559 results about "Location systems" patented technology

A decentralized event detection and geolocation system is disclosed, utilizing a dynamically adaptable Spontaneously Emergent Geolocation Network (SEGNet) comprising mobile, stationary, and other devices equipped with multi-sensor capabilities. The system operates by obtaining sensor data from distributed devices, applying trained models to detect potential events of interest (EOIs), and dynamically forming device networks for collaborative geolocation and event validation. The system employs synchronization mechanisms and geolocation techniques, including Time Difference of Arrival (TDOA) and / or Angle of Arrival (AoA), to determine event locations through multimodal data fusion and iterative validation processes. The architecture supports multiple operational modes, including decentralized, centralized, and hybrid configurations, enabling operation in connectivity-limited environments and enhanced processing when server access is available. The system is designed to accommodate dynamic task delegation and real-time threshold adjustments based on environmental conditions, providing reliable event detection and geolocation across diverse scenarios.

A system for AI-supported leak detection and localization in water distribution infrastructures, consisting of: a large number of distributed sensor nodes mounted along a water pipe, each sensor node comprising the following: a pressure sensor configured to measure local hydraulic pressure fluctuations within the pipeline with a resolution of at least 0.01 bar; a flow sensor configured to measure the volume flow within the pipeline with an accuracy of at least ±0.5% of the measured value; an acoustic sensor configured to detect vibration signatures caused by leaks in a frequency range between 50 Hz and 20 kHz; an embedded microcontroller with integrated analog-to-digital conversion circuitry for digitizing sensor outputs; a wireless communication module configured to transmit time-synchronized sensor data to a cloud-based processing platform; and a local energy subsystem with a rechargeable battery and an optional circuit for generating photovoltaic energy; the cloud-based processing platform includes an artificial intelligence engine that comprises the following: a data acquisition module configured to receive and decode the transmitted sensor data and to perform time alignment; a supervised learning module that is trained on historical data of flagged leaks and non-leaks to classify incoming sensor patterns; an unsupervised learning module configured to detect anomalies by modeling normal operating baselines of the pipeline; and a topology-aware localization module configured to determine leak coordinates using the topology of the pipeline network, modeling the propagation of hydraulic waves, and estimating the arrival time difference from multi-node acoustic detections; and wherein the system is configured to provide real-time leak alerts and georeferenced visualization via a remote monitoring interface.

The invention relates to the technical field of power system automation, in particular to a real-time monitoring and fault positioning system for a vehicle-mounted mobile substation. The system comprises a signal acquisition and processing unit which monitors and acquires line parameters and environmental parameters of a transformer substation and traveling wave signals generated when a fault occurs in real time; the fault type identification unit calculates the confidence coefficient of each fault type based on the traveling wave signal so as to judge the fault type generated by the traveling wave signal, and marks the arrival time of the traveling wave head; an algorithm fusion positioning unit preliminarily positions a fault point according to the fault type and the arrival time of a traveling wave head, and then constructs a fitness function through a particle swarm optimization algorithm in combination with line topology and environmental parameters to correct a preliminary positioning error; according to the system, high-precision fault positioning and rapid isolation recovery are realized, the accuracy of fault section division in the complex power distribution network is ensured by modeling switch state and branch change, and misjudgment caused by topological change or equipment overload is effectively avoided.

The invention discloses an intelligent substation communication link fault accurate positioning method and system, and the method comprises the steps: obtaining a configuration file and equipment state data, carrying out the processing of the configuration file and the equipment state data, and generating a standardized link feature vector and a marking data set; constructing a hybrid deep learning model, and optimizing parameter configuration of the hybrid deep learning model by adopting an optimization algorithm to obtain a parameter-optimized hybrid deep learning model; training by using a real fault sample in combination with a virtual fault sample generated by a generative adversarial network, optimizing a time sequence prediction capability through an echo state network, and generating a fault positioning model; in combination with the link state data, outputting a fault link positioning result and confidence evaluation through multi-stage confidence evaluation and topological correlation analysis; and carrying out virtual-real corresponding verification in combination with the configuration file, carrying out parameter optimization on the fault positioning model, and outputting a fault positioning system. The problems that the fault positioning precision is low, the response speed is low, and complex fault scenes cannot be processed are solved.

