Patents
Literature
3320 results about "Feature recognition" patented technology
Efficacy Topic
Property
Owner
Technical Advancement
Application Domain
Technology Topic
Technology Field Word
Patent Country/Region
Patent Type
Patent Status
Application Year
Inventor
The term "feature" implies different meanings in different engineering disciplines. This has resulted in many ambiguous definitions for feature. A feature, in computer-aided design (CAD), usually refers to a region of a part with some interesting geometric or topological properties. These are more precisely called form features. Form features contain both shape information and parametric information of a region of interest. They are now ubiquitous in most current CAD software, where they are used as the primary means of creating 3D geometric models. Examples of form features are extruded boss, loft, etc. Form feature is not the only type of feature that is discussed in CAD literature. Sometimes a part's functional or manufacturing features of the subject of attention. Although it is quite possible to see form features and manufacturing features are called by the same name, they are not exactly the same concepts. For example, one may either use the name "pocket" to refer to a swept cut on the boundary of a part model, or to refer to a trace left on the part boundary by a specific machining operation. The former is exclusively concerned with a geometric shape whereas the latter is concerned with both the geometric shape and a manufacturing operation, needing more parameters in its definition. As such, a manufacturing feature can be minimally defined as a form feature (if it has a form that can uniquely represent it), but not necessarily vice versa (forms can be interpreted differently in different manufacturing domains). Machining features are an important subset of manufacturing features. A machining feature can be regarded as the volume swept by a "cutting" tool, which is always a negative (subtracted) volume. Finally, there is also the concept of assembly feature, which encodes the assembly method between connected components.
Building digital twin three-dimensional reconstruction method and system based on large model
The invention discloses a building digital twinning three-dimensional reconstruction method and system based on a large model, and relates to the technical field of building digital twinning and three-dimensional modeling fusion, and the method comprises the steps: laying multi-source equipment in a building, collecting building multi-angle data, and carrying out type distinguishing and structured preprocessing. An adaptive deep network model is constructed and trained to identify building features, and the robustness of the model is improved by adopting a multi-type enhancement strategy. Point cloud splicing and coordinate unification are realized by using a fusion algorithm, and twin model updating and synchronization are realized based on a multi-dimensional threshold. According to the method, high-quality input is established for a depth model; building structure feature recognition has the advantages of robustness and precision; and the twinborn model has dynamic updatable capability. The three parts form a complete closed loop, the technical bottlenecks of a traditional reconstruction method in precision, stability and renewability are finally broken through, and a new building digital twinning three-dimensional modeling path facing a complex scene is achieved.
Owner:中亿丰数字科技集团股份有限公司
Intelligent robot inspection system in power distribution and transformation intelligent auxiliary system
The invention provides an intelligent robot inspection system in a power distribution and transformation intelligent auxiliary system, and relates to the technical field of intelligent sensing and control, and the system comprises a real-time operation collection module which is used for planning a global path of an intelligent inspection robot, generating an initial inspection path, carrying out real-time operation collection, and obtaining a multi-modal detection data set; the fault feature recognition module is used for performing fault feature recognition, generating an abnormal feature set and constructing a dynamic risk map; the simulation maintenance feedback module is used for carrying out simulation maintenance feedback according to the inspection correction path in combination with the equipment maintenance suggestion and generating a maintenance feedback result; and the inspection control module is used for generating an optimized inspection path to perform inspection control on the intelligent inspection robot. According to the invention, the technical problem that the routing inspection efficiency and the fault diagnosis accuracy are influenced because routing inspection path planning often depends on a preset environment map and the intelligent routing inspection robot cannot automatically adjust the routing inspection path according to the change of the equipment state in the prior art is solved.
Owner:JIANGSU ZHIZHENGHE TECH CO LTD
Logistics robot path planning method based on multi-modal perception
InactiveCN120628104ANavigational calculation instrumentsNavigation by speed/acceleration measurementsMulti modal dataOperations research
The invention discloses a logistics robot path planning method based on multi-modal perception, and relates to the technical field of robot path planning. Laser radar, visual camera and IMU data are fused, and environment state feature vectors are generated through multi-modal data synchronization and space-time alignment; the method comprises the following steps: analyzing environmental semantics by using models such as PointPill and YOLOv8, extracting dynamic characteristics, and identifying obstacles; constructing a space-time risk field, searching a path by a space-time algorithm, converting path points into a continuous trajectory, and optimizing the continuous trajectory; deviation is evaluated in real time, dynamic re-planning is triggered, and multi-robot cooperation and environment semantic understanding are included. Through multi-mode perception fusion, hierarchical planning, multi-target optimization and a cooperation mechanism, the obstacle detection accuracy and the obstacle avoidance success rate are improved, the path planning time is shortened, the energy consumption is reduced, the multi-robot conflict is reduced, the task efficiency is improved, the environment semantic understanding and task adaptive ability is enhanced, and the method is suitable for scenes such as intelligent storage and the like and has wide application prospects. The automation level is improved.
