3848 results about "Distance measurement" patented technology

The invention discloses a distributed power supply access-oriented power distribution network fault distance measurement method and system, and relates to the technical field of power systems, and the method comprises the steps: collecting the electrical parameters and operation states of distributed power supply access nodes in a power distribution network in real time, building a dynamic manifold model based on an ecological niche theory, and carrying out the calculation of the dynamic manifold model; adaptively adjusting manifold learning neighborhood parameters according to power fluctuation data included in the electrical parameters, and updating node ecological niches to reconstruct a dynamic manifold model; based on the reconstructed dynamic manifold model, fault features are extracted from three scales of a current harmonic component, a feed line inter-harmonic propagation path and whole network voltage influence, and a three-dimensional feature vector is generated through fusion of a graph correlation algorithm; based on the expanded fault sample library and the power fluctuation data, constructing a fault transfer relation model to predict a ground fault and a short circuit risk area; a fault source is modeled by adopting a topological neural network, and a fault point distance measurement value is output through state prediction and strategy deduction.

The invention provides a distribution line fault location optimization method based on single-ended traveling wave location, and relates to the technical field of traveling wave detection. The method comprises the following steps: carrying out segmented modeling on a line, calculating the traveling wave propagation speed and wave impedance of each segment, and correcting the traveling wave propagation speed and wave impedance; collecting a voltage / current traveling wave signal of a detection point, and extracting a line mode component; performing wavelet transformation on the line mode component, detecting the wave head position of the initial traveling wave through a modulus maximum search algorithm, and recording the arrival time of the initial traveling wave, a corresponding first energy value and polarity; calculating a reflected wave time window based on segmented modeling parameters, screening reversed polarity waves with qualified energy attenuation, and calculating a fault distance; if no effective reflected wave is detected in the reflected wave time window, triggering a pseudo double-end mode; a result is verified through quadruple constraints; the problems of poor parameter adaptability, low signal processing precision, strong reflected wave dependence and incomplete verification in traveling wave distance measurement of a complex distribution line are solved, and the accuracy and reliability of fault distance measurement are improved.

The invention relates to an autonomous navigation method for lunar satellite formation and a second-order filtering navigation architecture, and the autonomous navigation method comprises the steps: obtaining orbit prediction information based on a kinetic model of the lunar satellite formation, and obtaining collaborative theory observation information based on a collaborative observation model, carrying out fusion processing on orbit prediction information, collaborative theory observation information and multi-source observation data of in-orbit observation by using an extended Kalman filtering algorithm, and estimating an absolute orbit state of the lunar satellite formation; establishing a relative motion model of the slave satellite under the local coordinate system of the master satellite, and establishing a relative measurement model; and taking the absolute orbit state of the master satellite as a reference datum, obtaining a preliminary prediction relative orbit state based on the relative motion model of the slave satellite, and obtaining relative measurement data including distance measurement and angle measurement based on the relative measurement model, and fusing the relative measurement data and the preliminarily predicted relative orbit state through an extended Kalman filtering algorithm to estimate the relative orbit state of the slave satellite. Navigation may be independent of ground support.

The invention relates to the technical field of nuclear fusion devices, and discloses a nuclear fusion device and a monitoring system and an installation method thereof, the monitoring system comprises a cold shield main body, the cold shield main body is of an annular rotation structure, and the cold shield main body is arranged in a cavity and wraps the circumferential outer side of a vacuum chamber; the cold shield main body comprises a plurality of groups of fan-shaped cold shield sections which are sequentially arranged in the circumferential direction, and the plurality of groups of fan-shaped cold shield sections are encircled to form the cold shield main body; the distance measuring assembly is arranged on the cold shield main body, the distance measuring assembly comprises a plurality of groups of distance measuring sensors which are arranged in the circumferential direction of the cold shield main body at intervals, and each group of distance measuring sensors comprises a plurality of distance measuring sensors; the distance measuring sensor is used for detecting the size of a gap between the cold shield body and the longitudinal field coil and the size of a gap between the cold shield body and the vacuum chamber. Therefore, the cold shield main body can be assisted to be assembled at a position in the nuclear fusion device, and the matching position of the cold shield main body, the vacuum chamber and the longitudinal field coil can be monitored in real time.

