111 results about "Location technology" patented technology

The invention relates to the technical field of fault positioning, and discloses an indoor distribution multi-source data fusion fault positioning system based on reinforcement learning, which comprises a space-time tensor construction module, a federated collaborative detection module, a map reasoning positioning module and a prediction scheduling module, and is characterized in that a multi-source space-time data federated learning framework under privacy protection is constructed; and cross-physical domain dynamic reasoning and resource elastic scheduling of the fault propagation chain are realized. According to the method, through fusion of multi-source spatio-temporal data and federal collaborative learning, fundamental transformation from passive response to active prediction is realized, fault root causes in a complex environment can be accurately identified, and the false alarm rate is significantly reduced; equipment deadlock is effectively avoided by a dynamic resource scheduling mechanism, and the operation and maintenance efficiency is improved; the privacy protection design ensures the safety of cross-domain cooperation, meanwhile, the environmental perception capability enhances the robustness to hidden faults such as electromagnetic interference, and finally, a fault prediction-positioning-scheduling full-process closed loop is constructed.

The invention relates to the technical field of intelligent positioning of building construction, in particular to an intelligent positioning method and system for fabricated building laminated slabs based on AR and UWB. According to the method, a physical monitoring network comprising a UWB positioning base station and a visual positioning target is constructed, a digital operation instruction generated by analysis of a cloud BIM model is converted into a virtual contour superposed on a real operation plane by using an AR augmented reality technology, and further, the position deviation is calculated in real time and a sound-light alarm mechanism is combined, so that the real-time positioning of the cloud BIM model is realized. A construction quality closed-loop control system of real-time monitoring, alarming, adjusting and compliance is established, it is ensured that the laminated slab meets the design precision requirement in the installation process, and later reworking and rectification caused by installation errors are effectively avoided; meanwhile, based on data interaction of the cloud BIM management platform, full-process digital management from design model issuing to final installation position data returning is achieved, and reliable data support is provided for construction quality tracing and acceptance of the fabricated building.

The invention discloses a server fault diagnosis system based on service topology correlation analysis, and relates to the technical field of computer data processing and automatic fault localization, and the system comprises a service topology construction module which is used for collecting multi-source heterogeneous data to construct infrastructure, runtime environment and business performance feature vectors, a service dependence topological graph is maintained; the fault storm diagnosis module is used for identifying a fault storm by calculating node state weights and utilizing spatial compactness and a time synchronization coefficient, and positioning a root cause node based on reverse breadth-first search and a fault propagation index; and the fusion alarm generation module is used for calculating the response time contribution degree of the root cause node to verify the causal relationship so as to distinguish dominant storm and hidden faults. The system executes cascade alarm convergence for dominant storm, triggers snapshot capture during deep operation for hidden faults, locates hidden root causes under complex topology, and realizes automatic fault closed-loop processing.

The invention discloses a railway power distribution network fault information automatic diagnosis and positioning method and system, and belongs to the technical field of power distribution fault diagnosis and positioning, and the method comprises the steps: employing an auxiliary classification generation adversarial network, obtaining a class-balanced standardized training data set, and carrying out the preprocessing; mapping the preprocessed data in the standardized training data set into a snowflake-shaped SDP image under a two-dimensional polar coordinate system, inputting the snowflake-shaped SDP image into a fault diagnosis model based on a deep convolutional neural network, and outputting a fault section and a preliminary fault distance; constructing a physical circuit model of railway power distribution network distribution parameters, and calculating theoretical simulation voltage and simulation current by using a transmission line equation; and starting iterative correction based on the Pearson's correlation coefficient of each data, and outputting a diagnosis result. According to the method, high-precision, high-reliability and self-adaptive fault information automatic diagnosis and positioning are realized by fusing data enhancement, feature transformation, intelligent diagnosis, physical inversion check and topology self-adaptive adjustment.

