor data to realize real-time self-diagnosis; and the dual-mode communication unit is used for transmitting the compensated process control signal and diagnosis information in different channels. The system has the functions of environment adaptive compensation, real-time self-diagnosis and the like, and the problems of parameter drift and fault response delay in an industrial environment are remarkably improved.

The invention discloses a map real-time construction and rescue path dynamic planning system oriented to a fire dense smoke scene, and relates to the technical field of fire rescue. The system comprises a data acquisition and processing module, an environment modeling and path construction module and a post-processing module, based on millimeter wave radar, laser radar and motion sensor data, multi-modal information is obtained, synchronized and converted, a semantic segmentation model is utilized to analyze environment perception data to generate a feasible space, and laser radar point cloud and motion sensor data are fused to realize real-time positioning, map construction and rescue path planning in a fire scene. The path is updated in real time according to fire scene environment change, and a generated result is visually presented through a post-processing module and communicates with a command platform for real-time interaction. The system has the advantages of long-distance sensing of the millimeter wave radar and short-distance high precision of the laser radar, can realize quasi-real-time and high-precision fire scene environment modeling and dynamic path generation, and provides reliable path reference for rapid action decision in fire rescue.

The invention is suitable for the technical field of image recognition, and provides a live pig breeding state monitoring method and device, and the method comprises the steps: collecting real-time video data, and recognizing a current animal body region in the real-time video data; tracking the current animal body area, and collecting a subsequent animal body area according to a preset sampling frequency; identifying the behavior state of the subsequent animal body area; wherein the behavior state comprises standing and lying; and when the behavior states corresponding to the preset number of continuous follow-up animal body areas are all lying, sending abnormal prompt information and the continuous follow-up animal body areas to the user terminal. According to the invention, automatic and intelligent monitoring of the live pig behavior state is realized, and the accuracy and real-time performance of monitoring are improved.

The invention is suitable for the technical field of edge computing, and relates to an AC charging pile fault diagnosis method and system based on edge computing, and the method comprises the steps: a transformer area fusion terminal collects the total power of a transformer area and the charging characteristic power of a charging pile through HPLC communication; the power and current of the charging pile during charging, and the residual current and short-circuit characteristic current detected by the residual current protector are measured through the intelligent electric meter. Based on the matching relationship between the total power change of the transformer area and the charging characteristic power, establishing the mapping relationship between the intelligent electric meter and the corresponding AC charging pile; whether the alternating current charging pile breaks down or not is judged by combining sequential logic of the total power change, the residual current change, the short-circuit characteristic current change and the power change of the intelligent electric meter, and the fault type is determined; and after the fault is determined, the transformer area fusion terminal reports the fault information to the system master station through the communication network. According to the method, additional hardware facilities do not need to be added, the real-time performance, the accuracy and the safety of fault diagnosis of the alternating current charging pile are high, and the cost is low.

This invention relates to a method and system for intelligent processing and health assessment of multi-parameter acoustic-vibration data in GIS, belonging to the field of power equipment monitoring technology. The method includes: collecting acoustic signature data, vibration data, and geographic location information from GIS equipment to form a raw acoustic-vibration data stream with geographic tags; writing the raw acoustic-vibration data stream into a storage-computing architecture, sequentially extracting and fusing features from the acoustic signature data and vibration data to obtain a multi-parameter feature matrix with geographic tags; using a lightweight convolutional neural network to infer and label suspected faults on the multi-parameter feature matrix; using a support vector machine (SVM) model to identify faults in the multi-parameter feature matrix with suspected fault labels, obtaining the final fault type and confidence level; and combining equipment runtime, maintenance records, fault frequency, and GIS location information to perform a health assessment of the GIS equipment and classify fault levels. This invention significantly improves the accuracy of GIS fault identification and reduces the operation and maintenance costs of large-scale GIS applications.