The invention discloses a mechanical arm welding detection intelligent diagnosis method and system based on laser ultrasonic guided waves. According to the system, a high-precision multi-degree-of-freedom steering engine, an infrared distance measurement array, a temperature sensor, a laser vibration exciter and a laser vibration meter are integrated at the tail end of a mechanical arm, synchronous operation of welding and online detection is achieved by presetting a welding track, and the system collects an excitation signal, a reflection ultrasonic signal and temperature data through a high-speed data collection card; and the signal is preprocessed through a temperature matching model, phase compensation and baseline correction. Then, wavelet decomposition is adopted to extract time-frequency features, intelligent diagnosis is achieved through a pre-trained one-dimensional convolutional neural network, a dynamic threshold value is set based on the 3 sigma criterion, and recheck feedback is automatically triggered when detection data exceed the limit, the welding detection efficiency and precision are remarkably improved through the scheme, data closed-loop management and intelligent quality tracing are achieved, and the reliability of welding detection is improved. And the automatic production requirement of modern steel structure manufacturing is met.

The present disclosure relates to the technical field of smart power grids. Disclosed are a method and apparatus for constructing a high-order tensor network of a large-scale power grid, and a device and a medium. The method comprises: acquiring multiple category attribute sets of heterogeneous nodes in a large-scale power grid; performing feature extraction on the multiple category attribute sets, so as to obtain attribute features of the heterogeneous nodes; on the basis of the attribute features of the heterogeneous nodes, using a deep hash mapping model to establish multiple feature sub-spaces; using a breadth learning strategy to align the multiple feature sub-spaces to a unified feature dimension; on the basis of an attribute feature vector of the unified feature dimension, using a distance measurement method to calculate a distance measurement value between the heterogeneous nodes; on the basis of the attribute feature vector of the unified feature dimension and the weight of a heterogeneous node interaction relationship, determining a basis tensor for representing the heterogeneous node interaction relationship; and on the basis of the basis tensor and the weight of the heterogeneous node interaction relationship, using a tensor multiplication operation rule to construct a high-order tensor network of a large-scale power grid.

The invention provides a road marking quality intelligent evaluation system based on image analysis, and relates to the technical field of road facility monitoring, and the system comprises a detection unit, a marking quality evaluation unit, a marking wear prediction unit, a GPS positioning unit, a vehicle driving information unit, a control unit and a remote central control unit. The marking quality evaluation unit is constructed based on a differential geometry theory and comprises a curvature flow edge detection module, a marking geometric characteristic manifold representation module and a multi-scale differential invariant evaluation module, the system regards a marking as a two-dimensional manifold, and the marking quality is evaluated by calculating differential geometric quantities such as a Gaussian curvature, an average curvature and a shape index. And constructing geodesic distance measurement on the feature manifold, and evaluating the completeness, visibility and reflective performance of the marked line. And the marking wear prediction unit predicts the service life of the marking based on the traffic flow information and the environment characteristic mapping relation model, and generates a maintenance suggestion.

The invention relates to the field of government affair work order intelligent processing, in particular to a government affair work order intelligent processing method and system based on space-time semantic clustering and a large language model. According to the scheme, unified data feature modeling is conducted on a work order to be processed, an improved DBSCAN clustering algorithm is executed on the work order through a weighted space-time semantic three-dimensional distance measurement formula, and combined clustering of space, time and semantic features is achieved; calculating priority scores of the work orders, and dynamically allocating scheduling resources according to the clustering scale and the priority of the work orders; based on a retrieval enhancement generation technology of an RAG framework and an FAISS vector retrieval library, historical similar work orders are matched, a few-sample learning case is generated, and two sets of differential treatment schemes are generated by controlling temperature parameters of a large language model; visual display and interactive analysis of work order clustering are realized through an interactive GIS platform; and establishing a quality feedback closed loop of work order reconstruction. The method is suitable for intelligent government affair work order processing.