The invention relates to the technical field of fault detection, in particular to a heating and ventilation system fault positioning system and method based on big data, and the system comprises a multi-source sensing module, a disturbance feature module, a path modeling module, a frequency spectrum matching module and a fault positioning module. In the method, a real-time disturbance sequence is constructed through time window segmentation and parameter offset calculation, separation of an active response chain and an abnormal propagation path is realized through a directional joint state vector and a topological relation table, and time asynchronism of multi-device signal transmission is eliminated by adopting a dynamic time warping algorithm. In combination with a real-time parameter bidirectional verification mechanism of a frequency domain main frequency band energy mark, a valve opening degree and a pump rotating speed, the problem of path confusion in a multi-node parameter coupling scene of a traditional method is solved, the tracing efficiency of concurrent faults in a complex pipe network system is improved, the adaptability limitation of a single-dimensional threshold mechanism to equipment performance degradation is overcome, and the method is suitable for a complex pipe network system. And the error positioning probability caused by signal delay superposition is reduced.

The invention provides a power line fault distance measurement system and method, and belongs to the technical field of power line detection. The system comprises monitoring terminals deployed at two ends of a line and a background processing system, and each monitoring terminal comprises a sensor module used for detecting a traveling wave current signal related to a power line fault in the line; the data acquisition module is used for extracting the arrival time of a traveling wave head according to the detected traveling wave current signal; the GPS time synchronization module is used for adjusting the local clock of the data acquisition module, reducing the time synchronization error of the two monitoring terminals and correcting the arrival time of the traveling wave head; and the background processing system is used for calculating a traveling wave time difference and a junction wave velocity normalization processing result according to the corrected arrival time at the two ends of the line, and determining a fault position coordinate and a fault type. According to the invention, collaborative optimization of fault positioning precision and type identification in a hybrid power line environment is realized.

The invention discloses a server link fault positioning system and method, electronic equipment and a storage medium, and relates to the technical field of server link tests.Physical layer data and protocol layer data of a data collection point are collected through a collection assembly, a test assembly is controlled to conduct server link testing, the test assembly comprises a control module and an analysis module, and the control module is connected with the analysis module. The test instruction is issued to the server link through the control module, when the server link fault is monitored, the analysis module acquires the physical layer data and the protocol layer data of each data acquisition point from the acquisition assembly, and determines the fault position and / or the fault type of the server link according to the acquired data, so that the automatic link quality evaluation is realized, and the efficiency is improved. And the fault position and the fault type can be determined, so that the problems of difficulty in accurately positioning the fault position and distinguishing the hardware link fault and the software error through a single pressure test and low troubleshooting efficiency caused by manual fault positioning in the prior art are solved, and the technical effect of improving the troubleshooting efficiency is achieved.

Apparatus, systems, and methods for mapping utility lines in utility potholing operations are disclosed. Pothole mapping apparatuses, systems, and methods may be employed in utility locator devices and utility locating systems to map potholed utility lines. Data generated via pothole mapping may be used to calibrate utility depth measurements in utility locator devices and systems. Further, information revealed about utility lines during potholing procedures may be used to train neural networks and utilize artificial intelligence in generating predictions regarding the positions and characteristics of utility lines.

The invention relates to the technical field of power grid fault positioning, in particular to a rapid power grid fault positioning system based on digital twinning and AI, which obtains multi-dimensional operation data of each node of a power distribution network, constructs a structured data set, reflects the state of the system, and performs joint modeling on node features and a topological structure through a graph neural network. And reasoning to generate candidate fault nodes. And further constructing a digital twinborn model containing load flow calculation and disturbance injection, performing analogue simulation on candidate nodes, extracting an electrical quantity change rate, performing fuzzy similarity matching with operation data in a fault window, and accurately positioning a fault node. Through cooperation of three stages of prediction, simulation and matching, the problems of weak complex topology perception, poor perturbation identification, positioning offset and the like of the existing method are effectively solved, and the fault positioning precision and robustness are improved.

