222 results about "Three-dimensional graph" patented technology

The invention discloses a building pedestrian simulation statistics and analysis method, and belongs to the technical field of simulation. According to the invention, a comprehensive pedestrian behavior evaluation and optimization scheme is provided through normal pedestrian circulation simulation and emergency evacuation simulation in combination with statistical analysis, data visualization and an optimization algorithm. The system manages pedestrian density through a KD tree, performs real-time data visualization by using ScottPlot, generates one-dimensional, two-dimensional and three-dimensional charts, and visually displays pedestrian distribution and flow conditions in a building. In an emergency evacuation scene, the system dynamically plans a path through a # imgabs0 # algorithm, and identifies and relieves a potential bottleneck area in combination with a heuristic function of congestion measurement. The simulation system can collect abundant statistical data including evacuation time, people flow distribution, congestion point analysis and the like, and provides a scientific basis for building safety design improvement and emergency plan making.

The invention discloses a three-dimensional ground penetrating radar map generation method. The method comprises the following steps that S1, a three-dimensional ground penetrating radar is used for collecting selected road internal structure information to obtain original data; s2, preprocessing the obtained original data; s3, carrying out normalization processing and trilinear interpolation on the longitudinal section data of the preprocessed radar data; s4, generating a three-dimensional ground penetrating radar map, wherein the three-dimensional ground penetrating radar map at least comprises a single-channel oscillogram, a slice map, a longitudinal profile map and a three-dimensional map; and S5, based on the three-dimensional diagram, introducing a gradient enhanced adaptive perspective algorithm, realizing perspective of the three-dimensional diagram, and highlighting a disease area. According to the method, an effective and convenient standardized map is formulated in combination with data collected by the three-dimensional ground penetrating radar, the problems of section discretization and information discontinuity are solved, and through the generated three-dimensional perspective drawing, the visualization effect of a road disease area is effectively enhanced, and accurate positioning and recognition of road internal diseases are achieved.

The invention discloses a three-dimensional curved surface pattern layering processing method based on parameterized segmentation, and aims to solve the problem of high-precision pattern processing on the surface of a curved surface by using a laser scanning galvanometer. The method comprises the following steps: firstly, importing a three-dimensional model, and carrying out parameterization processing to obtain a two-dimensional parameter domain; positioning a to-be-processed plane pattern in the two-dimensional parameter domain to form a complete two-dimensional geometric grid covering a pattern area, generating a three-dimensional pattern grid attached to a curved surface, and calculating a center normal vector of the three-dimensional pattern grid; then, generating an equidistant plane group on the surface of the curved surface, and calculating an intersection line of the plane and the three-dimensional pattern grid as a laser scanning track; and the five-axis linkage platform-galvanometer system is started for machining. Through the parameterization domain, distortion of curved surface pattern machining is effectively solved, machining uniformity is improved, and the method is particularly suitable for laser machining of large-scale or high-complexity curved surface patterns.

The invention relates to the technical field of green product analysis, and discloses a green product full life cycle analysis system based on big data. The system comprises a data acquisition module, a preprocessing module, an environmental impact assessment module, a resource consumption optimization module, an association modeling and result generation module and a visual interaction module. The system collects data of all stages of a full life cycle and related element data of environment, resources, carbon emission and the like, after preprocessing of abnormal value elimination, entropy weight method weighting and the like, environment influence is dynamically evaluated through a fuzzy membership function, resource consumption is subjected to multi-objective optimization by utilizing a genetic algorithm, and the resource utilization rate is improved. A key stage is determined by means of grey relational degree, an analysis result is generated in combination with a multi-target decision model, and finally the analysis result is visually presented in the form of a three-dimensional map and a dynamic thermodynamic diagram. The system realizes efficient analysis and comprehensive evaluation of full-life-cycle data of green products, and provides scientific support for product environment performance optimization and decision making.

The invention provides a control parameter adjustment method based on a stability domain of a multi-grid-connected inverter system. The method comprises the following steps: acquiring a first proportionality coefficient and a first current reference value of a single-grid-connected inverter current controller; obtaining an effective power grid impedance matrix of the multi-grid-connected inverter system; based on the first proportionality coefficient, the first current reference value and the effective power grid impedance matrix of the multi-grid-connected inverter system, determining a loop gain matrix eigenvalue node diagram of the single-working-condition multi-grid-connected inverter system corresponding to the single-grid-connected inverter; determining a stability domain three-dimensional point of the single-working-condition multi-grid-connected inverter system based on a loop gain matrix eigenvalue node diagram of the single-working-condition multi-grid-connected inverter system; determining a multi-working-condition multi-grid-connected inverter system stability domain three-dimensional diagram corresponding to the single grid-connected inverter based on the single-working-condition multi-grid-connected inverter system stability domain three-dimensional point; and adjusting the first proportionality coefficient and the first current reference value based on the stability domain three-dimensional diagram of the multi-working-condition multi-grid-connected inverter system. The adjusting process is simple to operate and easy to implement.