The invention discloses a high-precision flow online monitoring device and method for a siltation section, and belongs to the technical field of hydrological monitoring. The device comprises a sensing terminal, an edge terminal and a mounting mechanism, the sensing terminal is integrated with an upper and lower section layered speed measurement module, an underwater distance measurement module, a first absolute pressure type water level measurement module and an attitude and temperature sensor, and vertical section flow velocity data is obtained by receiving water body reflection signals in a time-sharing manner; and the dynamic deposition section area is corrected in real time in combination with ultrasonic ranging. And the edge terminal compensates water level measurement data by using atmospheric pressure, and calculates the flow through fusion of a telemetering module. The installation mechanism supports fixed or telescopic installation, and the height of the installation mechanism is automatically adjusted according to the distance between a deposition layer and equipment. The method comprises the steps of dynamically correcting the section, calculating the flow through layered integration and compensating errors of multiple sensors, the problems of large area deviation, high operation and maintenance cost and the like caused by sedimentation in a traditional flow measurement technology are solved, and high-precision online monitoring under the high-sand-content complex flow state is achieved.

The invention discloses a sports video commentary generation method and system based on a multi-modal large language model, and the method comprises the steps: obtaining a multi-modal data set which comprises a sports video, and an audio and a commentary text corresponding to the sports video; constructing a multi-modal large language model, encoding the sports video, the audio and the explanation text so as to project corresponding video frames, audio waveforms and metadata to a shared embedding space, and determining a multi-modal embedding vector; a multi-modal clustering memory unit is set, multi-modal embedded vectors are grouped, and feature alignment between modals is optimized through comparative learning and information entropy regularization; based on a retrieval enhanced context learning mechanism, a historical instance is retrieved through sparse regularization distance measurement to serve as reference input of a current input multi-mode embedded vector; and jointly inputting the current multi-modal embedded vector and the reference input into the multi-modal large language model to obtain a sports video commentary. According to the method and the device, the problems of insufficient multi-modal information integration and insufficient context utilization are solved.

The invention relates to the technical field of goods shelf detection, in particular to a self-detection method and device for goods shelf settlement, and provides the following scheme: obtaining a top view image through an image sensor arranged right above the top of a goods shelf, dividing the image into a plurality of grid units, and positioning a rectangular geometric shape by utilizing Hough transform; and screening a plurality of to-be-detected areas in combination with the edge features. For an area to be measured, homographic registration and ortho-rectification are carried out based on a reference image, a displacement field is obtained by adopting sub-pixel-level dense registration, and a geometric parallax component field corresponding to imaging parameters is obtained through robust estimation. And under the hypothesis of small deformation, inverting the parallax into a pixel normal distance, and carrying out weighted aggregation on the local region to obtain a local distance measurement result. And by iteratively combining adjacent grids, determining a settlement area boundary, and finally outputting a settlement detection result. Millimeter-level settlement quantification can be realized under a single-frame image, hardware transformation is avoided, and the method is suitable for automatic detection and long-term monitoring of multi-specification goods shelves.

The invention discloses a high-voltage cable operation state on-line monitoring, intelligent early warning and fault positioning system, particularly relates to the technical field of power equipment insulation monitoring, and is used for solving the problems that transient discharge signals generated in the cable insulation degradation process are difficult to effectively capture and accurate fault positioning cannot be realized in the prior art. The method comprises the following steps: collecting transient leakage current signals and traveling wave propagation characteristic parameters, performing phase correlation analysis on leakage current pulses and power frequency voltage to identify discharge types, and performing variational mode decomposition and Hilbert-Huang transform on the signals to respectively extract complexity characteristics and energy distribution characteristics; signal logic conflicts are judged by analyzing similarity and statistical distance among characteristics of a plurality of monitoring points, and collaborative diagnosis is started or traveling wave distance measurement is directly utilized to carry out insulation state evaluation and fault location. And finally, differential early warning levels are generated according to the diagnosis result, and fault line selection and positioning information is output to realize real-time monitoring, intelligent early warning and accurate positioning of the operation state of the high-voltage cable.