The invention discloses a communication equipment fault intelligent diagnosis method and device, equipment and a medium. The method comprises the steps of collecting equipment operation logs in real time, and extracting an abnormal point set; clustering the abnormal points, and matching a hardware fault, a software error and a network congestion type in combination with a preset mode library; dimensionality reduction is carried out on temperature, voltage and current sensor data based on principal component analysis, and a time-synchronized fusion feature vector is constructed; analyzing features and abnormal modes, and outputting potential fault points; associating the classification model to generate a fault priority by extracting the dynamic characteristics of the network flow; and a dependency network is constructed in combination with Bayesian reasoning, so that accurate fault positioning is realized. The system supports incremental learning, updates an abnormal mode library and automatically expands a knowledge base. Through multi-dimensional data fusion and spatio-temporal feature joint modeling, the problems that a traditional method depends on manual rules and is high in false alarm rate are solved, and the method is suitable for complex scenes such as a 5G base station and a data center.

The invention discloses a power grid fault positioning system and method based on traveling wave distance measurement, relates to the technical field of fault analysis, and solves the technical problems that traveling wave feature analysis, temperature compensation and high-precision synchronization technologies are not effectively integrated, and rapid and accurate fault positioning of a smart power grid is difficult to meet. Through the technical combination of dynamic temperature compensation, high-precision time synchronization and intelligent fault classification, the bottlenecks of traditional traveling wave distance measurement in the aspects of precision, reliability and intelligence are systematically solved, temperature sensors are deployed at key nodes of a cable, the temperature is monitored in real time, the wave speed is dynamically corrected through a formula, the overall error is reduced, and the fault location accuracy is improved. Meanwhile, an optical fiber two-way time transmission method is combined, transmission delay errors are reduced, synchronization reliability is improved, finally, a mapping library is constructed through laboratory simulation and field data, a Euclidean distance matching algorithm is combined, fault reasons are automatically recognized, and rapid positioning of the faults and accurate recognition of the fault reasons are achieved.

The invention relates to a distributed fault positioning system and method for a power transmission and distribution line, and the system comprises the power transmission and distribution line, an acquisition unit group, a collection unit, a communication base station, a cloud server, and a data terminal. The acquisition unit group is used for monitoring current, self state parameters and the like of the power transmission and distribution line, the collection unit is used for receiving and sending communication data with the acquisition unit group, the communication base station is used for receiving and sending communication data with the collection unit, and the cloud server is used for communicating with the communication base station and the data terminal. And the data terminal is equipment with a communication function at the user side. According to the scheme, the application range of a line fault positioning system is expanded, including mountainous areas without mobile communication network coverage, a mode of collecting and installing equipment distributed calculation is adopted, the accuracy and efficiency of fault positioning are improved, the line patrol time is saved, the time of line power restoration is shortened, and the reliability of a power supply system is effectively ensured.

The invention provides a full-autonomous cell operation system based on body intelligence, and relates to the field of cell operation, the system comprises a system hardware architecture and a system software architecture; the system hardware architecture comprises a micromanipulation execution system, a precision positioning system, a multi-mode sensing system and an intelligent calculation and control center. The micromanipulation execution system is used for cell environment interaction, the precision positioning system is used for sample bearing and environment control, the multi-modal sensing system is used for providing key information, and the intelligent calculation and control center is used for operation decision making; the system software architecture comprises a sensing layer, a planning layer, an execution layer and an interaction layer. According to the application, cell recognition, tool selection, path planning, operation execution and result feedback can be automatically completed without manual intervention; through tool autonomous switching and strategy dynamic adjustment, various operations such as cell clamping, injection, controllable deformation and micro-assembly can be completed, and the problems that traditional cell operation depends on manual work, efficiency is low, and consistency is poor are solved.

The invention discloses a power distribution network line fault positioning system based on multi-source information fusion, which relates to the technical field of power system operation and maintenance and comprises a data acquisition module, a data preprocessing module, an electric network topology management module, a fault prediction module, a fault judgment module and a man-machine interaction and alarm module. The method comprises the following steps: acquiring running state information from a power distribution network in real time, generating a structured multi-dimensional information database according to the running state information acquired by a data acquisition module, and performing time alignment, format standardization and feature vector construction on the acquired running state information to generate the structured multi-dimensional information database; according to the method, a fault section is preliminarily judged according to fault features, a fault state prediction model is constructed, a multi-dimensional information database is used for estimating state variables of the model, and the method aims at overcoming the defects that in the prior art, fault positioning fuzziness and reliability are insufficient due to the fact that a single information source is relied on.