Disclosed are a key facility gas safety assurance method and a system, comprising the steps: 1. acquiring basic data; 2. using BIM technology to perform three-dimensional modeling of a key facility; 3. reviewing a model; 4. performing lightweight model handover of the reviewed model; 5. performing model splitting, control dashboard design, function development, and project deployment on a plan by means of a corresponding platform side of a key facility digital delivery platform adopting a B / S architecture; and optimizing the model by means of a corresponding mobile client utilizing AR and positioning technologies, then uploading the model to an AR collaborative platform, and performing location verification by means of creating a two-dimensional code on the AR collaborative platform and deploying the two-dimensional code. The present invention enables real-time monitoring, rapid linkage, intelligent command, and safety control of a gas system in a key facility.

This invention discloses a fire-fighting location and communication method and system that integrates multi-source sensing data, relating to the fields of fire-fighting location technology and communication technology. The invention significantly suppresses time drift at each node through a time calibration mechanism within the topological neighborhood. The corrected timestamp set generated by iterative correction ensures high consistency in cross-node timing, thereby improving the synchronization and reliability of multi-source data fusion. A dynamic generation strategy based on local gradients and communication status heartbeat signals enables the broadcast period to adapt to link fluctuations, improving network robustness in scenarios with thermal interference or smoke obstruction. Furthermore, the location and communication status table uniformly quantifies the location information interval, movement trend, and communication availability level, enabling synchronous optimization of location inference and communication routing selection, significantly improving the location accuracy and communication continuity for firefighters in complex environments.

This invention relates to the field of fault location technology and discloses a fault location method for a long-distance conveying inspection robot. The method includes: when the inspection robot performing long-distance conveying is detected to have reached an entrance equipped with an RFID tag, reading the RFID tag to determine the section of the long-distance conveying route to which the inspection robot belongs, and calculating the distance between the inspection robot and the entrance; acquiring an image of the idler roller taken by a camera mounted on the inspection robot, and using an image recognition algorithm to identify the idler roller code; when a fault signal is received, concatenating the section of the long-distance conveying route to which the inspection robot belongs, the distance between the inspection robot and the entrance, and the idler roller code identification result to obtain the position of the inspection robot in the long-distance conveying, and generating an alarm message. This invention combines RFID and visual recognition to accurately locate the inspection robot's position, improving positioning accuracy and thus improving fault handling efficiency.

This application relates to the field of three-phase distribution network fault detection and location technology, and discloses a method, device, system, and storage medium for fault location in distribution systems. It addresses the problem of low accuracy in fault identification and location in existing solutions due to poor traceability of PMU measurement data and high computational costs. The method includes: acquiring power grid data collected by acquisition units located on the distribution network of the distribution system; fusing the three-phase π model and state estimation equations characterizing the distribution network branches to obtain equations corresponding to the distribution branches, and solving them to obtain theoretical values; using a threshold filtering method to remove data with numerical fluctuations exceeding preset conditions from the power grid data, and compensating the removed power grid data based on the data acquisition accuracy to obtain target power grid data; using the LNR algorithm to perform fault detection based on the target power grid data and theoretical values; and employing a multi-stage candidate branch location strategy to locate the fault when it is detected.

The invention discloses an intelligent automatic test system and a test method, and belongs to the technical field of software testing, the system comprises a hardware layer and six software modules, namely a demand analysis module, a large model processing module, a test execution module, a self-healing optimization module, a result analysis module and a knowledge base management module, which are deployed on the hardware layer. The method comprises the following steps: extracting structured data through a demand analysis module, and intelligently generating test assets by a large model core processing module; the test execution module adopts a fusion positioning technology to carry out multi-terminal automatic test; the self-healing optimization module monitors the interface change in real time and automatically corrects the script; the result analysis module identifies defects and generates a report; and the knowledge base module continuously iterates to provide support. According to the invention, full-process automatic closed loop from demand to report is realized, the problems of low efficiency, poor compatibility and high maintenance cost of the traditional test technology are solved, and the test intelligence level and the adaptive capability are obviously improved.