Owner:TIANJIN SINO GERMAN VOCATIONAL TECHNICAL COLLEGE
Physical prior and spatio-temporal evolution fused remote sensing image ocean green tide monitoring method and system
The invention relates to the technical field of remote sensing monitoring, in particular to a remote sensing image ocean green tide monitoring method and system fusing physical prior and spatio-temporal evolution. The method comprises the following steps: acquiring a multi-modal remote sensing monitoring image; performing multi-modal feature extraction on the acquired image, wherein the multi-modal feature extraction comprises spectral reflectivity feature extraction, ocean dynamics feature extraction and feature alignment and unified representation; establishing a physical prior of a green tide characteristic wave band by using an ocean optical radiation transmission model; constructing a dynamic space-time diagram based on the extracted multi-modal features to obtain a node global feature vector and a dynamic adjacency matrix; carrying out adaptive graph convolution feature coding based on physical prior and a dynamic space-time diagram; through fusion of multi-spectral images of multiple platforms such as satellites and unmanned aerial vehicles and ocean dynamic data and combination of atmospheric correction and wave band resampling, consistency processing and high-precision extraction of multi-source features are realized, and comprehensiveness and reliability of green tide feature recognition are remarkably improved.
Owner:SHANDONG MARINE RESOURCE AND ENVIRONMENT RESEARCH INSTITUTE (SHANDONG MARINE ENVIRONMENTAL MONITORING CENTER SHANDONG AQUATIC PRODUCTS QUALITY INSPECTION CENTER)
Circuit board detection method and system based on machine vision
The invention provides a circuit board detection method and system based on machine vision, and the method comprises the steps: obtaining an original visual data set of a to-be-detected circuit board, carrying out the visual information optimization processing of the original visual data set, and obtaining a standardized image set with unified illumination intensity and contrast, calling a pre-trained defect discrimination model to perform key feature recognition processing on the standardized image set, generating a potential defect feature set of the circuit board in the image, and determining defect types existing in the to-be-detected circuit board and position distribution feature information of defects in the image according to the potential defect feature set, and generating a detection result report containing defect positioning coordinates based on the defect type and the position distribution feature information, and outputting the detection result report to a target display terminal to complete the detection process. According to the invention, the accuracy of defect identification is improved, and the reliability of defect positioning is ensured in combination with the position marking information, so that the overall quality of a circuit board detection result is effectively improved.
Owner:GUIZHOU RADIO & TV UNIV +1
Fluid pipeline topology optimization design method based on parameter simulation model
The invention relates to the technical field of fluid pipeline topological optimization, in particular to a fluid pipeline topological optimization design method based on a parameter simulation model. The method comprises the following steps of performing parametric modeling on a fluid pipeline to obtain a pipeline topology geometric parameter set; according to topological feature identification of the pipeline topology geometric parameter set, obtaining pipeline topology description data; constructing a multi-physics field equation set according to the pipeline topology description data to obtain a pipeline coupling field basic equation set; carrying out characteristic decomposition on the pipeline coupling field basic equation set to obtain a pipeline decoupling equation set; performing iterative solution on the pipeline decoupling equation set to obtain a pipeline multi-physics field coupling solution; performing sensitivity coefficient evaluation according to the pipeline multi-physics field coupling solution to obtain pipeline physics field sensitivity; and performing time domain integral response analysis on the pipeline physical field sensitivity to obtain the contribution degree of the pipeline physical field. According to the method, the deviation between the topological design and the practical application of the fluid pipeline can be obviously reduced.