The invention discloses a power distribution network fault positioning method and positioning system, and relates to the technical field of power distribution network fault positioning, and the method comprises the steps: collecting multiple groups of historical data of different faults of a power distribution network, obtaining the missing intervals of voltage and current sequences in each group of historical data, and positioning the missing intervals to the front, middle and back of the whole sequence; different interpolation methods of different missing intervals are obtained by combining the length of the missing interval, the distance from the starting point position of the missing interval to the previous nearest missing interval and the distance from the ending point position of the missing interval to the next nearest missing interval, an abnormal value is marked for a sequence after interpolation is completed, and the sequence is equally divided into S < front > and S < back >; the abnormal values are repaired by utilizing ELM, a standard data set belonging to the fault is obtained, clustering processing is carried out on data in the standard data set, irrelevant clusters are removed, and a specific position is positioned according to the similarity between the fault and each group of faults in the target cluster. The power distribution network fault positioning method effectively improves the power distribution network fault positioning precision.

Systems and methods include a medical device that scans for wireless broadcasts based upon received input or satisfying a scanning criterion. The medical device, based upon the scan, identifies data wirelessly broadcast from a control device. The medical device outputs information to the interface identifying the control device. The medical device receives input from the interface selecting the control device. The medical device receives a command from the control device. The medical device physically interacts with a user based upon the command received from the control device. The medical device sends wireless confirmation of pairing to the control device. The medical device subsequently sends wireless confirmation of unpairing to the control device. The medical device performs a scan for wireless broadcasts in response to the unpairing, based upon received input or satisfying the scanning criterion.

The invention belongs to the technical field of packaging jet printing, and discloses an external packaging carton two-dimensional code jet printing quality online monitoring and error correction process, which comprises the following steps: building a vision, laser, spectrum and pressure four-source sensing positioning system in a preprocessing stage, comprehensively collecting carton material and form related data, and forming a pre-calibration closed loop in cooperation with microsample jet printing verification; in the jet printing process, a high-speed imaging system of self-adaptive light supplement works synchronously, after an image is preprocessed through a combinatorial algorithm, various defects such as blooming and scratches are accurately recognized through a ResNet34-Transform-GAN fusion model, and then an LSTM neural network is used for predicting the development trend of the defects and conducting early warning; a three-level parameter configuration system of cloud decision, edge execution and twin simulation is utilized, an edge calculation unit uploads data such as materials, sizes and flatness collected in real time to the cloud, historical optimal parameters of the corresponding materials are called, and then dynamic adjustment is conducted in combination with the conveying speed.

The invention, which relates to the technical field of the wireless communication network, discloses an AI-based fault route rapid positioning system comprising: a whole network flow topology data synchronous acquisition module used for obtaining synchronized original data from network elements in the wireless communication network; the disturbance characteristic time sequence extraction module is used for generating a characteristic time sequence based on the synchronized original data; the flow topology coupling effect quantification module is used for combining the characteristic time sequence with the network topology index data to generate a real-time fault fingerprint sequence; and the fault source reverse reasoning module is used for acquiring a preset fault fingerprint database, calculating the fingerprint difference degree and judging the prototype fingerprint with the minimum difference degree so as to generate a fault positioning report. According to the method, the fault source can be globally and accurately positioned, the soft fault can be sensitively detected, the positioning precision and robustness are improved by fusing multi-dimensional information, and adaptive parameter optimization and learning expansion can be realized.

The invention discloses a low-cost transportable system for UUV path planning and control experiments. The low-cost transportable system comprises a shore-based unit, a buoy unit, an underwater vehicle unit, a zero-buoyancy cable and a software stack, the UWB tag, the router, the GNSS and the rocker receiver are integrated in the buoy, a sealing waterproof design is adopted, and the buoy can stably float on the water surface and is in wired connection with the underwater vehicle through the zero-buoyancy cable; the three-dimensional position of the underwater vehicle is obtained, the upper computer and the UWB base station are deployed on a shore base, the upper computer interacts the calculated position with the router in the buoy through wireless communication, and a stable and efficient communication link is constructed. The system can be quickly arranged in indoor and outdoor environments, supports closed-loop path planning and control experiments, can effectively replace expensive USBL or indoor dynamic capturing and positioning systems, remarkably reduces experiment cost, and improves experiment flexibility and portability.