The invention discloses a power distribution network partial discharge fault positioning device and method, and relates to the technical field of power distribution network fault positioning, and the device comprises a data collection module, a multi-dimensional analysis module, an intelligent traceability module, a directional verification module, a report generation module and a local database. All the modules collaboratively integrate discharge pulses and load data of corresponding lines, through feature extraction, correlation analysis and historical data verification, a plurality of discharge sources are accurately distinguished, a fault branch is locked, then through space-time signal propagation path analysis and multi-algorithm collaborative optimization, a fault is accurately positioned to a specific equipment node in the power supply branch, and the fault is accurately positioned. And a structured report is output, so that the positioning accuracy and efficiency are greatly improved, and reliable support is provided for operation and maintenance of the power distribution network.

The invention belongs to the technical field of carry-scraper positioning, and discloses an underground unmanned carry-scraper global rapid positioning method based on FASTLIO improvement. The method comprises the following steps: acquiring a high-precision underground map, and performing parameter initialization on a FASTLIO algorithm; a sampling strategy is adaptively set, point cloud data and inertial data are collected in real time, and a FASTLIO algorithm is dynamically optimized; feature classification is carried out on the point cloud data, and differential configuration of feature weights is carried out on the point cloud data according to a classification result and the high-precision underground map; adopting a dynamically optimized FASTLIO algorithm to perform tight coupling optimization on the point cloud data and the inertial data after feature weight configuration to obtain initial positioning data, and performing dynamic correction to obtain final positioning data; the problems of drifting and error accumulation of a traditional positioning technology in a narrow closed tunnel can be effectively solved, and the positioning precision and stability of the unmanned carry-scraper in a complex underground environment are improved.

The embodiment of the invention discloses an indoor positioning method and system, a storage medium and a server, and is applied to the technical field of computer vision, three-dimensional reconstruction and indoor positioning. The method comprises the following steps: a server extracts a semantic landmark in a current view of a mobile terminal and semantic information for describing a relationship between the semantic landmark and the mobile terminal through a semantic understanding technology based on a received video stream sent by the mobile terminal; and the real-time feature vector obtained based on the semantic landmark and the relational semantic information is matched with the preset semantic landmark feature library, so that the current position of the mobile terminal can be quickly determined. In this way, the snapshot type positioning experience of scanning and knowing is achieved, the method does not depend on the initial position and the continuous movement track of the mobile terminal, and the complexity of indoor positioning is greatly reduced.

The present application relates to VR auxiliary debugging and bearing fault positioning technical field, specifically, the present application relates to VR auxiliary debugging and fault positioning method for equipment maintenance, aiming at solving the problem that traditional bearing fault detection adopts visual and static detection, and cannot collect full angle torque dynamic characteristics and large fault positioning error, in the bearing press fitting link, the dynamic torque sensor integrated with the angle encoder is used to collect the instantaneous torque of the full angle, the torque curve of the rotation angle is generated and is associated with the coding storage, when the fault occurs, the measured curve and the standard curve of the same type are called, and are bound to the double virtual bearing model of the VR scene, the virtual driving model is synchronously rotated, the signal module generates the resistance signal according to the torque to control the force feedback data glove, the real rotation feeling is restored by superimposing the viscous damping, the comparison module compares the resistance difference point by point and in the sliding window, if the threshold value is exceeded, the abnormal rotation angle interval is locked, the effective fault area is verified and confirmed through the original point, and the positioning result is output, and the fault positioning precision is improved.

The shapes and sizes of teeth are greatly different in different crowds, and in addition, the problems of crowding, missing, overlapping and the like also exist, so that the complexity of tooth positioning is increased. At present, tooth segmentation and positioning are mainly based on tooth X-ray films, and shooting of the X-ray films in remote areas with backward medical resources is limited. In order to solve the above problems, a deep convolutional neural network is planned to be used in the research, and teeth are positioned and classified based on intraoral images. The method comprises the following steps: firstly, preprocessing a collected data set to improve the capturing capability of important features; secondly, a mixed attention mechanism is introduced into the project, and important information in feature maps of different scales is accurately captured; and finally, the convergence and generalization ability of the model are improved through a residual module. The specific innovation points are as follows: 1, a mixed attention mechanism is introduced into a basic framework based on U-Net + + to dynamically adjust the weight of each feature map in the network; 2, the low-level features and the high-level features are connected by adopting skip connection, so that the problem of local information loss possibly caused by the low-level features and the high-level features can be solved;