The invention discloses a laser radar test method based on a long-distance target distance measurement result, and the method comprises the following steps: obtaining a laser radar echo signal, and extracting the frequency spectrum information of the echo signal; doppler frequency shift characteristic parameters are extracted according to the frequency spectrum information, and the relative speed of the target is calculated based on a preset frequency shift calculation model; acquiring multi-source sensor data associated with the laser radar test platform, and fusing to construct a dynamic ranging reference coordinate system; performing dynamic motion compensation on a laser ranging result according to the relative speed of the target to obtain a target initial measurement distance after Doppler correction; mapping the target initial measurement distance after Doppler correction to the dynamic distance measurement reference coordinate system to obtain a remote target final distance measurement result aligned with a test platform coordinate system; and outputting the accurate position and moving state information of the target in the three-dimensional space according to the final distance measurement result. According to the invention, the ranging precision and stability can be improved.

The invention belongs to the technical field of action recognition, and discloses a small sample human body action recognition method based on a cross attention mechanism. An end-to-end small sample action recognition model is provided, the end-to-end small sample action recognition model is based on a prototype network, on a feature extraction-prototype construction-distance measurement framework of the model, a spatial-temporal feature extraction network is adopted for feature extraction, a prototype-like construction module is adopted for prototype construction, and an end-to-end small sample action recognition model is obtained. And adopting a classification and prediction module for the measurement distance. According to the method, the skeleton position image is introduced to effectively reduce the interference of irrelevant factors such as illumination and view angle change, and the robustness of the model to human body action recognition is enhanced; through the adaptive spatio-temporal feature fusion method, the model can accurately capture fine-grained features, so that the accuracy of action recognition is improved. The design of the multi-branch feature classification loss function optimizes the feature extraction and coding capability, so that the model has better performance in a small sample learning scene.

The invention relates to the technical field of automatic driving, and discloses a parking assisting method and system for automatic driving. The method comprises the following steps: cascading and splicing a first fisheye image acquired by a main camera in a vehicle body and a second fisheye image acquired by a slave camera to obtain a panoramic image; performing parking space boundary identification and obstacle analysis on the panoramic image to obtain parking space boundary information and obstacle position information, and synchronously performing distance calculation on a radar echo signal of an ultrasonic sensor to obtain distance measurement data; and a parking environment map is created according to the parking space boundary information, the obstacle position information and the distance measurement data, path planning is carried out based on the parking environment map, a parking execution instruction is obtained, and the parking execution instruction is used for vehicle parking auxiliary control. According to the method, the view coverage range and the flexibility of the observation angle are expanded, and the execution precision and safety of parking auxiliary control are improved.

Tracked distance measuring device, systems, and methods for determining and mapping point of interest for use in utility locating operations and other mapping applications are disclosed. A tracked distance measuring device embodiment includes simultaneously triggered rangefinder and positioning elements to measure a distance and determine location and pose, optionally in conjunction with a utility locator.

The invention discloses an optical time stretching sweep frequency interference measurement Doppler effect compensation method and device, and relates to the technical field of non-cooperative target absolute distance measurement. In order to solve the defect that the absolute distance measurement precision is reduced due to the fact that the Doppler effect cannot be efficiently suppressed in a complex environment in the prior art, the technical scheme provided by the invention comprises the following steps: generating a sweep frequency laser signal and splitting the sweep frequency laser signal to form measurement light, reference light and resampling light; performing time stretching processing on the reference light to obtain a chirp signal; performing interference on measurement light and the chirp signal to obtain a measurement interference signal; performing interference on the reference light and the resampling light to obtain a reference interference signal; performing cross-correlation processing on the measurement interference signal and the reference interference signal, and extracting an optical path difference; and carrying out distance calculation by combining the resampling data, and outputting a target distance after the Doppler effect is compensated. The method is suitable for optical measurement work for performing high-precision absolute distance measurement on a non-cooperative target in a tiny vibration or disturbance environment.

