107 results about "Track analysis" patented technology

The invention discloses a cross-modal large model construction method and system based on track spatio-temporal characteristics, and belongs to the crossing field of artificial intelligence and dynamic spatio-temporal data processing, and the method comprises the steps: carrying out the sliding sampling and spatial distribution difference judgment through the semantic dynamic segmentation of multi-scale track spatio-temporal data, and generating spatio-temporal data blocks with consistent semantics; designing a space-time encoder of a hybrid architecture, extracting track time sequence association and spatial features, and unifying dimensions; constructing a text space-time fusion mechanism, and dynamically adapting cross-modal features by means of an anchor interface and gating fusion; a staged instruction fine tuning strategy is adopted, semantic alignment of space-time and text features is optimized firstly, then model top-layer parameters are trained cooperatively, complex scene adaptation is enhanced in combination with instruction difficulty progression and hard sample mining, and space-time constraint regular terms are introduced to guarantee output rationality. According to the method, high-precision cross-modal reasoning capability is provided for scenes such as track analysis and track prediction.

The invention discloses a one-key performance test method, medium and equipment based on JMeter and template configuration, and the method comprises the steps: obtaining a parameterized performance test template from a template configuration center in response to a test instruction, injecting runtime parameters through a template engine, and generating an executable JMeter test plan; parsing the plan to identify a load pressure demand, thereby dynamically scheduling resources from a distributed load injector cluster and distributing a test plan; uniformly triggering test execution on the cluster, and synchronously acquiring a performance data stream from the JMeter and a resource data stream of the tested system; and finally, timestamp alignment and fusion are carried out on the two types of data streams, intelligent diagnosis is carried out on a formed monitoring data set based on a diagnosis rule base or an intelligent analysis model, and a visual test report containing bottleneck positioning, resource association and link tracking analysis results is generated. According to the invention, full-process automation and intelligentization of performance testing are realized, and the testing efficiency is remarkably improved.

The invention relates to the technical field of road surface monitoring, in particular to a sensor-based road surface quality detection system, which comprises a disturbance extraction module, a trajectory analysis module, a consistency identification module, a sudden change sorting module and a crack confirmation module. According to the invention, through the time sequence correlation analysis of the vertical structure vibration acceleration, the GPS direction vector and the transverse angular velocity signal in the vehicle driving process, the disturbance behavior and the trajectory deviation trend change in the vehicle and road surface contact process can be identified, and after the structure disturbance and the trajectory variation are correlated and compared, the stability of the vehicle is improved. Further screening real disturbance response from change consistency, constructing a space transfer model of crack mutation in combination with a joint state structure of disturbance intensity and offset amplitude, identifying a joint abnormal interval of structural damage and trajectory deviation in time and space, and determining a joint abnormal interval of structural damage and trajectory deviation in time and space through a multi-dimensional index distribution density and time continuity discrimination standard. And accurate judgment and spatial calibration of the crack area are realized.

The invention relates to a method, device and equipment for detecting shopping settlement fraud risk behaviors and a medium, and the method comprises the steps: obtaining a plurality of continuous video frames, and detecting a human body bounding box and a posture key point of a character object in the video frames, thereby obtaining a posture detection result; determining an upper body bounding box according to the human body bounding box, and tracking the upper body bounding box in a plurality of continuous video frames to obtain a motion track; according to the posture detection result and the motion track, determining whether the character object triggers a shopping behavior through track analysis and posture analysis, and if the character object triggers the shopping behavior, outputting and storing a detection record for a shopping behavior triggering event of the character object to obtain a shopping behavior detection result; and under the condition that the shopping behavior detection result represents that a shopping behavior trigger event exists, determining a wrist area image according to the wrist key point, performing commodity identification on the wrist area image through open set target detection, outputting and storing a commodity identification event record, and obtaining a shopping settlement detection result.