Owner:SHENZHEN MINGJIE MOULD PLASTIC PROD CO LTD
Rock burst early warning method and system based on data-mechanism dual drive
The invention discloses a data-mechanism dual-drive-based rock burst early warning method and system, and the method comprises the following steps: deploying a multi-modal sensor network to collect coal and rock stratum data, building a rock burst disaster precursor information sample database, providing a rock burst disaster multi-modal data precursor feature recognition algorithm, and carrying out the recognition of rock burst disaster multi-modal data precursor features. Mining the relevance between the multi-modal data and disaster-causing key risk indexes, and establishing a rock burst disaster multi-modal data prediction model; establishing a three-dimensional geological geometric model, fusing a multi-field coupling dynamics constitutive model and a catastrophe criterion, constructing a PINN physical information neural network prediction model of the rock burst disaster, and obtaining a time-space evolution rule of an energy field of a target area; providing a loss function coupling calculation method of a multi-modal data driving sample error and a physical driving control equation residual error, dynamic data and mechanism prediction result weight, comprehensively calculating a risk score, and accurately judging a top disaster danger level.
Owner:CHINA UNIV OF MINING & TECH
Electromechanical engineering construction information management method and system and medium
ActiveCN119849944AMathematical modelsCharacter and pattern recognitionRisk levelConstruction management
The invention discloses an electromechanical engineering construction information management method and system and a medium, and relates to the field of electromechanical engineering, and the method comprises the steps: collecting an electromechanical engineering construction site image set; performing feature recognition on the image set; according to an identification result, dividing construction personnel behavior risk levels and marking material attributes; the method comprises the following steps: dividing a construction process into a plurality of stages, constructing a Bayesian network model of a time slice in each stage, adding a time sequence dependency relationship between the Bayesian network models of adjacent time slices, and establishing dynamic Bayesian network risk evolution models of different stages of the construction process; predicting a risk distribution thermodynamic diagram of each construction stage in a future period of time by using a dynamic Bayesian network risk evolution model; and performing construction management according to the risk distribution thermodynamic diagram. For static risk assessment by adopting traditional Bayesian reasoning in the prior art, the accuracy and real-time performance of electromechanical engineering construction risk prediction are improved.
Owner:ZHEJIANG ZHUAN CONSTR GRP
Automatic water quality monitoring method and system
ActiveCN120748554AChemical property predictionMolecular entity identificationWater qualityData-driven
The invention relates to the technical field of water quality monitoring, in particular to an automatic water quality monitoring method and system.The method comprises the steps that multiple pieces of collected water quality monitoring data are combined pairwise, dynamic coupling strength is calculated, a topological network atlas is generated, and automatic extraction and structural characterization of the dynamic coupling relation among complex water quality parameters are achieved; the limitation of dependence on manual feature recognition traditionally is overcome; secondly, matching the topological network atlas with a preset pollution mode feature library, dynamically determining a newly added abnormal mode, and outputting an abnormal feature code set, thereby solving the key defect that a static model cannot recognize an unknown pollution mode; and finally, a water quality monitoring and early warning signal is output by fusing the pollution diffusion prediction result and the abnormal feature code set, so that bidirectional verification of data driving and a mechanism model is realized, and the early warning accuracy of a water quality abnormal phenomenon is remarkably improved.
Owner:HUNAN DUJIANG ENG TECH CO LTD
Geological data interaction method and system based on Ovi interaction map
The invention relates to the technical field of Otwei interactive maps, and discloses a geological data interaction method and system based on an Otwei interactive map. The method comprises the following steps: carrying out feature recognition and structural analysis on original geological data to obtain a standardized data packet, and establishing a geographic space reference conversion index table; performing feature extraction and classification on geological elements in the standardized data packet to obtain structured geological data; importing the structured geological data into an Ovoucher interactive map, and carrying out local registration through a mesh generation technology to obtain a visual geological element map layer; geological element drawing and attribute input are carried out, and an edited geological data set is obtained; and carrying out structure recombination and reverse coordinate conversion to obtain a standard format data file adaptive to the target geological information system. According to the method, accurate conversion of multi-source geological data between different coordinate systems and measuring scales is realized, and the problem of spatial dislocation during integration of different-source geological data in a traditional method is effectively solved.
Owner:HENAN NO 4 GEOLOGICAL SURVEY INST CO LTD +1
Seawater parameter calibration system
ActiveCN119920364AMolecular entity identificationMaterial analysis by electric/magnetic meansSoil scienceWireless transmission
The invention provides a seawater parameter calibration system, and belongs to the technical field of seawater parameter measurement. A thermohaline depth device is used for constructing a three-dimensional structure model to identify a spring layer position, a multi-parameter water quality sensing device is used for collecting data to establish a correlation model, and a dissolved oxygen analysis device is combined with thermohaline data to calculate a correction coefficient; and the spectral analysis device extracts feature recognition chemical components. The method comprises the key steps that a parameter interaction compensation function and an OceanParamNet model are adopted to construct a seawater comprehensive parameter calibration model, original data are corrected, and abnormal values are detected. The system realizes layered storage and wireless transmission of data, dynamically adjusts sampling frequency and power consumption, periodically executes a self-calibration program to compensate aging drift of a sensor, realizes high-precision self-adaptive calibration of seawater parameters, and solves the technical problems of low precision and poor environmental adaptability of seawater multi-parameter collaborative calibration in the prior art.