The invention discloses an underground engineering lining disease detection system based on point cloud, and belongs to the technical field of underground engineering detection. In order to solve the technical problems that an existing underground engineering lining disease detection method is low in detection precision, low in automation degree and the like, underground engineering point cloud data to be detected and corresponding position information are collected, and an improved PointNet + + model is adopted for disease recognition. According to the method, original three-dimensional coordinates of a point cloud are expanded into seven-dimensional point cloud data containing coordinates, normal vectors and reflection intensity, the normal vector standard deviation of points in a neighborhood of each candidate point is calculated to serve as local geometric complexity, a local geometric complexity index is fused into sampling distance measurement, then a multi-scale local neighborhood is constructed by combining sphere query, and therefore the multi-scale local neighborhood is obtained. And extracting geometric features, texture features and deformation features by using a PCA feature dimension reduction technology, carrying out feature fusion based on a normal vector weighting mechanism, finally obtaining disease type classification based on a network model, and calculating the size and position of the disease.

In some aspects, a music-based output produced by a generative artificial intelligence is segmented into multiple segments. An encoder is used to generate multiple output embedding. Individual output embeddings of the multiple output embeddings are derived from individual segments of the multiple segments. A distance measurement between individual output embeddings of the multiple embeddings and individual training segment embeddings of multiple training segment embeddings is determined to create a set of distance measurements. The plurality of distance measurements is correlated to a plurality of content creators that created multiple content items used to train the generative artificial intelligence. One or more creator attributions are determined based at least in part on the correlating. A creator attribution vector that includes the one or more creator attributions is determined and compensation is provided to one or more content creators of the plurality of content creators based on the creator attribution vector.

The invention provides a UWB-NLOS identification and distance measurement correction method based on a DEA-PSO hybrid optimization Iight GBM algorithm, and the method comprises the following steps: 1, building multi-dimensional features after data stratified sampling, obtaining an HCNLOS data set through two times of label screening, and generating initial positioning; step 2, adopting a DEA-PSO hybrid optimization algorithm to realize LightGBM hyper-parameter automatic adjustment and optimization, and improving parameter adjustment efficiency through dynamic fitness evaluation and collaborative search; 3, constructing a classification model and a regression model in parallel; and 4, fusing the corrected NLOS data and the original LOS / HCNLOS data, and outputting a high-precision coordinate through a positioning algorithm, thereby effectively improving the positioning robustness in a complex environment.

The invention discloses a city three-dimensional model rendering method, which comprises the following steps of: establishing a multi-level detail model system to create a plurality of three-dimensional models with different levels of detail for each building object in a city scene so as to form a continuous hierarchical structure from high precision to low precision; spatial distance, view angle factors and object importance are comprehensively considered, effective distance measurement from a view point to a target object is calculated, a continuous LOD switching function is established according to the effective distance measurement, and the distance is mapped into continuous detail level values; a smooth interpolation algorithm based on time is applied, progressive switching is carried out between adjacent LOD layers, and visual jump during switching is eliminated; visual jump of LOD switching in urban three-dimensional model rendering is remarkably reduced, the stability of rendering performance is improved, and smooth and continuous visual experience is achieved.