The invention discloses an e-commerce platform advertisement effect tracking analysis method based on a big data technology, and the method comprises the following steps: S1, collecting user data, and constructing a user behavior graph; s2, introducing an advertisement intervention path, comparing propagation states with or without advertisement intervention, calculating a disturbance consistency value and labeling an edge weight, and forming a structure chart; s3, inputting the structure diagram into a diagram causal reasoning network, and outputting advertisement individual effect estimation; s4, constructing a behavior disturbance sampler, generating a plurality of anti-fact behavior path training samples, and improving the causal fitting capability of the model; s5, executing path-level attribution on the actual user behavior graph by using the trained model, and outputting a causal weight matrix; and S6, generating an optimized advertisement putting strategy according to an attribution result. The advertisement causal attribution precision is improved, the putting strategy is optimized, and the conversion efficiency and the budget utilization rate are remarkably improved.

The invention relates to the technical field of battery pack capacity attenuation analysis, and discloses a battery pack capacity attenuation characteristic decoupling analysis method, which comprises the following steps: planning an analysis process based on battery pack design parameters and working conditions, determining electrochemical impedance spectroscopy content and cyclic aging test content, and determining different discharge rate types; generating a capacity attenuation analysis process set, determining an execution sequence according to an optimal matching principle, and generating a spectrogram acquisition setting list and a test scheme list of each magnification; and finally, associating to generate an overall analysis scheme. And the analysis content is updated through real-time operation data, the process execution sequence is adjusted, and a database is established for data management and long-term tracking analysis. According to the method, decoupling analysis of the capacity attenuation characteristics of the battery pack is realized, the analysis accuracy and reliability are improved, and technical support is provided for optimization of the battery pack.

The invention discloses a cold-chain pork quality dynamic evaluation method and system based on multi-source data fusion, and relates to the technical field of data processing and intelligent evaluation, and the method comprises the following steps: collecting multi-source signal information of a whole cold-chain transportation process, sorting according to a unified time sequence, continuously arranging all signals on a time axis, and carrying out data processing on all the signals; a complete dynamic record is formed; and extracting each time interval and signal amplitude change track from the formed dynamic record, analyzing a signal section with repeated wave crests in a short time, and generating a preliminary data manuscript for reflection interference judgment. According to the invention, through time sequence arrangement and dynamic association of multi-source signals, a wave crest track analysis mechanism is constructed, real-time identification and correction of reflection interference are realized, and continuity and accuracy of a gas concentration curve are ensured; and by generating a reflection source position list and adjusting numerical value distribution of repeated fragments, false fluctuation is eliminated, and the stability and reliability of cold-chain pork quality evaluation are improved.

The embodiment of the invention discloses a digital management method and system for a main and distribution network project. The method comprises the following steps: performing project information structured modeling on a full life cycle of a target main and distribution network project to obtain a project stage node index model; chain type tracking analysis is carried out on the engineering stage nodes, an information interaction rule and a data transmission path are established, and a data flow topological graph is obtained; extracting front-end node state layer information and rear-end engineering monitoring layer information based on a front-end and rear-end separation strategy; and constructing a multi-dimensional influence factor association network by using the information to perform risk evolution path deduction and risk event simulation to obtain a simulation result and generate a cross-node cooperative response strategy. According to the embodiment of the invention, through the digital support of the node chain type tracking and the front and back end separation architecture, the data island of each stage of the main and distribution network project is eliminated, the cooperation efficiency of the project management is improved, and the controllability of the whole life cycle process is enhanced.

Systems and techniques for generating track geometry data (TGD) for railroad track analysis. In embodiments, rail profile data for each of the rails of a track may be obtained at regular intervals as a vehicle carrying the system traverses the track. The rail profile data may be validated, and reference points on the profiles of each of the rails corresponding to specific geometric features of the rails may be identified. The rail profile data may be filtered and processed to generate track geometry data. The track geometry data may include data for a plurality of data channels. The track geometry data may be transmitted to a backend system receives for further processing to determine rail defects, and to generate notifications and alerts based on the determined defects. The system utilizes machine learning algorithms and models for defect detection and validation.

The invention relates to the technical field of ship safety, in particular to a ship navigation monitoring management system and method based on edge computing, and the system comprises seven cooperation modules: a data collection module synchronously obtains ship multi-source data, and a processing storage module achieves the data compression, marking and storage. The encryption security module completes full-process AES-256 encryption through a hardware encryption chip, the dual-power supply module guarantees stable power supply, the satellite positioning module obtains accurate positioning through Beidou / GPS dual modes, the self-inspection maintenance module monitors faults in real time, and the AI edge calculation unit achieves channel object recognition, track analysis and violation warning through a deep neural network model. According to the method, closed-loop processes of data acquisition, encryption, processing, intelligent analysis and fault handling are completed through module cooperation; the invention aims to solve the problems of high monitoring delay, insufficient data security, unreliable power supply and the like of the existing system.