Owner:青岛道万科技有限公司
Unmanned car washer stain panoramic identification system
The invention discloses an unmanned car washer stain panorama identification system. The system operation process specifically comprises the following steps: acquiring panorama image data of a target car; preprocessing the panoramic image data to obtain a standardized panoramic image set; performing stain area identification on the standardized panoramic image set based on a deep learning model to generate an initial stain distribution diagram; performing stain type classification on the initial stain distribution diagram according to a stain feature database to generate a stain classification result set; generating a dynamic cleaning path instruction set based on the stain classification result set and a cleaning strategy library; real-time images in the cleaning process are collected in real time, real-time stain residue analysis is conducted, and finally a cleaning effect feedback report is generated. The method has the following advantages and effects that the system of multi-dimensional stain feature recognition, classification and dynamic decision can be fused, so that the core contradiction that the cleaning strategy is not matched with the stain features in the prior art is solved.
Owner:SHENZHEN MIAOMIAO IOT TECH CO LTD
Self-adaptive deployment method and system oriented to credential heterogeneous environment
ActiveCN120104142ADigital data protectionPlatform integrity maintainanceCpu architectureTopological sorting
The invention relates to the technical field of automatic deployment of cloud computing platforms, in particular to a self-adaptive deployment method and system oriented to a credential heterogeneous environment. Aiming at three technical bottlenecks of low multi-CPU architecture adaptation efficiency, frequent software dependence conflicts and complex security baseline configuration in a localization process, a heterogeneous computing resource intelligent scheduling engine and a dynamic security policy generation mechanism are innovatively provided. The method comprises the following steps: constructing a heterogeneous resource portrait through a hardware feature automatic identification technology, and realizing component installation sequence optimization based on a DAG dependency relationship analysis algorithm and Kahn topological sorting; and creating an adaptive network security policy, and sensing the firewall state of the target system in real time through a probe. Compared with a traditional deployment mode, the method supports cross-architecture compatibility, solves the problem of dependency conflicts, improves deployment efficiency, and guarantees consistency and safety of the system.
Owner:TONGFANG KNOWLEDGE DIGITAL PUBLISHING TECH CO LTD
Large-scene monitoring video abnormal event early warning method based on multi-modal large model
The invention relates to the technical field of abnormal event early warning, and provides a large-scene monitoring video abnormal event early warning method based on a multi-mode large model. According to the invention, the problems of delay, low accuracy and limited coverage range of abnormal event early warning of large-scene monitoring videos in the prior art are solved. According to the main scheme, multiple paths of high-resolution monitoring videos are spliced and preprocessed to generate a panoramic video; synchronously acquiring and preprocessing audio and sensor data to construct a multi-modal data set; video key frames are extracted by adopting a traditional small model, and the video key frames and multi-modal data are jointly input into a multi-modal large model based on a Transform architecture for deep feature fusion; abnormal events such as tumble, congestion and fight are identified based on the fusion features; triggering an early warning mechanism to send event type and position information in real time; and storing the full-dimensional data of the abnormal event for tracing analysis. The real-time processing performance is optimized through edge calculation, the complex scene understanding ability is enhanced in combination with a multi-modal large model, and the detection precision and the response speed are remarkably improved.
Owner:PEKING UNIV (TIANJIN BINHAI) NEW GENERATION INFORMATION TECH RES INST +1
Injection mold part feature recognition method based on improved PointNet + +
The invention discloses an injection mold part feature recognition method based on improved PointNet + +, and the method comprises the steps: obtaining standard injection molding part models of a plurality of injection mold parts, and carrying out the uniform sampling of point clouds, and constructing a point cloud set; performing label labeling based on RGB information on each point of the point cloud set according to different processing feature types, and then performing normalization, random scaling and random translation; constructing and training a classification label prediction model based on an improved PointNet + + network according to the processed point cloud set; the entity model of the injection mold part needing feature recognition is converted into point cloud data, the point cloud data are input into the trained classification label prediction model, semantic segmentation output of different machining features is obtained, the semantic segmentation output is matched with the entity model of the injection mold part needing feature recognition in a mapping mode, and feature recognition is achieved. According to the method, data loss and precision reduction are avoided, and the feature recognition efficiency is improved.
