28 results about "Hausdorff distance" patented technology

The invention relates to the technical field of bolt length detection data processing, in particular to a bolt length detection system, which is characterized in that a three-dimensional data acquisition module generates a high-density point cloud and extracts a thread curvature extreme point, and a dynamic model matching module screens an optimal lead angle parameter based on a Hausdorff distance; and constructing an axial expansion model carrying phase offset gradient features. The projection mapping correction module adopts a genetic algorithm to optimize a compensation coefficient matrix, and generates a dynamic weight correction parameter to suppress geometric distortion; and the phase error correction module combines Fourier spectrum decomposition and an exponential decay weight coefficient to construct a frequency domain transfer function to eliminate an axial accumulative error. According to the method, the problems of projection distortion and phase deviation caused by the lead angle are effectively solved through geometric-phase double-domain correction, dynamic parameter iteration and an error collaborative suppression mechanism, and the spatial positioning precision of the feature points at the tail end of the thread is improved.

The invention discloses a ship trajectory clustering method, which comprises the following steps of: cleaning AIS data to obtain a plurality of navigation trajectories of a ship in a set time period; the Hausdorff distance between any two navigation tracks is calculated to serve as the calculation basis of a DBSCAN algorithm; a core point prediction model is constructed, high-probability data points in the navigation trajectory are screened out to serve as candidate core points, and neighborhood query and clustering expansion are performed on the candidate core points through a DBSCAN algorithm; a Bayesian optimization algorithm is improved through an adaptive acquisition function, and hyper-parameters of a DBSCAN algorithm are optimized based on the improved Bayesian optimization algorithm. The DBSCAN algorithm has the beneficial effects that the DBSCAN algorithm is improved aiming at the problem of relatively low operation efficiency of the density clustering algorithm under the condition of large data volume, and the operation efficiency of the algorithm is improved while the calculation precision is ensured. The Bayesian optimization algorithm is introduced to automatically optimize hyper-parameters of the DBSCAN algorithm, and the effect and stability of clustering analysis are improved.

The invention relates to the technical field of image processing, in particular to a numerical control machining multi-part positioning method and system based on image processing, and the method comprises the steps: obtaining an image containing a to-be-machined part, extracting an initial edge point, calculating the edge gray transition compactness of the initial edge point, and calculating the edge gray transition compactness of the initial edge point; the quantization module is used for quantizing the concentration degree of edge point gray change; candidate points are obtained through screening based on the edge gray transition compactness, and local curve segments are constructed; and calculating the geometric trajectory smoothness of the candidate points. According to the method, two indexes of edge gray transition compactness and geometric trajectory smoothness are constructed to quantify and distinguish a real workpiece contour and noise interference. Furthermore, a self-adaptive weighted Hausdorff distance matching algorithm is constructed based on the indexes, the sensitivity to abnormal points can be dynamically adjusted, and the positioning precision and reliability in a severe industrial environment are remarkably improved.

The invention relates to the technical field of natural language processing, in particular to an event extraction method based on entity representation and side information enhancement. The method comprises the following steps: fusing part-of-speech information, sequence information and an attention mechanism guided by an entity type through an entity representation enhancement module to optimize entity recognition, and solving sample imbalance and label transfer constraints by adopting a weighted cross entropy loss function; constructing a document graph comprising pseudo event nodes, entity nodes and context nodes, modeling a node relationship through three types of directed edges, and initializing edge feature vector explicit coding semantics; aggregating global information by using a graph attention mechanism, and dynamically integrating cross-sentence event elements through pseudo event nodes; the event decoding module adopts a Hausdorff distance loss function to measure the difference between a prediction event set and a real event set, and event type classification and argument role allocation are achieved. According to the method, the F1 value on a financial announcement data set reaches 83.9%, and the problem that document-level event elements are dispersed is effectively solved.

This invention discloses a fast e-commerce information retrieval method based on deep learning, comprising: acquiring an e-commerce product information database to obtain a set of product semantic fragments; constructing and training an improved Triplet network; collecting e-commerce search query text to generate a set of query semantic fragments; performing vectorization encoding to form a product vector set library; performing vector aggregation processing to obtain query and product representative vectors; performing vector similarity calculation to select a preset number of candidate products; executing the Hausdorff distance algorithm to output a preset number of products as the retrieval results. This invention, by introducing an improved Triplet network and the Hausdorff distance algorithm, achieves fast candidate filtering and high-precision retrieval of query and product information composed of multiple semantic fragments in e-commerce scenarios, while also meeting key attribute consistency constraints.