A distributed link tracking, analysis method and server, global scheduler, in the process of processing user request, when producing detail event, the meta event for detail event search is produced, the meta event contains tracking identification and event production time information, and the data quantity is less than the data quantity of corresponding detail event; The server saves the detail event and the meta event produced separately in local. The global scheduler in the distributed cluster sends a link query request to the server in the distributed cluster, receives the event information related to the tracking identification returned by the server after local search; and based on the received event information, the user request is analyzed by link. The application adopts local storage, on-demand analysis, removes the central warehouse and large database, solves the problems of high cost of data storage, analysis and network bandwidth, and scalability.

The invention discloses a mechanical arm anti-collision analysis system based on an explosive ordnance disposal robot, and relates to the technical field of public safety, the mechanical arm anti-collision analysis system comprises a multi-source heterogeneous data acquisition module, a space-time alignment characteristic distillation module, an attribute-track coupling prediction module and the like, and precise anti-collision is achieved by fusing obstacle attributes and tracks and gradient protection boundaries. The system has the advantages that attribute data such as obstacle material components and mechanical arm state data are synchronously obtained through the multi-source heterogeneous data acquisition module, features are extracted through fusion of the space-time alignment and feature distillation module, and a standardized data set containing rigid, explosive and quality tags is generated; and the attribute tag is incorporated into a state space by the obstacle attribute-track coupling prediction model, and the obstacle attribute and the motion track are associated to carry out collaborative analysis, so that the defect of separation of dynamic obstacle attribute and track analysis in the prior art is effectively overcome, and an accurate attribute-track association basis is provided for anti-collision analysis.

The invention provides a server cluster load balancing state tracking analysis method, and relates to the technical field of servers, and the method comprises the steps: collecting a load migration triggering moment, the number of control messages generated by single migration, and the number of active connections to be migrated of each server from each server in a cluster, meanwhile, the bandwidth bearing upper limit of a network control channel is obtained, migration triggering events are arranged according to the time sequence, and a list of the number of triggered migration servers is obtained; the migration scheduling strategy of each server in the load balancing system is updated by adopting the target migration coordination delay interval, a migration rhythm coordination confirmation signal is obtained by monitoring the network congestion change, and whether the cluster load balancing state is recovered to a safe range is verified by combining a high-risk time period list, so that the stability and efficiency of load migration are improved, and the load balancing efficiency is improved. And a reliable flow coordination guarantee is provided for a large-scale cluster system.

The invention discloses a network service recommendation method and system based on user behavior track analysis, and relates to the technical field of data analysis, and the method comprises the steps: collecting a power interaction behavior data sequence, and carrying out the analysis of a user behavior track; user power demand interactive capture prediction is carried out on the temporal behavior track characteristics and the spatial behavior track characteristics obtained through analysis, and a target user power demand prediction result is obtained; performing recommendation scheme analysis on the power network service platform to obtain an initial network service recommendation scheme; and obtaining a real-time position of a target user, and performing scheme deepening analysis in combination with the initial network service recommendation scheme to determine a target network service recommendation scheme. According to the method, the technical problems that user behaviors and demands cannot be accurately captured and recommendation services are lack of individuation and real-time performance in the prior art are solved, and the technical effects of accurately predicting user power demands and providing real-time and personalized power network service recommendation are achieved.

The application discloses a food full-link quality deterioration tracing method and system, a medium and a product, and relates to the technical field of food quality tracing.The method is implemented, and a sensory description label in consumer feedback information is extracted by a tracing system; with the aid of a preset food quality knowledge graph, accurate mapping of subjective sensory information and objective physical and chemical indexes is realized, and the problem that subjective feedback and objective data are disconnected in a traditional tracing system is solved.The tracing system carries out dynamic deduction on food full-link monitoring data through a preset quality deterioration dynamics model, and upgrades food quality deterioration from static threshold judgment to dynamic numerical evolution track analysis, so that the cumulative deterioration effect of each circulation link can be quantified.The tracing system screens food quality deterioration responsibility links based on average deterioration rate and link deterioration increment, traces deterioration inducement of the responsibility links in combination with the preset food quality knowledge graph, accurately defines the deterioration responsibility and traces the reasons, and improves the tracing efficiency and accuracy.

