254 results about "Spatial localization" patented technology

The invention relates to the field of remote sensing image processing, in particular to a high-resolution remote sensing image semantic segmentation method based on multi-scale feature fusion, which comprises the following steps: acquiring a public remote sensing image data set, preprocessing the image, and constructing a training and testing set of semantic segmentation; a CTMFNet is designed, an encoder is composed of a lightweight residual module and an MS-Transform, and local space details and global context information are extracted; rID is adopted to reduce spatial information loss, LSFE is introduced to improve spatial positioning capability, and feature calibration is carried out in space and channel dimensions through DecoderAttn to realize boundary fine segmentation; inputting the training sample into the network for training to obtain a converged optimal semantic segmentation model; and inputting the test set into the model to obtain a semantic prediction map, and outputting a fine segmentation result of the remote sensing image through multi-scale fusion and boundary restoration. According to the method, the precision and robustness of ground feature extraction are effectively improved, the calculation cost is remarkably reduced while high segmentation precision is kept, and the method has good practical value and popularization prospects.

The invention relates to an intelligent analysis method for energy consumption of industrial solid waste treatment, which comprises the following steps of: constructing a layered digital twinborn model for mapping a physical structure, a process flow and an energy consumption relationship through multi-point multi-dimensional data fusion acquisition and data cleaning, synchronization and standardized preprocessing; the model is used for feature coupling extraction and anomaly detection, spatial positioning and analysis of energy consumption anomaly are realized, multi-scene deduction and parameter optimization are performed through a digital twin sandbox, influence paths and anomaly factors are accurately identified, and optimal intervention suggestions giving consideration to energy conservation, productivity and process stability are automatically given. According to the scheme, the real-time performance and accuracy of energy consumption abnormity diagnosis of the production line are improved.

The invention belongs to the technical field of fault detection, and relates to a high-voltage transmission line fault detection and identification method. The method comprises the following steps of: dividing candidate fault sections according to a topological structure by synchronously acquiring steady-state and transient-state traveling wave signals of key nodes of a power grid; identifying a fault by using a multi-feature fusion criterion and extracting traveling wave features; executing mode recognition-based steady-state section judgment and multi-terminal ranging and polarity verification-based transient positioning in parallel to generate two types of positioning result sets; and finally, carrying out intelligent fusion judgment on the two types of results under topological constraints. According to the method, the problems that a traditional single-point signal analysis method cannot determine a fault section, lacks space positioning capability and is insufficient in adaptability are solved, section-level accurate positioning of the fault is realized, and the positioning accuracy, robustness and fault processing efficiency are remarkably improved.

The invention provides a tunnel defect automatic identification and evaluation method and system, and relates to the technical field of engineering monitoring, and the method comprises the steps: obtaining the surface deformation data and internal stress distribution data of a tunnel collected by each sensing node, and carrying out the unified clock calibration and vibration data screening, generating a multi-source data packet; feature level fusion is carried out on the multi-source data packet, a fusion feature matrix is generated, and the stress abrupt change points are the sensing nodes with stress abrupt change; and based on a plurality of grid units in the three-dimensional initial model of the tunnel, embedding the fused feature matrix according to the timestamps and spatial localization of the sensing nodes to generate a feature structure model. The tunnel structure can be dynamically monitored in all directions, the space-time coupling characteristics of the defects in the structure evolution process are accurately and effectively captured, and reliable decision support is provided for early warning, traceability, treatment and the like of the tunnel quality defects.

The invention discloses a wireless network coverage optimization method based on spatial positioning and transmitting power regulation and control. The method comprises the following steps: S1, collecting real-time signal quality and link state data of a base station and user equipment; s2, dynamically adjusting the transmitting power of the base station according to the collected signal quality and link state data; s3, constructing an interference sensing matrix, further calculating a conflict weight according to the interference sensing matrix, and optimizing frequency and time slot resources based on the conflict weight; s4, adjusting a frequency subset, a time slot subset and a power upper limit according to an optimization result; s5, dynamically adjusting the transmitting power and the interference coordination strategy by receiving interference information from other base stations in real time and the feedback of the user; and S6, adjusting power distribution, spectrum resources and channel selection of the network according to the real-time feedback of the network environment. According to the method, an efficient and scientific optimization scheme can be provided in wireless network coverage optimization, and remarkable technical values and economic benefits are brought to practical application.