The application discloses a communication risk detection method, system, device and storage medium, relates to the technical field of network security, and solves the problem of difficult data tracing by standardizing communication data and associating the standardized communication data with an abnormal list library to construct a dynamic network; through multi-time scale feature extraction combined with a parallel analysis architecture, fast response is realized by using a real-time rule matching layer, dynamic evolution rules are captured by using a hidden Markov model of a behavior pattern analysis layer, and group risks are identified by using a space-time weighted model of a correlation network analysis layer, so that the defects of poor adaptability and single dimension of traditional methods are overcome; finally, through multi-engine decision and hierarchical disposal mechanism, the recognition accuracy is guaranteed while the disposal efficiency is optimized, so that high-precision and low-delay identification and control of cross-border abnormal communication behaviors are realized.

The application discloses a kind of multi-source information mixed combination navigation method under visual assistance, gyro angular velocity and accelerometer linear acceleration information are provided by inertial navigation system;Speed measuring equipment obtains the real-time speed information of mobile object;Global navigation satellite system provides position information and second pulse signal;Visual sensor provides the image information required for navigation;Strapdown inertial navigation algorithm update module carries out navigation solution;Kalman filtering navigation algorithm module estimates the state variable of system in real time;Fault detection and elimination module detects whether the system fails;Image feature detection and tracking module realizes the extraction tracking of image key frame;Sliding window graph optimization algorithm module updates covariance matrix;Loop detection module gives similarity score through image information to judge whether there is loop;Navigation result output module outputs correct navigation information.The problem that existing navigation mode cannot position and orient for a long time is solved.

The application provides a synthetic aperture radar active composite jamming method and system, the method comprising: acquiring intermediate frequency radar signals to be jammed, radar related parameters and control parameters; calling DSP and multiple FPGA calculation boards to calculate modulation coefficients corresponding to each false scattering point according to pre-downloaded deception templates and radar related parameters; generating deception jamming signals corresponding to the intermediate frequency radar signals according to the intermediate frequency radar signals and the modulation coefficients corresponding to each false scattering point; generating suppression jamming signals corresponding to the intermediate frequency radar signals according to the control parameters; and determining composite jamming signals corresponding to the intermediate frequency radar signals according to the deception jamming signals and the suppression jamming signals corresponding to the intermediate frequency radar signals. The application can obtain composite jamming signals, has better jamming effect, is not easy to expose the position of the jammer, and has lower cost of the jammer. The signal processing architecture of DSP and FPGA is adopted, the calculation performance of the system is improved, and the real-time performance of system simulation is ensured.

This invention discloses a machine vision-based unattended monitoring and early warning method, device, and system for tunnel water inrush, comprising: calculating the optical flow vector of each pixel in the tunnel face image; determining the location, number, and optical flow vector of the inrush point based on the optical flow vector of each pixel; determining whether the inrush point has disappeared based on the change in the optical flow vector at the inrush point; determining whether a water inrush exists based on the optical flow vector at the inrush point and determining the optical flow vector at the water inrush location; determining the water volume of the water inrush based on the optical flow vector at the water inrush location; and determining whether to issue an early warning based on the water volume. By utilizing the motion characteristics of the water inrush, the optical flow method is used to monitor the range of tunnel water inrush, achieving real-time monitoring of tunnel water inrush.

This application discloses a CAN network load balancing method, apparatus, device, and medium, relating to the field of communication technology and applied to a master ECU node. The method includes: after power-on, sending a local clock timestamp to each slave ECU node at preset time intervals, so that each slave ECU node synchronizes its local clock based on the timestamp; obtaining the transmission load reported by each slave ECU node after synchronizing its local clock, and planning the transmission time points of each slave ECU node based on the transmission load to obtain a time schedule table; and sending the time schedule table to each slave ECU node so that each slave ECU node sends CAN messages at the target time points specified in the time schedule table according to its local clock. In this application, the master ECU node can uniformly schedule the time for slave ECU nodes to send CAN messages based on their transmission load, reducing the peak load of the CAN bus and ensuring the stability and real-time performance of signal transmission.