The invention discloses an intelligent video analysis system based on multi-mode AI, and belongs to the technical field of video analysis, and the system comprises a video preprocessing module which is used for extracting an analysis frame of an original video segment; the IFS and Tracking analysis module is used for carrying out cross-frame tracking on the analysis frames and screening important frames; the task arrangement and collaboration module is used for realizing state management and control and progress quantification by relying on Redis, and triggering a corresponding module to carry out parcel logo or face recognition if parcels or figures appear in an analysis frame; the logo identification module is used for screening the optimal frame from the analysis frame with the parcel, and determining the logo type of the parcel in combination with target detection and GPT dual identification; the face recognition module is used for carrying out face detection on the analysis frame with the appearance of the person and recognizing the identity of the person; and the structured video abstract generation module is used for generating a structured abstract of the original video segment. According to the method, the video can be efficiently processed, the recognition precision of the target in the video is improved, and subsequent retrieval and search are facilitated.

This invention relates to a method and system for analyzing test data of tool-type steel pipe truss composite slab structures, belonging to the field of testing and inspection technology for prefabricated building structures. The method includes: data parsing and layered storage, differential internal force calculation, recursive solution of isolated body forces, determination of effective flange width, and construction and comparative verification of beam element finite element models. The present invention uses a combined section co-force method to solve for the effective flange width, overcoming the shortcomings of traditional methods that rely on empirical formulas from specifications. This invention establishes a dual-track analysis method for isolated body analysis and verification of the overall beam element finite element model of composite trusses under asymmetric constraint boundaries. This method can be extended to the stress analysis of other steel truss composite slabs in similar engineering scenarios during the construction phase, providing a quantitative analysis tool from test data to design parameters for the engineering design of unsupported composite slabs.

The invention provides a power conductor galloping track extraction and vibration parameter automatic fitting method, and relates to the technical field of power transmission line state monitoring, and the method comprises the steps: collecting and preprocessing a visible light video of a power transmission line, and obtaining an enhanced image; performing Canny edge detection, contour extraction and screening on the enhanced image to obtain a lead area; determining the observation position of each node of the power transmission line in the lead area; establishing an ID-frame-coordinate mapping relation based on multi-point trajectory tracking of nearest neighbor distance matching in combination with observation positions of nodes; and fitting the galloping trajectory of the power transmission line through a trajectory analysis method based on the combination of frequency spectrum estimation and nonlinear fitting in combination with an ID-frame-coordinate mapping relationship. According to the technical scheme, the position of the wire node can be stably identified under different illumination and background conditions, and the motion trail of the wire node can be automatically tracked and extracted.

The application discloses a kind of based on multi-class deviation's magnetic levitation track smoothness evaluation method, medium and equipment, belong to magnetic levitation track analysis field.This method uses hierarchical amplitude evaluation criterion and hierarchical mean evaluation criterion, assesses the smoothness state of target track, wherein determining hierarchical amplitude evaluation criterion and hierarchical mean evaluation criterion includes: based on the layered deformation characteristics of track beam and stator core system, establish multi-class irregularity superposition model;Based on the superposition model, give the random amplitude of multi-class track geometric deviation in line with the set statistical distribution, and generate theoretical track random irregularity sample;Calculate the power spectral density of theoretical track random irregularity sample, and determine the multilevel confidence interval of power spectral density and corresponding track spectral area value;Based on the multilevel confidence interval of power spectral density, define track smoothness hierarchical amplitude evaluation criterion;Based on track spectral area value, define hierarchical mean evaluation criterion.The evaluation result of the application is more scientific, objective and comprehensive.