Owner:ZHEJIANG UNIV +1
Visual intelligent management tool system for power grid operation risk level
The invention relates to the technical field of power systems, in particular to a power grid operation risk level visualization intelligent management tool system. The system obtains power grid operation data through an Internet of Things sensor network, wherein the power grid operation data comprises current, voltage, equipment operation state and other multi-dimensional information; performing real-time analysis on the acquired data by adopting multi-level clustering analysis, a predictive maintenance algorithm and a deep learning model to realize abnormal behavior identification and risk prediction; a dynamic risk map is constructed based on a GIS technology, and accurate positioning and real-time display of risk levels are realized in combination with regional feature recognition and personalized threshold setting. According to the invention, multi-source data acquisition, intelligent analysis and visual presentation are creatively and organically integrated to form a closed-loop risk management system, so that the system has adaptive learning ability. Practical application shows that the system can early warn potential risks 30 minutes in advance, the operation and maintenance response time is shortened to 3 minutes, and the power grid operation risk monitoring and management efficiency is remarkably improved.
Owner:GUIZHOU POWER GRID CO LTD
Analysis method of water quality fingerprint database based on feature recognition
ActiveCN120108576AGeneral water supply conservationCheminformatics data warehousingWater qualityEngineering
The invention belongs to the technical field of water pollutant traceability, and particularly discloses a water quality fingerprint database analysis method based on feature recognition, which relates to the field of water pollutant traceability, and comprises the following steps: cross-comparing feature curved surface information of different upstream and downstream under feature peak whole database data and sorting to obtain pollutant features under different intensities; the pollution source type is identified according to the pollutant difference; sorting the characteristic curved surface information of the water body samples reflecting different nodes, calling a chemical characteristic analysis result, outputting a chemical characteristic sequence, and selecting a first sequence sampling point position of the chemical characteristic sequence corresponding to the spectral characteristics of the identified pollution source type as a pollution source; according to the method, whether the identification result is met or not is analyzed according to the biological characteristics of the pollution source, efficient source tracing is carried out on water pollutants, an accurate pollutant transmission path is output, meanwhile, the corresponding pollutant type is evaluated, the corresponding pollutant diffusion trend is given, and powerful data is provided for follow-up pollutant treatment.
Owner:CHENGDU BIG DATA IND TECH RES INST CO LTD
Leakage detection and partial discharge digital imaging detection method and system based on acousto-optic fusion
PendingCN120274964ADetection of fluid at leakage pointCharacter and pattern recognitionDigital imagingSound sources
The invention relates to the technical field of nondestructive testing, in particular to a leak detection and partial discharge digital imaging detection method and system based on acousto-optic fusion, and the method comprises the following steps: based on channel microphone array sound wave data in a partial discharge signal suspicious region, extracting a sound wave abnormal section, positioning a sound source, matching image edge features, and synchronously marking; and analyzing the phase change of the multi-frequency signal to judge a sound source concentration area, tracking the moving trend of a disturbance point, and outputting an acousto-optic fusion positioning trend track. According to the method, the partial discharge feature recognition sensitivity is improved through high-frequency peak paragraph screening and dominant frequency recognition, the abnormal region positioning precision is enhanced in combination with image edge extraction and sound source space matching, and acousto-optic synchronous positioning and trend trajectory display are achieved through multi-frequency signal phase analysis and image frame disturbance tracking. Through fusion of frequency domain feature extraction, image recognition, dynamic comparison and other actions, the spatial precision of abnormal source recognition and the multi-source fusion analysis efficiency are improved, and the partial discharge traceability and dynamic monitoring capability are enhanced.