This invention discloses an auxiliary detection system and method for fault location in hollow optical cables. By deploying moisture and dust detection devices in each splice box of the hollow optical cable and combining them with a splice box detection management platform, this invention achieves proactive monitoring and accurate fault diagnosis of environmentally sensitive factors in hollow optical cables. Specifically, addressing the pain point of hollow optical cables being highly sensitive to moisture and dust, and the difficulty of accurate fault location by traditional OTDRs, this invention utilizes real-time collected moisture and dust data, combined with signal reception power and historical detection data for comprehensive analysis. This effectively distinguishes abnormal environmental conditions within different splice boxes, thereby accurately identifying the specific location of the fault and solving the problem of traditional detection methods failing. Therefore, this invention provides an auxiliary judgment and location technology for faults in hollow optical cables caused by moisture and dust, improving maintenance efficiency and reducing hollow optical cable faults.

The application discloses a call quality difference root cause positioning method and system, computer equipment and a storage medium, and relates to the technical field of communication. The call quality difference root cause positioning method comprises the following steps: acquiring historical data of a quality difference analysis manual and quality difference cases. A quality difference knowledge graph is acquired according to the historical data of the quality difference analysis manual and the quality difference cases. A quality difference cause entity related to a first quality difference experience entity is acquired as a first quality difference cause entity according to the quality difference knowledge graph, so as to form a first quality difference cause entity set, and the first quality difference cause entity set comprises a plurality of first quality difference cause entities. Furthermore, the root cause of the first quality difference experience entity is determined in the first quality difference cause entity set according to the probability of each first quality difference cause entity in the first quality difference cause entity set. The combination of the knowledge graph and the Bayesian network realizes the probabilistic of the quality difference knowledge graph, and realizes the data and knowledge double-driven call quality difference root cause positioning technology.

This invention relates to the field of power line fault location technology, specifically to a method and system for power system line fault location. The method includes the following steps: S1, acquiring power frequency electrical quantity data collected by measuring devices at each node in the power system line; S2, calculating the data probability distribution divergence T between adjacent nodes based on the collected power frequency electrical quantity data, wherein the data probability distribution divergence is obtained by fusing the variance, standard deviation, and logarithmic operation of the electrical quantity data of the two nodes; S3, calculating the data probability distribution divergence difference between two adjacent monitoring intervals formed by three adjacent nodes; S4, introducing a flag function S to analyze the data probability distribution divergence difference and setting a location time threshold to determine whether a fault exists; S5, determining the specific location of the fault on the main line or branch line based on the value relationship of the flag function S; thereby improving the reliability and adaptability of power system fault location.

The invention relates to the technical field of AI positioning, and discloses a building industry AI positioning system, which comprises an AI task generation module, an AI positioning module, an AI positioning module and an AI positioning module, the worker capability vector construction module is used for constructing a multi-dimensional and updatable worker capability vector; the task intelligent recommendation and worker autonomous selection module is used for realizing a bidirectional collaborative task undertaking mode; the task receiving guarantee and dynamic activation module is used for constructing a multi-stage early warning mechanism based on retention duration; and the feedback optimization and system self-evolution module is used for constructing a closed-loop learning mechanism. According to the scheme, the problems of opaque dispatching, unfair distribution and the like in traditional construction management are solved, accurate digital positioning of personnel and construction tasks is realized, intelligent distribution and fair undertaking of the tasks are realized through AI task generation, worker capability vector matching and an autonomous selection mechanism, retention tasks are activated by adopting a hierarchical response strategy, and the construction efficiency is improved. Self-evolution is realized through closed-loop feedback, and intelligence, transparency and high efficiency of construction management are improved.

The invention discloses a power master station service-oriented fault positioning method and device, a medium and equipment, and belongs to the technical field of fault positioning. The method comprises the steps of obtaining multi-source data classified according to service topology levels; asynchronous decoupling is carried out on the data through a distributed message bus, and data cleaning and unified identification processing are carried out based on a power master station service rule and a service scene label system; inputting the processed data into a correlation analysis model trained based on a business dependency relationship and historical fault data, and carrying out cross-dimension correlation mining to identify a fault root cause; and in combination with a power master station exclusive network topology model and a graph computing technology, tracing a fault propagation path and deducing an influence range of the fault on the associated power business, and finally generating a fault positioning result containing a fault root cause, the propagation path, a fault influence score, a business influence range and a disposal priority. According to the invention, the problem that the fault of the power master station service cannot be accurately and efficiently positioned in the prior art is effectively solved.