The invention provides a 3D graph data processing method of a quantum graph neural network based on rotation arrangement equivariant, and the method comprises the steps: 1, building a rotation arrangement equivariant quantum graph neural network which comprises a rotation and arrangement equivariant module, a convolution and entanglement module, and a geometric deentanglement module; the rotation and arrangement isovariant module is used for processing geometric information and keeping rotation and arrangement isovariant of the quantum graph neural network; the geometric information entanglement module is used for distance and angle entanglement; the convolution and entanglement module is used for processing non-geometric information; and step 2, applying the quantum graph neural network to 3D graph data processing. According to the method, the limitation of an existing method in processing the three-dimensional diagram data can be solved, the model can cope with the change of the diagram data under spatial rotation due to the rotational symmetry, the consistency of the structure information of the diagram under different node arrangements is ensured due to the arrangement symmetry, and the method is suitable for the three-dimensional diagram data processing. According to the model, geometric information in three-dimensional diagram data can be more comprehensively understood and utilized.

Embodiments disclosed herein mitigate technological barriers in preparing, sourcing, and exporting 3D assets with practical applications for journalism. According to one embodiment, a computer-implemented method for generating a three-dimensional map is provided. The method includes displaying a two-dimensional region of a map on a graphical user interface (GUI), wherein the map is displayed along longitudinal axis and a latitudinal axis. The method includes obtaining, through the GUI, a first input from a user device, the first input comprising an indication of a selected sub-region of the two-dimensional region of the map, wherein the selected sub-region comprises a plurality of pixels having longitudinal coordinates bounded by a first longitude coordinate and a second longitude coordinate along the longitudinal axis and latitudinal coordinates bounded by a first latitude coordinate and a second latitude coordinate along the latitudinal axis. The method includes obtaining, from a first data source, elevation coordinates along a lateral axis corresponding to the longitudinal coordinates and the latitudinal coordinates for each of the plurality of pixels. The method includes generating a three-dimensional mesh of the selected sub-region, wherein the three-dimensional mesh comprises a plurality of vertices corresponding to the elevation coordinates, the longitudinal coordinates, and the latitudinal coordinates of the plurality of pixels and a plurality of edges connecting the vertices. The method includes displaying the three-dimensional mesh on the GUI.

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.

The invention relates to a porous medium modeling method based on a Lagguerre-Voronoi method, and the method comprises the steps: firstly generating a group of sphere data with the sphere diameter in logarithmic normal distribution by utilizing MATLAB software; using LAMMPS software to randomly stack the group of spheres in the fixed cubic space to obtain the sphere center coordinate and diameter of each sphere; the method comprises the following steps: randomly stacking spheres, performing space division on the randomly stacked spheres by using a Lagguerre-Voronoi method to obtain a corresponding three-dimensional Lagguerre-Voronoi graph, retaining edges and vertexes of each sphere division space in the three-dimensional Lagguerre-Voronoi graph, and generating a porous medium skeleton based on the edges and vertexes of each sphere division space; and finally, establishing a porous medium model of a required framework section shape according to the porous medium framework. Compared with a commercially available commercial foam structure, the porous medium model established by the invention can reproduce an actual foam structure more truly, and internal pores have good performance in the aspects of disorder and connectivity.

The invention innovatively provides a pile hole model risk assessment method, which is characterized by comprising a target detection model establishment step of acquiring pile hole three-dimensional image data in different states, and inputting the pile hole condition into a neural network for training, verification and testing to obtain a target detection model; a pile hole anomaly analysis step: forming a pile hole three-dimensional diagram from the collected pile hole data by using a 3D construction strategy component, inputting the pile hole three-dimensional diagram into a preset target detection model to obtain a pile anomaly point, and mapping the anomaly point into the pile hole three-dimensional diagram as a pile hole anomaly diagram; an abnormal point analysis step: obtaining abnormal data and normal data of the abnormal point through an abnormal point analysis strategy, and obtaining an abnormal probability according to the abnormal data and a target detection model; and the scheme correction step is used for obtaining normal data and abnormal data in the pile hole three-dimensional diagram, and obtaining a pile hole adjustment scheme through a scheme adjustment strategy according to historical data in the target detection model.