This invention discloses a triangular mesh coarsening method for broadband electromagnetic scattering analysis, belonging to the field of electromagnetic computation. The method first identifies the characteristic edges, characteristic edge points, and corner points of the mesh, and constructs normal or tangent vectors at the nodes according to the mesh node type. Then, a local Bezier surface is constructed, and local operations are performed on the mesh edges to ensure that the mesh and the local Bezier surface satisfy the Hausdorff distance constraint. Next, a target size field is constructed and smoothed based on curvature estimation and the Hausdorff distance constraint. Finally, guided by the size field, coarsening iterations are performed through edge folding operations, and mesh quality is optimized through edge swapping and vertex movement. This invention reduces the mesh size while quantitatively controlling geometric errors and accurately preserving geometric features, thus improving simulation efficiency and reliability.

The application discloses a kind of ruled surface wire cutting rough machining path generation and sequencing method, it is related to subtractive manufacturing and numerical control machining automatic path planning technical field.The specific includes: based on differential evolution algorithm to find viewpoint, it is evaluated using comprehensive objective function including volume item, uniformity item, barycenter offset item and overhang constraint term;Along the direction of view point, extract projection profile and utilize cubic B-spline curve to approach, according to Hausdorff distance to compensate offset to eliminate collision interference to generate path;Iterative execution until meeting preset termination condition obtains path set;Each path is modeled as three-node model including entry, internal and exit node, is converted into traveling salesman problem and uses safe sphere to establish weight between paths, determines optimal cutting order.The purpose is to solve the problem of uneven distribution of excess amount, poor machining stability and long idle time in wire cutting rough machining, realize efficient, stable and automated processing.

The application discloses a kind of optimal envelope trajectory tracking control methods of space non-cooperative target under multi-target constraint, mainly include the following steps: design the full-drive multi-finger space capture configuration with adaptive configuration adjustment and anti-escape capability, generate effective multi-finger envelope configuration using bidirectional Hausdorff distance based on finger feature and target edge point feature, and construct multi-finger dynamic capture domain according to target motion characteristics and joint feature length;Desired trajectory parameterization is carried out using continuous high-order Bezier curve, and smooth envelope trajectory is planned under minimum base disturbance based on multi-target constraint and multi-modal particle collaborative learning mechanism;Through the nonlinear coupling characteristics of inverse dynamics compensation system of multi-finger, design multi-finger collaborative hierarchical tubular model predictive control strategy based on disturbance observer to realize envelope trajectory tracking control.The method can effectively overcome the interference caused by target shape complexity, motion uncertainty, nonlinear dynamic coupling, realize the accurate tracking control of space non-cooperative target trajectory.

The application relates to the technical field of image intelligent analysis, and specifically discloses a feature extraction method and system based on deep learning and imageomics, which comprises the following steps: through calculating the overlap rate of deep learning and imageomics ROI boundaries and the absolute difference of Z-score standardization of GLCM-entropy, double determination and accurate identification of ROI boundary double inconsistency are realized; based on a spatial attention mechanism, a pixel weight distribution model is constructed in combination with texture abnormality, abnormal weight elimination, smoothing normalization processing and adaptive filtering of pseudo boundaries are carried out, a unified coordinate system with the imageomics boundary center as the origin is re-constructed, image standardization is realized by minimizing and optimizing affine transformation parameters through the Hausdorff distance, finally, a three-order Bezier curve is used to fit the dislocation area and iterative smoothing correction is carried out, high-precision unified ROI boundaries are established, image correction and efficient fusion of heterogeneous features are realized, and the effectiveness of coupled feature representation is improved.

The application provides a layout fuzzy matching method and device based on Hausdorff distance, a medium, a program product and a terminal. The first layout and the second layout to be executed for fuzzy matching are obtained, and a preprocessing operation is performed on the coordinate point sets in the layouts respectively. The Hausdorff distance calculation operation is performed on the first coordinate point set and the second coordinate point set after the preprocessing operation, and the maximum Hausdorff distance is obtained based on the calculation result. Whether the first layout and the second layout are consistent is determined by judging whether the maximum Hausdorff distance is less than or equal to a preset threshold. The application solves the problem that the existing layout fuzzy matching method has long operation time and low efficiency when processing large-scale layouts. The efficiency and accuracy of layout fuzzy matching are significantly improved.