Owner:李美娟 +1
Slurry pump motion monitoring management system based on data analysis
The invention relates to the technical field of vibration monitoring, in particular to a slurry pump motion monitoring management system based on data analysis, which comprises a multi-source acquisition module, a period judgment module, a trend focusing module and a dynamic management and control module. According to the method, vibration data are collected through a three-axis acceleration sensor, a fundamental frequency amplitude is extracted through FFT, time-frequency characteristics and periodic distribution are fused in combination with an extreme value interval sequence, the data representation dimension is enhanced, the rising slope is processed through moving average, the periodic variation is calculated, random noise is restrained, and trend continuity is enhanced. Monotonicity test is combined with dynamic threshold judgment to improve anomaly recognition sensitivity; a sliding window is used for segmenting multi-cycle data; a sudden change interval is positioned based on a pressure amplification rate second derivative; the limitation of a frequency domain on transient feature recognition is broken through, a pressure amplification rate three-dimensional vector is constructed, cosine similarity is calculated, and a working condition difference degree is quantified to dynamically bind a maintenance instruction; and closed-loop feedback is formed to improve the early warning and decision matching degree.
Owner:SHANDONG PUMPFEI NEW MATERIALS TECHNOLOGY RESEARCH & DEVELOPMENT CO LTD
Instruction execution method and device for artificial intelligence chip
The invention discloses an instruction execution method and device for an artificial intelligence chip, and relates to the technical field of artificial intelligence chips, and the method comprises the steps: carrying out the deep learning driven feature recognition and resource demand prediction of an input task, and generating a demand prediction report of the task for computing resources through the analysis of a computational graph and a data dependency relationship of the task; a computing unit and memory resources are intelligently scheduled, an optimal instruction execution path is dynamically selected, and meanwhile a caching strategy is optimized; automatically generating a micro instruction set corresponding to the task according to the computing resource demand, the computing characteristic and the intelligent scheduling result of the task; when multiple tasks are executed in parallel, the execution sequence of the multiple tasks is dynamically adjusted according to the calculation load and the resource sharing condition of the tasks, and resource allocation is optimized. According to the method, the computing resources and the memory bandwidth required by each task can be accurately predicted through the deep learning driving analysis of the task computing graph, so that the allocation of the computing resources is optimized.
Owner:BEIJING LEKAIWENYU TECHNOLOGY CO LTD
Underground powerhouse construction risk identification and disposal method, system, equipment and medium
The invention relates to the field of underground powerhouse construction risk identification, and provides an underground powerhouse construction risk identification and disposal method, system, device and medium, and the method comprises the steps: collecting multi-source heterogeneous data in real time, obtaining historical risk case data, and carrying out the preprocessing to obtain structured time-space correlation data; constructing a multi-dimensional analysis model based on a parallel computing algorithm, and performing multi-scale risk analysis on the structured time-space associated data to obtain multi-level risk feature data; performing risk feature recognition through a multi-modal machine learning model to obtain risk quantitative indexes, and performing recognition based on a fuzzy comprehensive evaluation algorithm to obtain construction risk levels; and matching emergency strategies of construction risk levels, carrying out parameter expansion through a combinatorial optimization algorithm, generating a plurality of candidate disposal schemes, carrying out weight calculation and sorting on the candidate disposal schemes by adopting a multi-criterion evaluation model, and outputting an optimal disposal scheme. According to the invention, efficient identification and accurate emergency decision-making of the construction risk of the underground powerhouse are realized.
Owner:ECONOMIC & TECH RES INST OF HUBEI ELECTRIC POWER COMPANY SGCC
Intelligent tracing method for process medium leaked in circulating water
PendingCN120561600AGeneral water supply conservationVisual data miningProcess equipmentWater quality
The invention relates to the technical field of industrial water system safety monitoring, in particular to an intelligent source tracing method for a process medium leaked in circulating water, which comprises the following steps of: acquiring multi-dimensional operating parameters such as conductivity, pH value, turbidity, dissolved oxygen, temperature, pressure and characteristic ion concentration; a standardized water quality parameter matrix is generated after space-time alignment and wavelet noise reduction; the method comprises the following steps: extracting an abnormal fluctuation signal by using a leakage feature recognition model based on transfer learning, simulating a diffusion process through a three-dimensional leakage diffusion model, realizing leakage source positioning by combining reverse particle tracking and kernel density estimation, associating a high-probability leakage region with upstream process equipment, extracting backtracking path features, and matching a process medium feature library, thereby realizing leakage source positioning. The leakage medium type is judged; and finally generating a structured traceability report. According to the method, high-precision identification, positioning and medium analysis of process leakage in a complex circulating water system can be realized, and the method has relatively high practicability and popularization value.