This invention discloses a distributed intelligent fire location system based on the Internet of Things (IoT), relating to the field of fire location technology. It includes: sensing devices comprising multiple environmental information acquisition units installed on each floor of a building to collect environmental data, including smoke concentration and ambient temperature; a cloud platform connected to the sensing devices; the cloud platform is configured to: acquire environmental data fed back by the sensing devices; execute preset processes for estimating the fire source location and predicting the fire spread direction based on the environmental data, obtaining the estimated fire source location and the estimated fire spread direction respectively; and send the estimated fire source location and the estimated fire spread direction to pre-connected management personnel and designated third parties. This application has the effect of intelligently determining the core location and spread direction of a fire by analyzing data from multiple sensing devices, providing crucial information for rescue efforts.

This application relates to a method, system, storage medium, and smart terminal for detecting leaks in water supply pipelines, and pertains to the field of leak detection and location technology. The method includes: acquiring a training sample dataset; training a model on the training sample dataset to obtain model output results; calculating the sum of feature correlation weights; calculating the correlation weights of features in each group of sample data; calculating correlation information; acquiring selected sample data features; constructing a sample training set and a sample test set; and training and acquiring a leak detection model based on the sample training set. This application has the effect of improving the accuracy of detection by selecting only highly correlated features, reducing interference from other features, overcoming the interference and constraints of complex conditions on the leak detection method, and eliminating interference from other features.

This invention relates to the field of positioning technology, and provides an adaptive positioning method, system, and storage medium for smartwatches. The method includes: receiving a positioning request and simultaneously activating Wi-Fi scanning and GPS modules; scanning to obtain a list of BSSIDs of surrounding Wi-Fi hotspots; matching with a local BSSID location information database; if successful, directly outputting the corresponding location; if unsuccessful, obtaining network positioning and GPS positioning, comparing their accuracy, and outputting the optimal result, and associating the current BSSID list with the final positioning result in a local database. This invention, through simultaneous activation, priority matching in the local database, real-time accuracy optimization, and a self-learning update mechanism, achieves progressive optimization, including second-level positioning in familiar scenarios, high-precision output in unfamiliar scenarios, and increasing accuracy with use. This effectively solves the problems of slow positioning, unstable accuracy, and limited scenarios in existing smartwatches, and is particularly suitable for all-weather monitoring of elderly smartwatches, improving positioning efficiency and reliability.

The application discloses a production line fault positioning method and device and a readable storage medium, and relates to the technical field of production line monitoring. The production line fault positioning method comprises the following steps: acquiring a trained tree model, wherein the trained tree model is obtained by training sample production data of a target product to be positioned; determining first risk probabilities of each production station of the target product according to split node information of the trained tree model; acquiring prior risk probabilities of each production station in each production station, and correcting the prior risk probabilities to obtain posterior risk probabilities of each production station; determining second risk probabilities of each production station according to the first risk probabilities and the posterior risk probabilities; and generating corresponding risk station information and risk station information according to the first risk probabilities and the second risk probabilities. The application improves the applicability of the fault positioning technology for the production line.

This invention relates to the field of fault location technology, and discloses a method and system for rapid fault location in operation and maintenance. The method includes: acquiring operational data and denoising it to obtain a denoised data sequence; segmenting the sequence and identifying anomalies, determining the anomaly range through trend offset, and obtaining anomaly markers; if the waveform distortion metric of the anomaly marker exceeds a threshold, obtaining the anomaly location through time series analysis; extracting periodic sequences, grouping similar behaviors among devices to obtain associated device clusters; constructing a causal graph among devices, obtaining a list of potential anomalous devices through propagation path backtracking and node dependency sorting; assessing the impact degree of each device and identifying the faulty device; and obtaining the final fault location based on the topology information of the faulty device through cross-cluster association decomposition, causal edge weight adjustment, and graph structure simplification. This method can accurately and quickly locate the source of a fault in complex network environments with severe noise interference and tight device coupling.