The invention discloses a power distribution network high-resistance fault positioning method and positioning system based on multistage joint filtering, and the method comprises the steps: collecting the power data of a power distribution network in real time, including a zero-sequence voltage signal and a zero-sequence current signal; constructing a signal flow graph strategy to process the power data by using a multi-stage joint filtering technology, and generating output data; the extraction of fault features is completed while the signal descrambling is carried out; establishing a dynamic threshold value, and performing comparative analysis based on the output data and the dynamic threshold value to determine a fault occurrence moment; based on a fault occurrence moment, generating a fault measure by using a heuristic method and feature polarity accumulation; based on two-dimensional characteristics of fault measurement amplitude and polarity and according to distribution characteristics of fault measurement of each measurement point relative to a fault point, a fault section is positioned through a recursion positioning algorithm containing an adaptive threshold value, a fault feeder line is quickly positioned, recursion positioning is carried out by using the adaptive threshold value, abnormal values caused by interference are eliminated, and the fault feeder line is quickly positioned. Therefore, accurate positioning under complex working conditions is realized.

The disclosure includes vehicle-mounting devices to mount one or more utility locator devices to a vehicle for use in locating and mapping buried utility lines. Such vehicle-mounting devices may improve over other vehicle-mounting devices known in the art by preventing damage to associated utility locator devices as well as the vehicle mounting device. Further, such devices may be included in vehicle-based locate systems as well as in a computer implemented method for utility line positions and characteristics using Artificial Intelligence (AI).

Provided are a system and method for coordinating dual wireless communications protocols when implementing a time difference of arrival (TDOA) framework for ranging between nodes. A first of the protocols (e.g., BLE) can be used for transmission of synchronization and TDOA schedules that prescribe synchronization and TDOA frames. The synchronization and TDOA frames can then be executed according to a second of the protocols (e.g., UWB), thus exemplifying an efficiency in energy consumption owing to an absence of transitioning between the first and second protocols transmissions throughout the schedules.

The invention discloses a power distribution line passive real-time fault positioning system, which belongs to the technical field of power distribution line fault detection and comprises a power distribution line fault positioning device management system and a plurality of fault positioning terminals distributed along a power distribution line. The distribution line fault positioning device management system establishes two-way communication with each fault positioning terminal through a 4G / 5G wireless public network; the distribution line fault positioning device management system comprises a data center, a client and a plurality of mobile terminals. The fault positioning terminal comprises an ARM processor, a time synchronization unit, a signal acquisition unit, a signal processing unit, a passive self-powered unit, a communication unit and an auxiliary unit. According to the invention, the distributed fault positioning terminal is combined with an intelligent algorithm, so that high-precision fault recognition and real-time positioning under a complex network are realized, and the fault handling efficiency of the power distribution network is remarkably improved.

The invention relates to a server fault positioning system and method, and the system comprises a debugging card and a mainboard, and the debugging card is electrically connected with the mainboard. The debugging card is used for acquiring a power-on self-test code of the mainboard and matching the power-on self-test code with a pre-stored fault code library; determining a fault code corresponding to the power-on self-test code, and determining a fault module corresponding to the fault code in the target server; the mainboard is used for calling and starting BIOS debugging firmware stored in the debugging card, entering a debugging mode and obtaining enumeration information of a fault module; the debugging card is also used for analyzing the enumeration information and determining a state code corresponding to each unit included in the fault module; respectively matching each state code with a pre-stored state code library; and determining a fault state code which cannot be matched with the correct state code in the state code library, and determining a fault unit corresponding to the fault state code. Through the method and the device, the problem of relatively low fault positioning efficiency of the server in related technologies is solved.