The invention discloses a method, a system, a medium and equipment for quickly judging the axial stability of an external short-circuit winding of a power transformer. In the method, a power transformer winding axial vibration calculation model is established; through changing a short-circuit current amplitude, a cushion block stress-strain curve characteristic value and a pre-tightening force, a critical condition of separation of a wire cake and a cushion block of a winding is obtained, and a three-dimensional map of a wire cake-cushion block vibration separation critical state is drawn. An axial stability analysis system when the power transformer is subjected to external short-circuit impact in an operation state is constructed, a computer is deployed locally to operate a calculation instruction corresponding to the method, and a short-circuit current peak value is extracted according to a current recording diagram of the power transformer under an external short-circuit fault; and determining a fault point location in the three-dimensional atlas according to the actual pre-tightening force of the winding and a cushion block stress-strain curve, and quickly judging the axial stability of the external short-circuit winding according to the relative relationship between the fault point location and a critical state interface.

The invention relates to the technical field of electric digital data processing, and discloses a 3D intelligent stocktaking method and device, and the device comprises a 4D millimeter wave radar disposed at the top of a stock bin, S1, obtaining the data of a corresponding coverage area detected by the 4D millimeter wave radar; s2, preprocessing the acquired data; S3, processing the preprocessed data by a point cloud data grid filtering algorithm to obtain point cloud data on grids on a global grid map; s4, checking the integrity of the data, and if blank grids exist in the global grid map, filling the grids of the blank data in the global grid map by using a point cloud smooth interpolation algorithm to form a final smooth point cloud; and S5, reconstructing the surface of the material, and constructing a three-dimensional diagram of the surface of the material according to the final smooth point cloud determined in the step S4. Through the 4D millimeter wave radar and various algorithms, the real-time and all-around monitoring of the material bin is realized, and accurate three-dimensional material level imaging is provided.

The invention discloses a lead compound optimization method and system based on skeleton constraint and training enhancement, and belongs to the field of artificial intelligence drug discovery. The method comprises the following steps: performing structural treatment on an initial lead compound, extracting a growth skeleton structure, and pairing a protein pocket structure; inputting information of the skeleton structure and the protein pocket structure into a coding model based on a three-dimensional graph neural network for joint coding to obtain structure coding representation; on the basis of a Delete model, an atomic distance-based resampling mechanism and a hydrophobic group mask are introduced, and a molecular generation model is constructed; training and tuning a molecule generation model through staged pre-training and a knowledge enhancement fine tuning strategy so as to improve the structural accuracy, the binding activity and the druggability of generated molecules; and inputting the structure coding expression into a trained and optimized molecular generation model PocketGrow to generate optimized molecules, screening the generated optimized molecules, and outputting a lead compound with development potential.

The invention provides a user abnormal behavior monitoring method, and belongs to the technical field of artificial intelligence. The method comprises the following steps: collecting user behavior data and relational data; generating three-dimensional diagram data; based on the user behavior data and the three-dimensional diagram data, abnormal features and cross-node abnormal association features are extracted in parallel; calculating an abnormal initial score based on the abnormal features, and identifying an abnormal sub-graph based on the cross-node abnormal association features; based on the abnormal recognition sub-graph, correcting the abnormal initial score to obtain an abnormal final score, and calculating a community confidence coefficient; and according to the abnormal final score and the community confidence, determining a user risk level, and generating a user abnormal behavior monitoring report. According to the method, the three-dimensional graph model is constructed by fusing the multi-source data, and the graph neural network is combined, so that accurate identification and risk assessment of the abnormal behavior of the user are realized, and the comprehensiveness and accuracy of monitoring are effectively improved.

A method includes accessing map data of an area of a real environment, the map data comprising three-dimensional feature descriptors describing features visible in the real environment. A plurality of map packages are generated based on the map data, wherein each of the map packages (1) corresponds to a two-dimensional sub-area within the area of the real environment, and (2) comprises a subset of the three-dimensional feature descriptors describing features visible in the sub-area. A first sequence of the plurality of map packages are broadcast through one or more base stations, wherein the first sequence is based on the two-dimensional sub-area of each of the map packages, wherein each of the map packages is configured to be received and used by an artificial-reality device to determine a pose of the artificial-reality device in the associated sub-area based on the associated subset of the three-dimensional feature descriptors.