The application discloses a ship trajectory clustering method, comprising the following steps: cleaning AIS data to obtain the sailing trajectories of a plurality of ships in a set time period; calculating the Hausdorff distance between any two sailing trajectories as the basis for calculation of a DBSCAN algorithm; constructing a core point prediction model and screening high-probability data points in the sailing trajectories as candidate core points; performing neighborhood query on the candidate core points and carrying out clustering expansion through the DBSCAN algorithm; improving a Bayesian optimization algorithm through an adaptive acquisition function, and optimizing the hyperparameters of the DBSCAN algorithm based on the improved Bayesian optimization algorithm. The application has the beneficial effects that: in view of the problem that the operation efficiency of the density clustering algorithm is relatively low in the case of a large amount of data, the DBSCAN algorithm is improved, the operation efficiency of the algorithm is improved while the calculation accuracy is ensured, the Bayesian optimization algorithm is introduced to automatically optimize the hyperparameters of the DBSCAN algorithm, and the effect and stability of the clustering analysis are improved.

The invention discloses a ruled surface linear cutting rough machining path generating and sorting method, and relates to the technical field of subtractive manufacturing and numerical control machining automatic path planning. The method specifically comprises the following steps: searching a viewpoint based on a differential evolution algorithm, and evaluating by using a comprehensive objective function comprising a volume item, a uniformity item, a gravity center shift item and a suspension constraint item; a projection contour is extracted in the viewpoint direction, approximation is carried out through a cubic B-spline curve, and offset compensation is carried out according to the Hausdorff distance to eliminate collision interference to generate a path; iteratively executing until a preset termination condition is met to obtain a path set; each path is modeled into a three-node model containing an entrance node, an internal node and an exit node, the three-node model is converted into a traveling salesman problem, a safety spherical surface is used for establishing weights between the paths, and the optimal cutting sequence is determined. The method aims at solving the problems of non-uniform allowance distribution, poor machining stability and long idle feed time in linear cutting rough machining, and efficient and stable automatic machining is achieved.

The application provides a Bloom filter configuration method for a hash connection, comprising: sampling initial data, analyzing the initial data, dynamically analyzing a variety of change trends, fitting a change trend model, constructing a Bloom filter, evaluating a Bloom filter size, and adjusting a Bloom filter configuration. The application combines probability statistics and mathematical modeling to dynamically analyze part of data sets and estimate code value inclination, uses a change slope and a coefficient of variation to judge a stable trend of data, uses Hausdorff Distance to select an optimal model to estimate a Bloom filter, finally proposes different configuration Bloom filter strategies, efficiently configures a Bloom filter size, fully utilizes memory resources, and improves overall query efficiency of the hash connection.

This application discloses a method, system, and related devices for flexible load restoration in distribution networks, belonging to the field of power system fault recovery. The method includes: combining a flexible load extreme operation model with distribution network power flow constraints to form the constraints for the distribution network operator; transforming the opportunity constraints in the operator's constraints into deterministic constraints, and then calculating the distribution network's operational safety domain using a vertex search method based on Hausdorff distance; constructing a distribution network load restoration model based on the operational safety domain; solving the distribution network load restoration model based on the operational safety domain; and performing decision optimization at the distribution network level during power restoration based on the solution results. This method performs load restoration while considering the distribution network's operational safety domain, ensuring the safety and robustness of the power grid restoration process, and ultimately helping the distribution network operator make informed decisions.

The present invention discloses a multi-endpoint star map recognition method based on an optimal path. The method comprises the following steps: S1. constructing a navigation star library and, based on the concept of a minimum weight spanning tree, constructing a navigation feature library containing navigation star characteristic patterns; S2. processing an observed star map and, based on the concept of a minimum weight spanning tree, generating characteristic patterns of observed stars; and S3. matching and identifying the navigation star characteristic patterns with the observed star characteristic patterns based on the bidirectional Hausdorff distance. The present invention integrates graph theory knowledge and the optimal path problem with star map recognition methods, utilizing the concept of a minimum weight spanning tree to extract star point characteristic patterns. Due to the unique distribution of star points, the characteristic pattern of each star point is ensured to be unique, thereby increasing the accuracy of star map recognition.

The present invention discloses a method, system and storage medium for identifying and counting cracks in an image. First, a semantic segmentation algorithm is used to identify crack pixel information, and the crack pixel information is clustered to distinguish each discontinuous crack and remove noise pixels. Then, a judgment is made as to whether two cracks are the same crack, and the judgment criteria include whether the Hausdorff distance between the crack endpoints of the two cracks and the angle between the direction vectors related to the two cracks meet the requirements. Two cracks that are considered to be the same crack are merged, and then iterative calculations are performed again until all cracks cannot be merged into a new crack. Finally, accurate crack count statistics are achieved. The present invention uses the crack direction characteristics to analyze and count cracks, and can classify scattered cracks with regular direction as the same crack. It has good practical value for cracks with obvious direction, unclear texture, and partially obscured areas.