The invention provides a method and system for monitoring the health state of server equipment, and relates to the technical field of server monitoring. The system comprises a data acquisition module, a message processing module, an event distribution module, a log conversion module, a mapping table module, a health state management module and an alarm module. According to the method, data and SEL logs are collected in parallel through multiple threads, events are converted into uniform IDL logs, the uniform IDL logs are associated to specific hardware equipment through a mapping table, the sub-health state, the overall health state and the type summarized health state of the equipment are updated based on the alarm level, and accurate alarms are generated when the equipment is abnormal. According to the invention, through the design of the multi-level health state architecture and the mapping table, the accurate positioning of the fault is realized; the monitoring real-time performance is guaranteed through multiple threads and a priority message queue; the resource consumption is reduced through the differentiation strategy, the method is suitable for large-scale server cluster deployment, and the problems that an existing monitoring mode is poor in real-time performance, inaccurate in positioning and the like are effectively solved.

The application discloses a kind of based on image data's track area abnormal detection method and device of machine tool, it is related to image recognition technical field.The method includes: using image recognition algorithm, introduce multi-objective optimization algorithm, build machine tool target detection model, and connect to candidate region segmentation engine and space-time correlation filter engine;Video stream of track area is collected, and pretreatment is carried out, and the image data of continuous frame is obtained;The image data of continuous frame is input to candidate region segmentation engine, and the ROI region of each frame of image data is obtained;ROI region is input to machine tool target detection model, and the detection frame of machine tool target is obtained;The detection frame of machine tool target is input to space-time correlation filter engine, identifies stationary effective target, and carries out abnormal detection to stationary effective target.The application solves the problems of low detection accuracy, difficult model deployment and poor anti-interference ability in the prior art.

This invention relates to the field of software operation forensics and fault diagnosis technology, specifically to a method for recording a minimum sufficient evidence package for an airbag control unit and an automotive airbag control unit. The method is executed in a Classic AUTOSAR environment and includes: determining whether both anomaly symptom conditions and operational state time gating conditions are simultaneously met; if so, determining that the trigger condition is established; recording the trigger time; and freezing event information, path signatures, and key variable snapshots at the end of a predetermined window after triggering. Combined with the invariant assertion bitmap at the time of triggering, a minimum sufficient evidence package is generated. Compared with existing technologies, this invention can record a minimum sufficient evidence package with predictable and extremely low operational overhead, and has advantages such as not changing the airbag control logic path, not entering the ignition ISR critical segment, and retaining evidence even in power-down scenarios.

The invention discloses a concrete pump pipe fixing system and an assembling and monitoring method thereof. The system comprises a vertical fixing device, a bent pipe fixing device, a horizontal fixing device and a monitoring and control system. The assembling method comprises the following steps of positioning and paying off, installing the vertical fixing device, installing the bent pipe fixing device, installing the horizontal fixing device, installing the pipeline, and clamping and fixing. The monitoring method comprises five main steps of system initialization, data acquisition, edge calculation processing, cloud analysis and early warning, and decision support and feedback. According to the invention, lossless installation, intelligent monitoring, active early warning and predictive maintenance are realized, the construction safety is remarkably improved, the service life of equipment is remarkably prolonged, and the management efficiency is remarkably improved.

The application discloses a mobile device path planning method and an electronic device. The mobile device path planning method comprises the following steps: constructing a fitness function of mobile device path planning; initializing a particle swarm population, and a particle position is used for encoding a candidate path composed of multiple intermediate path point coordinates; performing multiple iterations of optimization, in each iteration, after each velocity and position update is completed, performing a dimension-by-dimension optimization operation on the entire population, the dimension-by-dimension optimization operation searches the path point coordinates of the candidate path encoded by all particle positions in the population dimension by dimension, and optimizes the corresponding path point coordinates in the global optimal position; after the iterations are completed, determining an optimal path based on the path encoded by the global optimal position. The application overcomes the defect that the effective local feature is lost due to simple elimination of low fitness particles in the existing PSO algorithm; meanwhile, repeated calculation of full path evaluation is avoided, and the real-time performance and high efficiency of algorithm operation are ensured while the optimization precision is effectively improved.