Owner:QINGDAO JIANGHAO ENVIRONMENTAL PROTECTION TECH CO LTD
Low-altitude unmanned aerial vehicle trajectory tracking and monitoring method based on 5G-A communication and inductance integrated base station
ActiveCN121393218ASynchronisation arrangementNetwork traffic/resource managementData streamInterference (communication)
The invention discloses a low-altitude unmanned aerial vehicle trajectory tracking and monitoring method based on a 5G-A communication sensing integrated base station, and relates to the technical field of low-altitude traffic management and communication sensing fusion, and the method comprises the steps: firstly collecting multi-source data such as a communication sensing fusion signal, environment interference and unmanned aerial vehicle attributes, and carrying out the alignment and packaging of a unified timestamp and a coordinate system into a synchronous data frame; then, deep fusion and anti-interference processing are carried out on the data frames, noise is filtered out, and pure fusion data is generated; and furthermore, real-time track calculation and motion trend prediction are carried out on pure data by utilizing multi-base-station cooperative calculation and prediction. Based on this, through a multi-target feature recognition and clustering separation mechanism, independent individual trajectories are accurately stripped from a complex mixed data stream, and compliance verification and anomaly judgment are performed on the trajectories in combination with an airspace rule base. In this way, the problems of signal interference and multi-target aliasing in a complex environment can be effectively solved, and therefore high-precision global tracking of the low-altitude unmanned aerial vehicle and real-time monitoring of abnormal behaviors are achieved.
Owner:JIANGSU XINWANG VIDEO SOFTWARE TECH CO LTD
Defoaming agent foam distribution analysis method based on image feature recognition
The invention discloses a defoaming agent foam distribution analysis method based on image feature recognition, and particularly relates to the field of industrial foam behavior perception and analysis for recognizing an image object with a random mode as a feature, and the method comprises the following steps: obtaining a foam image sequence in a target area, and collecting the foam image sequence through imaging equipment, the image frames of the foam image sequence have time continuity; and performing disturbance feature extraction operation on the foam image sequence to obtain local disturbance speed information, membrane surface tension change trend information and form boundary fluctuation information of the foam edge within a preset time. According to the method, foam structure disturbance characteristics are extracted from an image time sequence, a structure evolution graph memory bank is constructed, and irregular sudden change image behaviors are identified in combination with a trend matching mechanism, so that dynamic perception and abnormal response of a sudden foam state without prior support are realized, and the problem that a random mode foam state cannot be identified is solved.
Owner:HANGZHOU SERAPH TECH CO LTD
Remote sensing image multi-class ground feature recognition method based on self-supervised learning
ActiveCN119810672ACharacter and pattern recognitionBiological modelsSupervised learningSpatial consistency
The invention discloses a remote sensing image multi-class ground feature recognition method based on self-supervised learning. The method comprises the following steps: S1, generating standardized remote sensing image data; s2, performing feature pre-training on the standardized remote sensing image data based on self-supervised learning, and outputting depth feature representation; s3, inputting the depth feature representation into a gradient enhancement decision tree classification module, and outputting a preliminary classification result; s4, updating a gradient enhancement decision tree classification module; s5, converting the depth feature representation into low-dimensional feature representation through a feature distillation module, and outputting an optimization classification result; and S6, implementing space consistency optimization, classification boundary refinement and category redistribution on the optimized classification result, and generating a final remote sensing image multi-category ground feature recognition result. According to the method, the classification precision and the category distinguishing capability of complex ground feature categories are remarkably improved.
Owner:JIMEI UNIV
Mechanical transmission system fault trend prediction system based on dynamic feature recognition
The invention discloses a mechanical transmission system fault trend prediction system based on dynamic feature recognition, and relates to the technical field of mechanical state monitoring. Comprising the following steps: synchronously acquiring a load torque signal and a lubrication state parameter signal of a transmission system and vibration acceleration signals of a plurality of measuring points through a signal acquisition module; the working condition decoupling characteristic generation module carries out time-frequency analysis on the vibration signal, calls a pre-stored load disturbance spectrum template according to a load torque signal to carry out adaptive differential processing so as to eliminate load fluctuation interference, and calls a correction rule set according to a lubrication state parameter signal to carry out form recombination on the signal so as to compensate the lubrication state influence; and finally outputting a working condition decoupling feature representing the health state of the mechanical part. And the trend prediction module calculates and obtains fault development trend and residual life estimation data through a pre-trained fault prediction model. According to the method, the dynamic characteristics representing the essential degradation of the part are effectively extracted, and the accuracy and reliability of fault trend prediction of the mechanical transmission system are improved.