A method for surveying an environment by a movable surveying instrument with a progressional capturing of 2D-images by at least one camera and applying a visual simultaneous location and mapping algorithm (VSLAM) or a visual inertial simultaneous location and mapping algorithm (VISLAM) with a progressional deriving of a sparse evolving point cloud of at least part of the environment, and a progressional deriving of a trajectory of movement. The method comprises a progressional matching of the sparse evolving point cloud with a previously derived 3D-geometry, with a minimizing of a function configured to model a distance between the sparse point cloud and the previously derived 3D-geometry and deriving a spatial localization and orientation of the surveying instrument. At least one surveying measurement value of the environment by a spatial measurement unit is combined with the sparse point cloud or the previously derived 3D-geometry.

The invention discloses an image forgery positioning method based on double-flow multi-scale feature fusion, and belongs to the technical field of image forgery positioning, and the method comprises the steps: respectively extracting multi-scale semantic features and noise features of a normalized RGB image through a double-branch structure; stacking the same-scale features to generate preliminary fusion features; multi-scale enhancement operation is executed, and enhancement features are generated by combining global channel weighting and local space enhancement; performing up-sampling splicing on the multi-scale enhanced features, encoding space information in horizontal and vertical directions through a coordinate attention fusion module, generating direction attention weights, and performing weighted fusion on the features; and generating a prediction mask based on the weighted fusion feature, and combining a Dice loss function and a Focal loss function to optimize the model. According to the method, semantic and noise information is comprehensively utilized, the multi-scale feature expression and spatial positioning capability is enhanced, and the counterfeit positioning precision and robustness in a complex scene are improved.

The invention provides a soil organic pollution concentration prediction method and system based on a resistivity parameter, and the method comprises the steps: synchronously obtaining dielectric constant distribution data, conductivity spatial distribution data, a resistivity parameter and a polarizability parameter of a target region in an organic pollution detection scene in a saline-alkali soil environment, and obtaining the dielectric constant distribution data, the conductivity spatial distribution data, the resistivity parameter and the polarizability parameter of the target region; and constructing a bimodal characteristic matrix reflecting the electrical characteristics of the soil. And performing multi-source coupling on the bimodal characteristic matrix, the dielectric constant and the conductivity data to generate a dynamic data set, and analyzing and extracting the polarization attenuation characteristic difference between the organic pollutants and the salt ions by using a frequency domain dielectric spectrum. And finally outputting a spatial concentration distribution prediction result of the organic pollutants in the high salinization environment in combination with a machine learning model. According to the method, the detection accuracy and the spatial positioning precision of the organic pollutants in the high-saline-alkali soil are improved.

The invention relates to the technical field of three-dimensional models, and discloses a GIS data-based low-altitude visual three-dimensional model automatic generation method, which comprises the following steps of: acquiring multi-source GIS vector data from an open geographic data source, performing standardized preprocessing through a data cleaning rule set, constructing a Cesium earth scene basic framework in a UE5 engine environment, and dynamically generating a city L2-level three-dimensional visualization model based on a preprocessed GIS data stream; when a low-altitude visual three-dimensional model is generated, a lightweight data format is adopted, data transmission efficiency and dynamic updating capability are improved, complex light environment changes can be adapted in real time, the problem of color distortion on the surface of the model is reduced, meanwhile, a visual angle deviation detection and correction mechanism is established, the geometric body edge distortion phenomenon is relieved, and the generation efficiency of the low-altitude visual three-dimensional model is improved. And the color rendition precision and the spatial positioning reliability of the low-altitude scene are improved.