Systems and methods include an asset tracking platform for tracking, analyzing, and managing facility assets at an operational facility site. The asset tracking platform includes a site operator device in local communication with a field device. The facility assets are assigned to physical asset tags using an assignment procedure that includes scanning the physical asset tag with the field device (e.g., using a radio-frequency identifier (RFID) sensor) to associate an identifier of the physical asset tag with asset data (e.g., location data, an asset identifier, an asset type, etc.). The field device downloads an asset task list using the local communication to represent a list of daily tasks to be completed with the field device. Task execution procedures are performed for the list of daily tasks by scanning the physical asset tag with the field device which starts a timer. Task completion data is synced with the site operator device.

A system and method for interactive learning comprising a content database, at least one software program disposed on at least one computer system designed to calculate story vectors from which to at least one or more of craft and analyze a story and select at least one learning objective, the system including at least one interaction vector determining the action of a story track. At least one machine learning program is designed to at least one or more of create and analyze story tracks. Story track analysis starts from at least one start point in time to at least one following point in time, the at least one software program further adapted to calculate degrees of change from the story vectors including story vector direction and magnitude, the following point in time further marking at least one change result and further adapted to maintain change results from the story vectors.

The utility model belongs to the technical field of quality tracking of catalyst tablet potassium in the production process of fluazinam, and discloses an analyzer for quality tracking of catalyst tablet potassium in the production process of fluazinam, which comprises a base and a fluazinam reaction container, and the fluazinam reaction container is mounted on one side of the upper end face of the base. One side of the fluazinam reaction container is connected with a tracking analyzer, and the tracking analyzer is mainly composed of a sample injection system, an analysis and detection system, a data processing and display system and a control system. According to the device, the mass change of the catalyst flake potassium in the reaction process is accurately tracked in real time, so that the device has important significance on optimizing the production process, improving the product quality and reducing the production cost.

The embodiment of the invention provides a UWB-based highway free flow charging method and device, and the method and device achieve the precise positioning through the innovative design of a multi-base-station positioning network, time difference measurement and angle positioning. A vehicle track analysis system is constructed, and a reliable charging management mechanism is established in combination with identity verification. A transaction security policy is introduced, and user information security is protected through matching verification and encrypted transmission. According to the method, the levels of the traditional technology in the aspects of positioning precision, trajectory analysis and transaction security are effectively improved, and a technical guarantee is provided for highway toll collection.

The invention discloses a perception analysis system based on intelligent management. An operation method of the system comprises the following steps: performing information input and data processing of an intelligent network connection automobile; detecting, tracking, analyzing and processing the intelligent networked automobile; carrying out intelligent network connection automobile traffic conflict analysis, discrimination and management; and carrying out statistics on the user data information of the intelligent networked automobile. The information input and data processing of the intelligent connected automobile comprises the following steps: inputting destination information to the system through the sensing analysis system before the user of the intelligent connected automobile drives each time; distortion elimination processing is carried out on the image information collected by the intelligent network connection automobile equipment; after the laser video all-in-one machine in the intelligent networked automobile completes acquisition of driving data, coordinate system conversion processing is carried out on the driving data. The step of detecting, tracking, analyzing and processing the intelligent networked automobile comprises the step of detecting the position information of the intelligent networked automobile in real time. The system has the characteristics of intelligent analysis and management and high safety.

The invention discloses a shot peening forming method and device based on reverse modeling and a medium. Acquiring a target wing arm plate part to be subjected to shot peening forming, an original shot peening molded surface and a target shot peening molded surface in real time; according to the original shot peening molded surface and the target shot peening molded surface, analysis is conducted through a shot peening forming track analysis method, and a current shot peening track path section and current wing arm plate part rib stringer intersection point distance data are obtained; analyzing and processing through a shot peening forming reverse modeling method to generate a current reverse modeling virtual forming molded surface; and according to the target shot peening molded surface and the current reverse modeling virtual forming molded surface, whether shot peening forming conditions are met or not is judged, and whether shot peening forming operation of the target wing arm plate part is completed or not is determined. The problems that the shot peening effect is poor due to the fact that the shot peening condition of the middle process cannot be determined in the shot peening process of large aircraft parts, and the workload is large due to manual analysis of the middle process are solved, and the shot peening forming accuracy and the analysis efficiency of the middle process are improved.