The invention discloses an interference pulse suppression technology, and aims to provide a multi-type interference pulse suppression method based on signal waveform analysis, and the key point of the technical scheme is that the method comprises the steps: S1, building a partial discharge test system, and collecting and measuring partial discharge waveforms of different defect types; s2, collecting a partial discharge waveform of the to-be-detected cable; s3, preprocessing the collected partial discharge pulses of different defect types and the partial discharge waveform of the cable to be detected, analyzing the pulse waveforms corresponding to different defects and noise sources, and using an envelope line and a sine function to construct a mathematical model of partial discharge signals to extract pulse waveform characteristics; and S4, drawing a feature distribution two-dimensional diagram (beta-alpha and Ap-At) and a three-dimensional diagram (f-beta-alpha and f-Ap-At) through the extracted feature parameters, establishing an interference pulse and defect knowledge base, and realizing effective separation of partial discharge signals and interference pulses. The method is suitable for the technical field of interference pulse suppression.

The invention discloses a general building structure tensorization feature extraction method and system and related equipment, and the method comprises the steps: S1, selecting the node, edge and overall features in a building structure, and selectively selecting a label for an end application; s2, establishing a random sample library of the building structures of the same type based on the features and the labels selected in the step S1; s3, performing XYZ three-direction scanning on the building structure based on the building structure random sample library established in the step S2 to form a three-direction series diagram, and storing a three-dimensional diagram at the same time; s4, establishing a feature extraction and tensor data representation network; and S5, feature extraction, tensor data representation network training and model solidification are carried out. According to the scheme, the problems existing in the prior art can be effectively solved, the universal data feature representation content of the building structure can be formed, and the method can be applied to various tail ends such as subsequent access design algorithms, optimization algorithms and response prediction.

The invention discloses a casting part multi-mode intelligent cost accounting method and system, and relates to the technical field of casting engineering and intelligent cost accounting. The casting part multi-mode intelligent cost accounting method comprises the steps that process information in casting engineering is extracted and processed in a structured mode, and missing information of a plane drawing is automatically supplemented; matching a target casting process route and key parameters based on the process information subjected to the structured processing; and calculating the basic total cost according to the target casting process route, and correcting the basic total cost in combination with the historical data deviation, the real-time market data and the order variables to obtain the corrected total cost. Unified automatic analysis of the plane drawing and the three-dimensional drawing is achieved, the problem that information of the plane drawing is incomplete is solved through image recognition and rule completion, and the limitation that only a single drawing type is supported is broken through; the casting process constraint extracted from the three-dimensional drawing is directly used as a core parameter of process matching, and the plane drawing indirectly maps process requirements through feature recognition, so that quantitative association of drawing information-process parameter-cost is realized.

The present invention discloses a visual recognition method for bolt missing in a pipe gallery under the condition of robot mobile shooting. The method corrects the red channel of the bolt missing visual recognition data set, uses a median filter and a DnCNN combined model to remove impulse noise and Gaussian noise, and on this basis, performs grayscale transformation calculation, cepstrum compression operation and centering operation on the blurred image, performs edge detection operation and Radon transformation on the obtained image, and correctly estimates the blur angle; calculates the peak value and blur angle by utilizing the peak symmetry of the first-order differential autocorrelation and the cepstrum three-dimensional graph; constructs a point spread function for the blur parameter, and uses the Richason-Lucy algorithm to iterate the blurred image for multiple times, thereby restoring the image. The training set and the validation set are input into the improved Yolov8 model to prove the effectiveness of the constructed model. The present invention can achieve the purpose of improving calculation efficiency and prediction accuracy.

The invention relates to the field of mapping, in particular to a three-dimensional mapping method, which comprises the following steps of: initializing a system; oRB features are extracted from the left camera and the right camera; constructing an initial key frame: sending image data of a first frame of a left camera to a semantic thread, and setting the frame as the initial key frame; performing a mask prediction mechanism, key frame tracking and dual-stage tracking on the image of the left camera, and alternately performing key frame tracking and static tracking on the right camera; and binocular stereo matching is carried out according to results of the left camera and the right camera, map points are updated, and an obtained result is a three-dimensional diagram. The method has practical significance when being practically applied to rapid three-dimensional mapping of a small computing unit or a large scene, dynamic objects are filtered out of the mapping in the mode, the real-time performance and the mapping efficiency of the mapping are guaranteed, three-dimensional mapping can be rapidly completed on a low-computing-power platform, and the method is suitable for large-scale popularization and application. And the method has good practical performance and application potential.