The invention relates to the technical field of three-dimensional visualization, in particular to a power grid line loss intelligent diagnosis and visualization method based on multi-source data acquisition, and the method comprises the steps: obtaining a sensor data grouping sequence, detecting power fluctuation synchronism, extracting a change trend, analyzing a power difference and a node trend, marking an abnormal path, generating a line loss map, and positioning an abnormal node coordinate level. And mapping the topological graph to adjust the style, and generating a visual layer result. According to the invention, through obtaining the multi-dimensional data of the feeder line and performing efficient analysis, capturing power fluctuation and abnormity, identifying abnormal nodes in combination with the power difference of adjacent nodes, analyzing the fluctuation rate to reveal the line loss area and the structure abnormity, calibrating the abnormal position by using the three-dimensional coordinate, realizing spatial positioning and risk assessment, and clearly displaying the operation state by the three-dimensional layer. The monitoring accuracy is improved, path connection and node positioning help to quickly identify a high-risk area, the operation and maintenance efficiency and the diagnosis comprehensiveness are optimized, and a precise basis is provided for power grid management.

A method for determining an optimal installation position of an electronic device in an area of a building, the electronic device being configured to monitor and / or serve the area, comprising the following steps: Providing a representation of the building, wherein the area comprises at least one building element; Generating data points arranged in a grid; Labelling each data point with a data point label, the data point label providing information if a respective data point is associated with the at least one building element and, if the data point is associated with the at least one building element, about which kind of building element the data point is associated with; Simulating placements of the at least one electronic device at valid installation positions, thereby determining a monitoring and / or serving coverage of the electronic device; and Outputting the optimal installation position with the highest monitoring and / or serving coverage.

The invention relates to the technical field of pile foundation deformation measurement, in particular to a pile foundation deformation distributed test method and system, and the method comprises the steps: obtaining a time sequence strain value sequence of sampling points of a tower pile foundation, calculating a dynamic disturbance index, extracting a quasi-static signal, and determining a long-term strain value increment through time domain trend analysis; through space-time decoupling operation, correlation between time evolution behaviors of a sampling point and a physically adjacent sampling point is compared, and a space localization index is determined; taking the spatial localization index as a confidence coefficient weight, and performing weighted distribution on the long-term strain value increment to respectively determine an adaptive global trend component and a local abnormal component; and finally, performing spatial integral operation on the global trend component and the local abnormal component to obtain two decoupled deformation curves so as to determine the deformation state. The method improves the accuracy of the deformation test.

The invention relates to the technical field of data processing, and discloses a drainage pipe network rain and sewage mixed connection tracing and spatial positioning method for a micro monitoring station network, which comprises the following steps: defining an upstream convergence pipe network range of each micro monitoring station according to a flow direction connection relationship of a drainage pipe network and layout nodes of the micro monitoring stations, establishing a unique mapping relation library between each pipe section and the corresponding multi-stage monitoring topological sequence; obtaining water quality and water level data of a monitoring station, intercepting an analysis time period, and identifying a target monitoring topological sequence which generates a response currently in the mapping relation library based on a time-space propagation association attribute of data between stations; locking an isomorphic mapping candidate pipe section set corresponding to the sequence, and constructing a pollutant source emission inversion model of each candidate pipe section according to a pipe network fluid transport diffusion mechanism; and calculating the fitting deviation degree of the source hypothesis of each candidate pipe section to the monitoring data by using the model, and selecting the pipe section with the minimum deviation degree as a positioning result.

The invention provides a space registration and image guiding method for a soft tissue intervention puncture surgical robot, belongs to the field of surgical robots, and relates to an intelligent puncture surgical robot registration guiding method combining an optical positioning system and an AR technology. And full-flow closed-loop control from preoperative image reconstruction to intraoperative real-time guidance is realized. The method not only inherits the advantages of an optical positioning system in the aspect of spatial positioning, but also enhances the information expression ability of the surgical field by means of the AR technology. According to the method, a closed-loop process from preoperative image reconstruction to intraoperative real-time guiding can be constructed, the problems that an existing puncture guiding mode is difficult to register and lacks visual feedback are solved, puncture operation guiding with high precision, high real-time performance and high visualization ability is achieved, the intuition of puncture path planning and operation safety are improved, and the operation efficiency is improved. Good clinical popularization values are realized.