The invention discloses a three-dimensional modeling method and system, and relates to the technical field of intelligent perception and three-dimensional reconstruction, and the method comprises the steps: taking BIM as a priori, sampling a geometric entity as a visibility evaluation point cloud, and constructing a graph structure environment state under the constraints of a field of view, distance measurement, an incident angle, overlapping and other sensors; on the basis, a deep reinforcement learning agent which is pre-trained by a synthetic scene and subjected to domain randomization migration is introduced, stations and scanning parameters are selected online according to an observation-decision-execution-update closed loop, visibility and coverage are re-estimated after each step of scanning, and self-adaptive correction is carried out on an unexecuted sequence in combination with online optimization; compared with an off-line global optimization method, the method has the advantages that a search space is effectively compressed through candidate station pre-generation and visibility gating, and continuous and adjustable balance is formed among coverage, point cloud quality and operation time by multi-target awards; for engineering constraints such as temporary shielding, site reachability, registration overlapping degree and the like, the strategy can be dynamically replanned in an execution period.

The invention relates to the technical field of laser radars, in particular to an obstacle detection method and system based on a frequency-modulated continuous wave laser radar, and the method comprises the steps: transmitting a chaotic frequency-modulated continuous wave signal to a detection region, and obtaining a reflection echo signal of a target object; performing decoupling calculation on the difference frequency electric signal to obtain a target time frequency distribution matrix; according to the target time-frequency distribution matrix, predicting the Doppler frequency shift amount of the target object at the next moment; based on the chaos frequency modulation adjustment signal, obtaining a distance measurement deviation compensation amount; the chaos frequency modulation adjustment signal is obtained by dynamically adjusting the chaos frequency modulation slope of the chaos frequency modulation continuous wave signal through the Doppler frequency shift amount; and compensating the difference frequency electric signal frequency value of the target object according to the distance measurement deviation compensation amount and the environmental noise data so as to solve obstacle distance speed detection information. According to the invention, the Doppler frequency shift amount is predicted in real time and the chaotic frequency modulation continuous wave signal parameters are dynamically adjusted, so that the accurate compensation of the distance measurement deviation is realized, and the accuracy of obstacle distance speed detection is improved.

The embodiment of the invention discloses a digital key ranging value filtering method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring ranging information of a plurality of UWB anchor points in real time; obtaining the position change trend of the digital key according to the distance measurement information; under the condition that the effective distance measurement value does not exist, a preset target position is obtained according to the positioning result corresponding to the moment t of the previous effective distance measurement value, the position change trend and the unlocking and locking state of the vehicle terminal, and a predicted distance is obtained according to the distance relation between the effective distance measurement value at the moment t and the preset target position; obtaining a prediction duration T according to the prediction distance; in the T, when an effective distance measurement value is not detected, state one-step prediction of a Kalman filtering algorithm is executed to obtain a filtered distance measurement value, and when the effective distance measurement value is detected, the state one-step prediction is terminated, and a filtering estimation value is obtained according to the Kalman filtering algorithm to serve as the filtered distance measurement value; and obtaining a positioning result of the area outside the vehicle according to the filtered distance measurement values of the plurality of anchor points.

Disclosed herein is a device for filtering a point cloud. The device may include processor configured to receive a plurality of sensed points representing distance measurements to points in an area around an entity. The processor may also be configured to determine, for each sensed point of the plurality of sensed points, one or more probabilities that the sensed point is associated with an obstacle in the area around the entity, wherein each probability of the one or more probabilities is based on a corresponding filter of one or more filters. The processor may also be configured to generate a filtered point cloud from the plurality of sensed points based on, for each sensed point, a hierarchical combination of the one or more probabilities.

A position determination device, which determines a position of a portable device relative to a vehicle, includes a first communication unit performing Bluetooth (registered trademark) communication with the portable device and a computer executing a process for determining the position of the portable device. The first communication unit transmits and receives (i) a modulation signal for data communication and (ii) continuous wave signals for distance measurement purpose. The first communication unit maintains a communicable state with the portable device even while the computer operates in a power saving mode. The first communication unit executes a process of calculating a distance from the first communication unit to the portable device using data related to reception phases of the continuous wave signals transmitted from the portable device, compares the calculated distance with a predetermined value, and switches from the power saving mode to a normal mode based on comparison result.