The invention belongs to the technical field of power distribution network single-phase earth fault positioning, and particularly discloses a low-current grounding system single-phase earth fault section positioning method and system. The method comprises the steps of determining whether to start detection of single-phase earth fault section positioning or not based on abrupt changes of zero-sequence voltage and zero-sequence current at an outlet of a protected section; if the detection is started, the outlet of each section of the small current grounding system respectively calculates the transient zero sequence power of the outlet; determining an integral time window by using a zero-cross detection and continuity check mechanism, and integrating the transient zero-sequence power in the corresponding time window to obtain generalized transient zero-sequence energy; and judging whether the fault point is located at the upstream or downstream of the current measurement point based on the positive and negative generalized transient zero-sequence energy at the outlet of the protected section, and further judging whether the section between the two measurement points is a fault section. According to the method, the polarity difference of generalized transient zero-sequence energy of the fault section and the non-fault section is maximized, and the method is not influenced by transition resistance and line changes.

A computer-implemented system processes store data from multiple retail locations and content posts from store-based users to provide location-filtered retail content to user devices. The system may employ geolocation to determine user proximity to retail stores and multi¬ criteria filtering algorithms to content posts based on user preferences and real-time location data. Technical innovations include optimized database indexing for rapid location -based content retrieval, adaptive notification algorithms that identify users meeting proximity and preference criteria, and efficient content aggregation protocols that consolidate multiple store¬ based user posts into unified feeds. The system implements near-field communication and / or QR code scanning to trigger content display. Processing optimizations may include compressed transmission protocols and caching mechanisms that pre-load location-relevant content based on user movement patterns, resulting in improved response times and reduced bandwidth consumption for mobile retail content delivery.

The invention provides a self-adaptive repositioning method and system of a mobile robot, the robot and a medium, and relates to the technical field of repositioning. The method comprises the steps that after it is detected that positioning of the mobile robot fails, repositioning is carried out according to current multi-source sensor data; if the relocation fails, determining a relocation failure type according to the multi-source sensor data; and according to the relocation failure type and the relocation times, determining whether to continue relocation and parameters during relocation. According to the method provided by the invention, invalid retry can be avoided, so that the real-time performance is ensured, and the success rate of relocation is improved.

A smart irrigation system is disclosed, integrating advanced components to optimize water management. The system comprises a central controller interfacing with remote terminal units, environmental sensors, and a hybrid communication network supporting Thread, Bluetooth Mesh, Wi-Fi, and PLC protocols. Utilizing real-time and historical data, the controller dynamically adjusts irrigation schedules to conserve water and maximize efficiency. Localization technologies such as ToF, AoA, and RSSI provide precise zoning and component tracking. Energy efficiency is achieved through RTC-based scheduling, complemented by a battery management system that integrates solar panels and a water-driven generator for reliable, off-grid operation. The system incorporates AI-driven fault detection and blockchain encryption to enhance operational reliability and security. This comprehensive solution addresses energy consumption, precision irrigation, and secure communication for sustainable agricultural practices.

This invention discloses a method for 5G signaling traffic anomaly detection and fault location, belonging to the technical field of traffic anomaly detection and fault location. It includes step-by-step fault sample collection, time-series data acquisition and feature extraction, dynamic graph construction of endogenous context, dynamic association learning, graph-level representation generation and multi-head decision-making, and multi-stage pre-training and micro-processing. Compared with existing technologies, this invention has significant advantages in terms of real-time performance, sensitivity, accuracy, and intelligent analysis capabilities in 5G signaling traffic anomaly detection. Through innovative data processing methods, this invention fundamentally overcomes the inherent anomalies of existing technologies at the data source level. Through a unique model architecture and training strategy, this invention enhances intelligent analysis capabilities. It effectively overcomes the anomalies of low sensitivity, slow response, insufficient intelligence, and heavy reliance on expert experience in existing 5G signaling traffic anomaly detection technologies.