The invention discloses a method and system for screening drug targets with space-time specificity and computer equipment, and relates to the technical field of bioinformatics and computational biology. The screening method is based on single cell transcriptome sequencing data, and comprises the following steps: (1) quantitatively reconstructing spatial positioning and functional modes of cells in tissues, namely 1.1) carrying out data preprocessing on the single cell transcriptome sequencing data; 1.2) reconstructing the spatial positioning of the single cell; 1.3) reconstructing a single cell biological function mode; (2) screening a drug target with space-time specificity, wherein the screening comprises the following steps: 2.1) cell-cell communication analysis; the invention discloses a single-cell data analysis method based on a GRN (Gene Regulatory Network), which is characterized by comprising the following steps of (1) establishing a single-cell data analysis method, (2) establishing a GRN (Gene Regulatory Network) taking a specific tissue microenvironment state as a core, and (3) discovering a target spot. The single-cell data analysis method is innovative, provides a new thought and a technical path for research and development of drugs for metabolic diseases and other systemic diseases, and has a popularization and application basis.

The invention discloses a distribution network tower material identification method based on spatial three-dimensional segmentation and a point cloud group structure, and the method comprises the steps: collecting and preprocessing distribution network tower and environment three-dimensional point cloud data, and constructing a material feature database; calculating the space distance between the points, and constructing an undirected point cloud picture; selecting seed points according to density, distribution or rules in the graph, wherein each seed point corresponds to a material category; carrying out random walk clustering by taking the seed point as a starting point, and completing space segmentation according to a probability maximum principle; constructing an improved three-dimensional Gaussian mixture model, training parameters, and generating fine-grained clustering labels; the clustering labels and the feature database are combined to complete type calibration, quantity statistics and spatial positioning; and outputting a structured result for material inventory, inspection and management. According to the method, the random walk clustering and the improved three-dimensional Gaussian mixture model are fused, so that high-precision identification and spatial positioning of the distribution network tower materials are realized.

The invention relates to the technical field of AR, and discloses an AR war chess projection and identification method and system based on spatial positioning and region segmentation. The method comprises the following steps: acquiring a map local image, identifying angular point pixel coordinates and angular point world coordinates of a reference mark in the map local image, and calculating a working range polygon of a map surface currently covered by a projection device based on the angular point pixel coordinates and the angular point world coordinates; the coordinate information of the working range polygon is sent to a server, and the server screens local situation data located in the working range polygon from the global situation data; and receiving the local situation data pushed by the server, rendering a projection image limited in the working range polygon, driving the projection device to project the projection image to the surface of the map, and displaying situation enhancement information in a region corresponding to the working range polygon in an overlapping manner. According to the invention, the efficient multi-device cooperative work capability is realized, and the technical problem of large-size map AR enhancement is solved.

The present application provides a method for generating an environmental model, a display method, an apparatus, an electronic device, and a storage medium, and relates to the field of Internet of Things technology. The generation method includes: displaying a spatial layout diagram corresponding to a target scene; the spatial layout diagram is generated based on the relationship between the trajectory of a first target object in the target scene and each space in the target scene; identifying each second target object deployed in the target scene, and obtaining the position of each identified second target object in the target scene; generating an environmental model of the target scene based on the position of each second target object in the target scene and the spatial layout diagram corresponding to the target scene, for describing the status of the first target object and / or the second target object in the target scene. The present application associates the second target object with the spatial layout diagram, and provides a device monitoring method based on spatial positioning, which can intuitively monitor various equipment and facilities in the target scene, thereby helping to improve the effectiveness of the device control service.

The invention relates to the technical field of product design, in particular to a household appliance appearance defect optimization product design method based on image discrimination, which comprises the following steps: acquiring a household appliance appearance image, calculating a gradient direction, constructing a distribution matrix, analyzing consistency to generate a defect edge image, extracting high-frequency feature scores to identify defect areas, and clustering point cloud to output defect clusters. According to the method, by calculating the gradient direction numerical value of each pixel point and constructing the gradient direction distribution matrix, the processing capacity of the directivity difference of the household appliance surface texture is effectively improved, the defect point cloud is accurately divided through the density-based noise application spatial clustering algorithm, the defect point cloud is accurately divided, and the defect point cloud is accurately divided. According to the method, the space positioning accuracy of the defect area is improved, the precision of optimization design is ensured, curved surface reconstruction is performed in combination with the least square method, the appearance design of the household appliance is accurately corrected, and the production efficiency and the design quality are optimized.