The invention provides a high-dynamic deformation measurement system and method based on laser section contour differential scanning. The measurement system is composed of a section contour measurement unit, a calibration unit, an error compensation unit and a data processing unit, wherein the section contour measurement unit comprises a multi-sight-line structured light sensor module, a speed sensing module and a distance measurement module; the calibration unit comprises a synchronous control module, an adjustment module and a common tooth-shaped calibration target; the error compensation unit comprises a vibration detection module, a posture detection module and a temperature detection module; the data processing unit is a device with programming and computing functions. The measuring method comprises the following steps: (1) calibrating a laser plane and an image plane; (2) unifying a global coordinate system; (3) obtaining point cloud data; (4) error compensation; (5) constructing a deformation time-history model; and (6) carrying out maximum deformation global optimization. According to the measurement system and method, accurate expression and maximum value global optimization of a pavement micro-deformation three-dimensional space under the load effect can be realized.

The invention discloses an intelligent fault recording and traveling wave distance measurement integrated control method and device, and belongs to the technical field of fault positioning, and the method comprises the steps: collecting the power frequency electric quantity data and high-frequency traveling wave data of monitoring points at two sides of a fault line; calculating a first fault distance estimation value based on the power frequency electrical quantity data, and identifying an initial traveling wave head based on the high-frequency traveling wave data to calculate a second fault distance estimation value; defining an evaluation time period, and calculating a signal-to-noise ratio value in the evaluation time period; and according to the signal-to-noise ratio value, determining the contribution degree of the first fault distance estimation value and the second fault distance estimation value in generating final fault positioning distance calculation, and performing comprehensive processing on the first fault distance estimation value and the second fault distance estimation value in combination with the contribution degree to obtain a final fault positioning distance. According to the invention, the accuracy and reliability of fault positioning are improved, and positioning requirements under different fault conditions and signal environments are met.

The invention provides a heterogeneous multi-sensor information fusion method and system for accurate positioning of coal mine underground mining equipment, and the method comprises the steps: S1, collecting inertial navigation information, and extracting the pose information of a heading machine; s2, inputting the pose information of the heading machine into a millimeter wave radar; s3, distance measurement information of the laser radar and the millimeter wave radar is collected; s4, extracting target position information from the target library; s5, constructing first branch information and second branch information; s6, performing information fusion on the collected inertial navigation information, the first branch information and the second branch information by adopting a fusion technology based on a factor graph to form fusion information; s7, returning and transmitting the fusion information to the inertial navigator; and S8, the inertial navigator carries out navigation information correction according to the fusion information. According to the invention, a multi-sensor fusion scheme which takes inertial navigation as a basis and takes a laser radar and a millimeter-wave radar as main auxiliary equipment is adopted, so that positioning equipment which can completely adapt to performance requirements of underground operation of a coal mine is provided.

The invention provides a power distribution network fault intelligent positioning and self-healing recombination method and system. The method comprises the steps that S1, operation data of a power distribution network are acquired and preprocessed; s2, modeling the power distribution network topology into a weighted undirected graph, and constructing transient characteristics including node characteristics and edge characteristics; s3, on the basis of the transient characteristics and the power distribution network topology, the fault type is judged in real time by adopting a graph convolutional network, and a fault section is determined in combination with a traveling wave distance measurement and impedance method; s4, when entering an isolation fault state, automatically generating a power supply reconstruction scheme meeting current, voltage and switch constraints, and selecting an optimal scheme through multi-objective optimization; and S5, issuing a switching instruction according to the optimal scheme to complete topology reconstruction, and updating a fault identification and recombination strategy according to an actual execution result to improve positioning precision and recovery efficiency. According to the invention, a novel fault processing scheme integrating multi-source measurement, an efficient algorithm and online learning can be adopted, so that the power failure time is shortened, the power failure range is reduced, and the toughness of the power distribution network is improved.