The invention relates to the technical field of motor performance testing, and discloses a micro-control motor multi-dimensional dynamic loading testing system and method, and the system comprises a cooperative control and data collection module which synchronously collects the electrical parameters, the multi-point temperature, the load torque and the rotating speed of a micro-control motor to be tested through a hardware synchronous triggering mechanism, the data processing and performance analysis module performs loss separation calculation considering real-time temperature on the basis of the data to generate a three-dimensional MAP graph representing a performance coupling relation, and is configured to analyze the data in real time and identify a performance parameter abnormal change area in the testing process, so that the performance parameter abnormal change area is analyzed in real time. And an instruction is automatically sent to the cooperative control and data acquisition module so as to increase the density of test working condition points of the area, and self-adaptive test is realized. According to the invention, the performance characteristics of the to-be-tested micro-control motor under a complex working condition can be accurately and comprehensively obtained, and the automation degree and the data resolution of the test are improved.

The present disclosure provides systems and methods that combine physics-based systems with machine learning to generate synthetic LiDAR data that accurately mimics a real-world LiDAR sensor system. In particular, aspects of the present disclosure combine physics-based rendering with machine-learned models such as deep neural networks to simulate both the geometry and intensity of the LiDAR sensor. As one example, a physics-based ray casting approach can be used on a three-dimensional map of an environment to generate an initial three-dimensional point cloud that mimics LiDAR data. According to an aspect of the present disclosure, a machine-learned model can predict one or more dropout probabilities for one or more of the points in the initial three-dimensional point cloud, thereby generating an adjusted three-dimensional point cloud which more realistically simulates real-world LiDAR data.

The present application 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, obtaining sensor data grouping and sorting, detecting power fluctuation synchronicity, extracting change trend, analyzing power difference and node trend, marking abnormal path, generating line loss atlas, positioning abnormal node coordinate level, mapping topological graph adjustment style, and generating visualization layer result. The present application efficiently analyzes multi-dimensional data of a feeder line, captures power fluctuation and abnormality, identifies abnormal nodes in combination with power difference of adjacent nodes, analyzes fluctuation rate to reveal line loss area and structural abnormality, calibrates abnormal position by using three-dimensional coordinates, realizes spatial positioning and risk assessment, clearly displays operation state by three-dimensional layer, improves monitoring accuracy, helps to quickly identify high-risk area by path connection and node positioning, optimizes operation and maintenance efficiency and diagnosis comprehensiveness, and provides accurate basis for power grid management.

The invention discloses an urban rail transit engineering structure health ultrasonic vision measurement method and device, and relates to the technical field of urban rail transit engineering structure health monitoring. Firstly, the internal defect type and the internal defect position of a target structure are analyzed based on ultrasonic measurement data. By combining ultrasonic measurement and visual measurement, the internal defect and the external defect of the structure can be detected at the same time, and more comprehensive health state evaluation is provided. By analyzing the correlation between the internal defects and the external defects, the relation between the defects can be deeply understood, the root causes of the defects can be determined, the detected defects can be visually displayed in a three-dimensional image form by utilizing a three-dimensional reconstruction technology, and the detection accuracy is improved. And particularly, the associated defect three-dimensional diagram is subjected to three-dimensional display, so that engineers and decision makers can better understand the health condition of the structure, the workload of manual analysis is reduced, and the detection efficiency is improved.

The invention discloses a crawler-type dredging robot slip rate optimization control method and system, and relates to the technical field of crawler-type mobile robot control, and the method comprises the steps: 1, importing a dredging robot three-dimensional diagram, carrying out the modeling of a crawler chassis, obtaining a kinetic model, applying torque drive in the model, and obtaining motion data; 2, establishing a dynamic mathematical model according to the dynamic characteristics of the dredging robot, and obtaining the relation between the motion state of the dredging robot and torque driving; 3, the slipping condition of the robot is analyzed through the motion data, and the slipping rate of the robot in actual motion is obtained; 4, according to a slip rate calculation result, identifying an optimal slip rate through a self-adaptive variable step size strategy; 5, designing a driving anti-slip controller of the fuzzy sliding mode according to the dynamic mathematical model, the slip rate in actual motion and the optimal slip rate; and 6, the motion of the robot is dynamically adjusted according to the driving anti-skid controller.