The invention discloses a ship route intelligent identification and standardization processing method based on AIS data. The method comprises the following steps: standardizing a port name through a four-layer progressive framework; identifying a stay point through a stay point identification algorithm, and performing segmentation to generate a single-voyage-number track segment set carrying a leg identifier; extracting starting and ending ports, a time range and quality information of a single voyage number trajectory segment to establish an OD index; after grouping is carried out according to an OD index, HDBSCAN clustering is carried out on grouping information by adopting a direction perception hybrid Hausdorff distance measurement method; and selecting an optimal track from the clustering cluster through multi-dimensional scoring. According to the invention, end-to-end automatic processing from original AIS data to a standardized route mode is realized, a standardized route database covering a global port network is constructed, and reliable technical support is provided for shipping planning, safety management and efficiency optimization.

This invention discloses a method for JRC estimation based on Hausdorff distance. The method involves extracting the coordinates of 10 standard profiles of Barton's structural surfaces with a sampling interval of dx. Based on the extracted x and y coordinate data, the cumulative slope of each standard profile is calculated, forming a cumulative slope data sequence of standard curves. The structural surface curves are then measured in the field, and the coordinates of the measured curves are extracted with a sampling interval of dx. The cumulative slope of the measured curves is calculated, forming a cumulative slope data sequence of measured data. The Hausdorff distance between the cumulative slope of the measured curves and the cumulative slope of the standard curves is calculated. The standard profile of the structural surface most similar to the measured curve is identified, and its corresponding JRC value is assigned to the measured curve, ultimately estimating the JRC value of the measured curve. This invention achieves JRC value estimation based on the self-similarity of the cumulative slope of the curves, avoiding the arbitrariness and subjectivity in determining the JRC value caused by comparing visual observation with standard profiles.

The invention relates to the field of numerical control machining, and particularly discloses an accurate bow height error control method based on Hausdorff distance evaluation, which comprises the following steps: S1, calculating an initial chord length by using an OC method, positioning a bow height error point by using a curve derivative, solving a Hausdorff distance h0, and iteratively adjusting the interpolation step length to meet delta max; s2, performing lofting according to parameters of a construction line to form an extensible straight line curved surface; s3, layering the offset curved surface by means of a horizontal sectioning plane according to a Z value, obtaining boundary track points by an S1 algorithm, and connecting the points to obtain a cutter axis vector to determine a cutter path track; s4, calculating a middle layer processing point by using a vector extension method, and calculating geometric deviation through Euclidean distance; s5, constructing a machine tool multi-coordinate system mapping transfer relation, and introducing a global compensation parameter compensation error; and S6, verifying the validity of the method. According to the technical scheme provided by the invention, the problems of approximate evaluation, difficulty in adapting to five axes and neglecting of geometric errors of a machine tool in an existing method are solved, the bow height control precision is effectively improved, and the machining precision of complex curved surface parts is improved.

The application discloses a special scene early warning shielding method and device, electronic equipment and a storage medium, and the method comprises the steps of obtaining a fire image to be identified and a special scene reference image; adopting a preset scale invariant feature transformation algorithm to determine matching feature points between the fire image to be identified and the special scene reference image, and determining a Hausdorff distance between the fire image to be identified and the special scene reference image according to the matching feature points; judging the size relationship between the Hausdorff distance and a preset threshold value; if the Hausdorff distance is smaller than the preset threshold value, it is determined that the fire image to be identified is a special scene image, and a fire early warning shielding program is started. The application solves the technical problem that repeated alarms are frequently received in the prior art under special scenes such as hot work, fire drill, facility maintenance and the like.

According to the GIS equipment deformation detection method based on point cloud registration, a lightweight hardware architecture is adopted, a high-precision three-dimensional imaging system and an embedded processing unit are integrated, and point cloud data acquisition, multi-stage registration, deformation analysis and risk early warning are realized in combination with a software system. According to the method, a curvature constraint-based multi-stage point cloud registration algorithm is provided, and the registration precision is improved through adjustable farthest point sampling, maximum clique preliminary registration and curvature feature constraint fine registration; an innovative improved point cloud comparison method is combined with octree search and a local Hausdorff distance to realize accurate deformation detection. The problems that a traditional monitoring method is low in precision, poor in efficiency and insufficient in portability are solved, automatic and high-precision deformation monitoring of GIS equipment can be achieved, and guarantee is provided for safe operation of a power grid.