Owner:HARBIN UNIV OF SCI & TECH
Unit magnetic variable online monitoring method and system
The invention relates to the technical field of unit detection, in particular to a unit magnetic variable on-line monitoring method and system, and the method comprises the steps: carrying out the multi-source data collection through a sensor, carrying out the correction of the multi-source data through a multi-dimensional calibration mechanism, synchronizing a timestamp through a dual-synchronization system, and carrying out the frequency-band-divided conditioning and standardization processing; environmental noise in the standardized multi-source data is eliminated through an intelligent algorithm, feature vectors are extracted, and purified feature vectors are obtained; screening effective abnormal features through an isolation forest algorithm; and inputting the effective abnormal features into an LSTM prediction model to obtain a corrected prediction value, substituting the corrected prediction value into a logistic regression formula to obtain a fault prediction probability of fault occurrence, calculating a health degree score, and performing graded early warning according to the health degree score. According to the scheme, through multi-dimensional calibration, working condition adaptive feature extraction and graded early warning, the unit monitoring data precision, the fault feature recognition accuracy and the operation and maintenance decision efficiency are improved.
Owner:BEIJING HUAKE TONGAN MONITORING TECH CO LTD
Remote sensing image enhancement method and system based on visual analysis
The invention relates to the technical field of image enhancement, in particular to a remote sensing image enhancement method and system based on visual analysis. The method comprises the following steps: firstly, acquiring a plurality of preliminary connected domains of a remote sensing image through a connected domain algorithm; then, according to the color, the texture condition, the area and the shortest distance among all edge pixel points in each preliminary connected domain, obtaining a plurality of connected domains of the remote sensing image, calculating local feature indexes of the connected domains, evaluating the merging possibility, clustering and dividing earth surface feature regions, determining the pixel point window side length and the neighborhood pixel weight, and finally, obtaining the remote sensing image. And performing enhancement processing on the remote sensing image according to the weight. According to the remote sensing image enhancement method provided by the invention, the quality of the remote sensing image is effectively enhanced, the earth surface feature recognition precision is improved, the noise is effectively removed while important details are kept, the filtering result can more accurately conform to the actual features of the image, key information is kept, and the processing efficiency and the visual effect are improved.
Owner:SHANDONG GEO-SURVEYING & MAPPING INST
Station electric equipment steady state feature extraction system based on load perception
ActiveCN119807713AData processing applicationsComplex mathematical operationsData setElectric power equipment
The invention relates to the technical field of power equipment load management, in particular to a station electric equipment steady-state feature extraction system based on load awareness, and the system comprises a load data processing module which obtains load data based on the operation state of power equipment, analyzes the interaction effect between each type of load data, extracts the correlation features between parameters, and outputs the correlation features between the parameters; and identifying periodic characteristics and abnormal fluctuation of the load data to obtain a standard load data set. According to the method, more accurate and comprehensive steady-state feature extraction of the power equipment can be realized through multi-dimensional parameter analysis and processing of the load data. Meanwhile, the load data interaction effect is calculated, the incidence relation between the parameters can be better recognized and analyzed, the data consistency is ensured, and the feature extraction accuracy is improved. In data quantile analysis, data subsets of different quantiles are constructed, parameter characteristics under the steady-state condition are extracted, and subtle differences of equipment under different steady-state conditions can be captured.
Owner:国网山西省电力有限公司超高压变电分公司
Intelligent electric meter fault early warning method and system based on multi-parameter synchronous measurement
ActiveCN120198842ACharacter and pattern recognitionBiological modelsElectric power systemSmart meter
The invention discloses an intelligent electric meter fault early warning method and system based on multi-parameter synchronous measurement. The method comprises the step of synchronously collecting operation videos, reading data and environmental parameters of the electricity meter. Firstly, illumination compensation optimization is performed on a video, image features are extracted through a convolutional layer and a full connection layer, a comprehensive visual feature vector is constructed in combination with a cross attention mechanism and environmental parameters, and the overall shape of an electric meter is extracted to detail features in a layered manner; the change trend and fluctuation characteristics are extracted from the reading data by using time sequence analysis, and the influence of environmental factors is considered. Then, fusing multi-source features to generate a feature map reflecting the state of the electric meter; normal and fault state features are compared through similarity calculation, and a fault risk is identified and early warning is carried out; and evaluating a result by using ID matching and a machine learning algorithm, and optimizing fault early warning in combination with historical data. By implementing the method, multi-source information can be fused, the speed and accuracy of fault diagnosis can be remarkably improved, and continuous and stable operation of a power system is ensured.
Owner:SHENZHEN JIANGJI IND