The invention relates to the technical field of power grid information system fault positioning, and particularly discloses a power grid information system fault positioning system based on adaptive learning, and the system comprises a data collection module which is used for collecting electrical quantity data and state quantity data in the operation process of a power grid; the data preprocessing module is connected with the data acquisition module and is used for carrying out preprocessing operations such as filtering, denoising and normalization on the acquired data and removing interference and invalid information in the data; and the fault feature extraction module is connected with the data preprocessing module and is used for extracting feature parameters related to the power grid fault based on the preprocessed data. According to the power grid information system fault positioning system based on adaptive learning, a dynamic multi-scale adaptive learning algorithm is fused with reinforcement learning and transfer learning mechanisms, model parameters and structures are dynamically adjusted according to the real-time operation state of a power grid, similar scene experience is migrated, and the fault positioning accuracy and adaptability are remarkably improved.

A package storage device with a monitoring and security system that utilizes motion and sensors to provide secure package delivery and validation. Also having the ability to automate the delivery process with secure communications and encrypted codes to create a hands-free delivery system. This storage device has the capability of capturing photos and metadata to enhance security and forensics. It can be connected to a cloud-based system that enables ease of interface and security connectivity in a mesh format.

The embodiment of the invention discloses a visual fine adjustment method and device of an interface, a storage medium and a terminal. Firstly, a source code and a running state preview interface are synchronously obtained, and it is ensured that operation is based on a real rendering state. Then, when the user edits the interface elements, the system accurately positions the visual elements to the corresponding positions in the source codes during operation through a pre-established bidirectional mapping mechanism. Based on the accurate positioning, the system generates a code modification instruction and updates the target code. And finally, generating a new preview by running the updated code in real time, completing an operation feedback closed loop, and realizing a real-time editing preview effect. According to the method, manual modification of complex codes is avoided through the complete process, the modification precision is ensured while the low operation threshold is kept through intuitive visual operation, and the operation simplicity and control precision are effectively balanced.

The invention provides a cable testing method and a small handheld cable tester. The method comprises the following steps: carrying out wavelet transform noise reduction, Z-score standardization and time sequence dynamic regularization on original cable data; then constructing a geometric deep learning network by using a dispersed self-organizing structure of the rotating cube set, and extracting multi-modal depth features; fusing different modal features through a spiking neural network gating mechanism and a cross-modal attention mechanism; and finally, fault classification is carried out based on a differential evolution optimized neural network, and fault location is realized by combining a time sequence generative adversarial network and a dynamic probability neighborhood growth clustering algorithm. The system also evaluates the data contribution degree of each modal through information entropy and mutual information analysis, and optimizes the model performance by using adaptive weight distribution and lightweight neural network technologies. According to the invention, various fault types such as cable breakage, short circuit, insulation aging, poor contact and the like can be identified and positioned with high precision, and the efficiency and the accuracy of cable maintenance are remarkably improved.

Techniques described herein utilize a system comprised of a cloud-based communication platform server (CPS), a plurality of fixed location wireless beacons within a geofenced area, and a fleet of user equipments (UEs). Each UE is capable of wireless communication with the CPS over one or more of a plurality of wireless RF networks. Additionally, each UE may also be configured to receive RF transmissions directly from the plurality of fixed location wireless beacons. The system may implement a method for determining areas of poor wireless connectivity within the geofenced area. The method may comprise determining whether a UE has an active connection with the CPS via at least one of the plurality of wireless RF networks. When the UE does not have an active connection with the CPS via any of the wireless RF networks, it may self-determine its location within the geofenced area and store its self-determined location. The UE may repeat the location self-determining and location storing steps on a periodic basis until the UE has re-established an active connection with the CPS. Once the UE has re-connected to the CPS, it may then upload the set of stored self-determined location data to the CPS that was acquired while the UE was disconnected from the CPS.

This application discloses a communication method for a UWB and a related product. This application can be applied to a UWB-based wireless personal area network system, a sensing system, a positioning system, a ranging system, or a communication system, and can be further applied to a wireless local area network system that supports 802.11 series protocols such as a next-generation Wi-Fi protocol of IEEE 802.11ax, for example, 802.11be or Wi-Fi 7, and a next-generation protocol of 802.11be, for example, Wi-Fi 8. The method includes: generating a first message including a first bitmap, where an ith bit in the first bitmap corresponds to an ith UWB device, and when the ith bit is set to a specified value, the ith bit indicates a location of parameter configuration information of the ith UWB device in a first DPL; and sending the first message.