An example computing system is configured to (i) receive a request to generate a cross-sectional view of a three-dimensional drawing file, where the cross-sectional view is based on a location of a cross-section line within the three-dimensional drawing file and includes an intersection of two meshes within the three-dimensional drawing file; (ii) generate the cross-sectional view of the three-dimensional drawing file; (iii) add, to the generated cross-sectional view, dimensioning information involving at least one of the two meshes; (iv) generate one or more controls for adjusting a location of the cross-section line within the three-dimensional drawing file; and (v) based on an input indicating a selection of the one or more controls, adjust the location of the cross-section line within the three-dimensional drawing file, update the cross-sectional view based on the adjusted location of the cross-section line, and update the dimensioning information to correspond to the updated cross-sectional view.

The invention discloses a digital coal yard management and control system, which comprises a coal feeding management module, a coal inventory module and a central control module, the coal feeding management module is used for collecting data of coal entering a factory, the coal stocktaking module is used for collecting three-dimensional model data of a coal pile, and the central control module comprises a partition management module, a central control unit and a three-dimensional display module; the partition management module is used for dividing a coal yard into at least two partitions and transmitting partition data to the central control unit; managing a stacking and taking strategy of the coal pile; the coal feeding module is used for conveying coal as received to a coal pile of a corresponding subarea according to the coal as received data; the central control unit is used for receiving the three-dimensional model data of the coal pile to generate a three-dimensional model of the coal pile; the central control unit is connected with the three-dimensional display module, and the three-dimensional display module is used for displaying the three-dimensional diagram of the coal pile in each subarea and displaying the real-time state of each subarea. The space of the coal yard is reasonably distributed and managed through partition management, so that the storage space of the coal yard is properly utilized, and the storage efficiency of the coal yard is improved.

The invention relates to the technical field of remote sensing surveying and mapping, and particularly discloses an intelligent surveying and mapping system and method based on a remote sensing technology, and the method comprises the steps: obtaining a multi-time-sequence remote sensing image data set of a target region through multiple platforms carrying intelligent sensing elements; performing three-dimensional reconstruction and cross-time-phase accurate alignment on the time-phase data to generate a three-dimensional space coordinate sequence under a unified coordinate system; carrying out conjoint analysis on the multi-time-sequence attribute of each spatial point in the sequence, and generating a fused spatio-temporal feature by distinguishing a persistent structure and instantaneous interference; constructing a three-dimensional graph structure according to the features, performing hierarchical aggregation, and identifying a point set with similar features and continuous space as an entity unit with a single semantic identifier; based on the semantic and geometric attributes of the entity units, automatically establishing a spatial topology and time evolution relationship, and generating a structured information set containing complete space-time dimension information; according to the invention, high-precision intelligent surveying and mapping from static modeling to dynamic spatio-temporal knowledge generation is realized.

Methods are provided for the automated detection, characterization, and selection of micro-objects in a microfluidic device. In addition, methods are provided for grouping detected micro-objects into subgroups that share the same characteristics and, optionally, repositioning micro-objects in a selected sub-population within the microfluidic device. For example, micro-objects in a selected sub-population can be moved into sequestration pens. The methods also provide for visual displays of the micro-object characteristics, such as two- or three-dimensional graphs, and for user-based definition and / or selection of sub-populations of the detected micro-objects. In addition, non-transitory computer-readable medium in which a program is stored and systems for carrying out any of the disclosed methods are provided.

The present application provides a control parameter adjustment method based on the stability domain of a multi-grid-connected inverter system, including: obtaining a first proportional coefficient and a first current reference value of a current controller of a single-grid-connected inverter; obtaining an effective grid impedance matrix of the multi-grid-connected inverter system; determining a single-condition multi-grid-connected inverter system loop gain matrix eigenvalue Bode diagram corresponding to a single-grid-connected inverter based on the first proportional coefficient and the first current reference value, and the effective grid impedance matrix of the multi-grid-connected inverter system; determining a single-condition multi-grid-connected inverter system stability domain three-dimensional point based on the single-condition multi-grid-connected inverter system loop gain matrix eigenvalue Bode diagram; determining a multi-condition multi-grid-connected inverter system stability domain three-dimensional diagram corresponding to a single-grid-connected inverter based on the single-condition multi-grid-connected inverter system stability domain three-dimensional point; adjusting the first proportional coefficient and the first current reference value based on the multi-condition multi-grid-connected inverter system stability domain three-dimensional diagram. The adjustment process is simple to operate and easy to implement.