The invention discloses an aircraft structure load monitoring method. The method comprises the following steps: S1, polishing a bonding surface on the surface of a refitted key structure of an aircraft fuselage; s2, bonding a strain sensor on the bonding surface; s3, a strain / stress monitoring device is installed in a luggage compartment of the airplane; and S4, an optical fiber lead and a power supply and signal line are laid, the optical fiber lead is connected between the strain sensor and the strain / stress monitoring device and used for transmitting strain and stress data of the surface of the refitted key structure in real time, and the power supply and signal line is used for providing a power source for the strain / stress monitoring device and conducting communication. According to the invention, the stress data of the refitted key part of the aircraft fuselage can be accurately collected in real time, and long-term tracking analysis and maintenance decision are facilitated.

The invention relates to the technical field of robots, and discloses an obstacle avoidance method, device and equipment for a self-balancing robot and a medium, and the method comprises the steps: obtaining the three-dimensional space position of an obstacle in an environment, and carrying out the grouping of the currently detected obstacles according to an adjacent relation, and forming an obstacle cluster. And matching the obstacle clusters at the current moment with historical information, and endowing each obstacle cluster with a stable identity label so as to continuously track multiple targets. And analyzing passable gaps between the obstacle clusters with the identities. And determining a longitudinal spatial interval and a required time window for executing the obstacle avoidance action based on an analysis result of the gap. And an obstacle avoidance track is planned according to the space interval and the time window, and the track guides the self-balancing robot to keep self-balance while bypassing the obstacle. Through grouping tracking and spatio-temporal joint planning, the obstacle avoidance stability of the self-balancing robot in a multi-obstacle environment is improved.

The invention relates to the technical field of action tracks, and discloses a track analysis processing method and device, equipment and a storage medium, and the method comprises the steps: obtaining the initial position data of a target object based on a multi-modal technology; performing data processing on the initial position data to obtain an initial behavior track of the target object; performing binding analysis on the initial behavior track and map road network data to obtain an effective behavior track of the target object; obtaining a business area of the target object, and dividing the business area based on an electronic fence technology to obtain a target electronic fence area of the target object; acquiring real-time position information of the target object when the target object advances based on the effective behavior track; and based on the real-time position information and the target electronic fence area, constraining the hyper-trajectory line of the target object. According to the scheme, the working range of the target object is managed and controlled, the super-region problem is found and processed in time, the working route of the target object is optimized, the time cost and the traffic cost are reduced, and the working efficiency is improved.

The invention provides a teaching task allocation system based on dynamic heterogeneous resource perception, and the system comprises a heterogeneous resource collection module, a task feature analysis module, an intelligent scheduling decision module, a dynamic load balancing module, a fault tolerance and recovery module, and a performance evaluation module. The system has the following beneficial effects: 1, a physical layer-virtual layer-container layer three-level monitoring system is combined with an edge cloud cooperation mechanism, so that the periodic energy consumption of teaching is reduced by 25%; and 2, double-track analysis of static compiling instrumentation and dynamic behavior tracking is carried out, and Juser / IDE teaching scene features are accurately identified. The invention also provides a distribution method of the teaching task distribution system based on dynamic heterogeneous resource awareness, and the method has the following beneficial effects: 1, the utilization rate of heterogeneous resources is increased by more than 40%, and the utilization rate of the heterogeneous resources is increased by more than 40%; multi-dimensional feature quantization is realized through tensor decomposition; 2, a double-track analysis engine enables the task matching accuracy to reach 92%, and manual intervention is greatly reduced;

This invention relates to a data processing method for single-event multi-track detection based on a time projection chamber, belonging to the field of particle track analysis technology. The method includes the following steps: S1: Denoising preprocessing of the original points; S2: Reconstructing and correcting all tracks in the event using three-dimensional iterative Hough transform and weighted least squares method, outputting the linear equation of each track; S3: For a given straight line, calculating the distance from all points in the event to the straight line, setting a distance threshold, and considering points less than the threshold as points located on the straight line, thereby achieving track splitting; S4: Overfitting processing of the split tracks. This invention improves the processing effect of time projection chamber and other particle track detectors on single-event multi-track detection, providing a practical solution for high-energy particle multi-track detection and identification.