Disclosed is an audio codec that represents an immersive signal by a two-channel stereo signal that is a stereo rendering of the immersive signal and directional parameters. The directional parameters may be based on a perceptual model describing the direction of virtual speaker pairs to recreate the perceived location of dominant sounds. Audio processing at the decoder may be performed on the stereo signal in the frequency domain for multiple channel pairs using time-frequency tiles. Spatial localization of the audio signals may use a panning approach by applying weightings to the time-frequency tiles of the stereo signal for each output channel pair. The weightings for the time-frequency tiles may be derived based on the directional parameters, an analysis of the stereo signal, and the output channel layout. The weightings may be used to adaptively process the time-frequency tiles using a de-correlator to reduce or minimize spectral distortions from spatial rendering.

The invention provides a lightweight intelligent control method for a low-altitude operation scene, and the method comprises the steps: focusing a low-altitude key target through an attention mechanism based on a lightweight deep learning model; data enhancement is carried out through a dynamic data enhancement module so as to expand the diversity of training samples; calling a space-time calibration model to process the multi-source data, and controlling a time synchronization error and a space positioning deviation within a preset range; based on a dynamic obstacle trajectory prediction module, historical motion data and environmental constraints are fused, and a lightweight LSTM network is adopted to predict a trajectory of a dynamic target in a future time period; and calling a task priority-computing power load dynamic matching mechanism to realize task allocation, and adjusting computing power occupation of non-critical tasks according to a designed energy consumption perception scheduling strategy. According to the method, the autonomous perception, decision making and resource management capabilities of the low-altitude operation unmanned aerial vehicle in a complex environment are comprehensively improved, so that the low-altitude operation unmanned aerial vehicle better meets the requirements for safety, efficiency and continuity in actual operation.

The invention discloses a quadruped robot space precise positioning method and system based on deep learning. The quadruped robot space precise positioning method specifically comprises the steps that S1, a laser radar data stream and an inertial measurement unit data stream are aligned to generate a synchronous sensing data sequence in a unified mode; s2, determining a mapping pose sequence through consistency evaluation of poses output by the offline point cloud registration algorithm pool; s3, performing parallel loopback detection to generate a unified loopback constraint set; s4, the mapping pose sequence, the loopback constraint set and the pre-integration constraint are written into the factor graph model to generate a three-dimensional point cloud reference map; s5, the local point cloud frame and the three-dimensional point cloud reference map are registered, and a map matching pose is output; s6, the map matching pose and the pre-integration result are written into a factor graph model to continuously solve and output a continuous-time six-degree-of-freedom pose result; and S7, outputting a six-degree-of-freedom pose result in continuous time. According to the invention, direction constraint consistency point cloud registration and dual-channel loopback optimization are introduced, and stable and high-precision positioning of the closed space is realized.

The invention relates to the technical field of Internet of Things coding, in particular to a communication infrastructure asset digital management and operation and maintenance system based on the Internet of Things, which comprises the steps of acquiring equipment output content, arranging frequency bands and interface identifiers, combining positioning information for verification, generating a unified record structure, expanding coding comparison to form an evolution number, and carrying out management and maintenance. And inserting a character to construct an intergenerational identifier, matching boundary refined region mapping, and aligning and splicing to generate an operation and maintenance identifier. According to the method, a uniform data field structure is formed through sequential combination of frequency band coverage and interface identification and fusion of spatial positioning information, a continuous equipment intergenerational relationship is constructed through splicing of evolution sequence numbers, spatial distribution levels are processed through the number of region registration and boundary rules, and the spatial positioning information is obtained. Uniform identification content is generated through splicing of the intergenerational numbers and the region identifiers, collaborative organization of communication facilities in development states, space attribution and management relations is supported, and the scheduling and management efficiency of asset data is improved.

The invention discloses a telemetering site position display and information query system and method based on AR information labeling. The system comprises a multi-source data management module, an interactive query module, an AR recognition module and a mobile terminal device. The interactive query module is arranged in mobile terminal equipment, and the mobile terminal equipment is in communication connection with the AR identification module through the communication module; the AR identification module is in communication connection with the multi-source data management module through the communication module; equipment pose synchronization, spatial range screening and a three-dimensional space anchoring algorithm based on ARCore are executed through the system, and finally hierarchical information capable of being interactively displayed is generated through AR label generation and rendering; the method aims at solving the problems that in the prior art, a telemetering site information query mode is backward, the information display dimension is single, and operation steps are tedious and low in efficiency, and telemetering site visual query can be achieved through the combination of the mobile intelligent device and the space positioning and AR labeling technology.

The invention provides a spatial diagnosis system for mountainous city facility layout. Comprising the following steps: a data acquisition and preprocessing module preprocesses initial multi-source spatial data of a target area to obtain target multi-source spatial data; the space unit division module performs space unit division on the target area to obtain a plurality of space units; a public service facility reachability calculation module determines public service facility reachability of a target demand point in the target area according to the target multi-source spatial data; the spatial difference diagnosis module identifies spatial heterogeneity of each spatial unit on different scales according to the target multi-source spatial data; the problem space positioning module performs problem space positioning according to the public service facility accessibility of the target demand point and the topographic features of the target area; and the optimization scheme generation module generates an optimization scheme for each problem space. Therefore, according to the regional characteristics of the mountain city, optimal configuration schemes of different facilities are provided in a targeted manner, so that the scientificity and rationality of walking facility configuration are improved.

The invention discloses a large-burial-depth pipeline nondestructive detection method and system, and relates to the technical field of pipeline positioning. The system combines a region feasibility identification module, an initial positioning module, a multi-type nondestructive detection unit, a multi-path anomaly identification module, an underground structure matching module, an intelligent obstacle avoidance compensation module and a signal fusion module, and adopts a multi-source information fusion and intelligent path planning technology. And high-precision and non-intrusive nondestructive detection of the metal pipeline with the burial depth exceeding 5 meters is realized. Through comprehensive evaluation of ground obstacles and underground interference sources, the detection path layout is optimized, and the problems of signal interference, multi-path reflection and detection blind areas in the urban complex underground environment are effectively solved. The system can accurately reject non-target structure reflection signals, dynamically generate an obstacle avoidance compensation path, and improve the detection coverage rate and the signal integrity. And finally, three-dimensional space positioning and digital map coordinate output are realized, and the accuracy of pipeline positioning and the reliability of depth estimation are remarkably improved.

The invention discloses a cutting pick wear detection method and system for a heading machine, and relates to the technical field of mining machinery state monitoring, and the method comprises the steps: obtaining a cutting pick tool seat and a tool bit, fixing the tool bit on the tool seat through a plurality of rotating shafts, and arranging a plurality of high-bandwidth acoustic emission sensors on the rotating shafts; identifying a rotation detection signal by using a high-bandwidth acoustic emission sensor, and extracting characteristics such as acoustic emission pulse starting time and peak amplitude; constructing a sound source space positioning model to obtain a sound source positioning result; and mapping a sound source positioning result to the rotating shaft three-dimensional model to identify hidden wear, and outputting a risk level. The technical problems that the traditional detection means is difficult to accurately identify the hidden wear of the heading machine cutting tooth rotating shaft and cannot comprehensively and accurately acquire wear information to meet the accurate evaluation requirement are solved, and the accurate identification and risk grade evaluation of the hidden wear of the heading machine cutting tooth rotating shaft are achieved; and the accuracy and comprehensiveness of cutting pick wear detection are improved.

The invention relates to the technical field of computer vision detection, and discloses a PCB defect detection method based on improved YOLOv8. According to the invention, by introducing the C2f module fused with the coordinate attention mechanism, the adaptive weighted bidirectional feature pyramid structure and the lightweight decoupling detection head, the feature extraction capability and the spatial positioning precision of the model for PCB micro defects are improved, and the problem of small target missing detection is solved; meanwhile, in combination with defect area specific enhancement training and a dynamic receptive field optimization strategy, the anti-interference capability of the model to a complex background is enhanced, and the false detection rate is greatly reduced; besides, by adopting a structure re-parameterization technology, the model reasoning speed is improved while the detection precision is ensured, so that the method can be efficiently deployed on industrial detection equipment with limited resources, the balance of high precision and high efficiency is realized, and the comprehensive performance of PCB defect detection is comprehensively improved.