The invention provides a bidding and tendering table structure calibration method and device, relates to the field of information processing, and solves the technical problem of deviation in table calibration precision in the prior art. The method comprises the following steps: acquiring image data of a bidding and tendering table scanning copy; performing image enhancement on the image data to obtain enhanced image data; inputting the enhanced image data into an improved CNN model, and extracting a semantic unit center point; carrying out edge positioning on the enhanced image data by adopting quadratic spline interpolation to obtain a geometric edge coordinate set; taking the semantic unit center point as a reference, searching geometric edge points in the corresponding geometric edge coordinate set in a preset radius neighborhood, and calibrating the semantic center point and the geometric edge points by adopting a Hausdorff distance minimization algorithm to obtain a calibrated table geometric edge point set; and establishing a uniform page space reference system through the binding hole sites, and aligning and splicing the cross-page tables into the same table. The method and the device are used in a bidding table structure calibration process.

The invention discloses a flight body attitude angle multi-index fusion identification method based on net target data, and the method comprises the steps: firstly obtaining a real coordinate point set of a net target broken hole contour and a flight body rotation projection contour under a rectangular coordinate system, and extracting a polar coordinate point set from the real coordinate point set; and then, according to the coordinate point sets, calculating a Pearson correlation coefficient, a Hausdorff distance, a PCA principal component axis included angle and a principal component axis length difference, and determining an optimal attitude angle of the flight body through similarity analysis. Besides, the mesh target broken hole contour, the optimal attitude angle and the projection contour of the adjacent attitude angle are displayed in the polar coordinate system, and the principal component axes of the mesh target broken hole contour and the projection contour of the optimal attitude angle are drawn to form a visual graph. According to the method, by means of multi-index fusion, the attitude angle of the flight body can be accurately identified, and powerful technical support is provided for accurate analysis and research of the flight state of the flight body.

The present invention proposes a method for detecting arc faults in series on low-voltage distribution lines based on a waveform similarity algorithm. First, arc fault tests and fault feature analysis are performed on common loads, and the voltage sag threshold for starting arc fault detection and the H threshold for identifying arc faults are given. Secondly, based on the voltage sag characteristics at the load end when an arc fault occurs, the load end voltage sag value exceeding the voltage sag threshold is used as the detection start condition. Then, the similarity of the load end voltage waveform is calculated based on the Hausdorff distance algorithm. When the Hausdorff distance H value between the load end voltage and the sine wave exceeds the H threshold, it is determined that an arc fault has occurred. Finally, the recognition effect of the detection method proposed by the present invention is verified through examples. The results show that this method can effectively improve the reliability of arc fault detection.

The invention discloses a man-machine cooperation method and system for a multi-dimensional intelligent interaction pen, and mainly relates to the technical field of man-machine interaction cooperation. Comprising the following steps: synchronously collecting user interaction information through a visual channel, a voice channel and a sensor channel; calculating the matching degree of the tangent plane and the to-be-selected plane by using the bidirectional Hausdorff distance and the normal vector included angle; selecting the intention with the maximum probability of each channel as a candidate intention, and if the intentions of the channels are consistent, calculating a channel expected value by using information entropy and performing linear weighted fusion; if the intentions conflict, prompting the user to input again; and generating a corresponding operation prompt or navigation type selection guide. The method has the beneficial effects that the problems of time waste and low efficiency caused by repeated selection are effectively reduced, the reliability of the system is improved, and a better method and technical support are provided for classroom geometry teaching.

The application discloses a CUSUM-RHD-based artillery recoil mechanism state evaluation method, and belongs to the technical field of artillery recoil mechanism state evaluation. The method comprises the following steps: analyzing and extracting a fault characteristic data signal; performing normalization processing on the fault characteristic data, so as to eliminate the influence between dimensions; constructing a relative Hausdorff distance calculation model to calculate the Hausdorff distance between two adjacent shootings of the artillery; constructing a cumulative sum relative Hausdorff distance calculation model to calculate the cumulative sum relative Hausdorff distance, and defining the cumulative sum relative Hausdorff distance as a health factor for evaluating the state of the artillery recoil mechanism; and finally, performing state evaluation on the artillery recoil mechanism according to the health factor index. The state evaluation method has good evaluation accuracy, robustness and anti-interference ability. The application also has the advantage that the state of the artillery recoil mechanism can be evaluated without obtaining the full life cycle data.

The application discloses a chip pin recognition method for an SMT chip mounter. The method is characterized in that, through the discrimination mode of Hu invariant moments and Hausdorff distance difference, the similarity of similar contours is mutually corrected, then according to the characteristics that the shapes and sizes of the same type of pins in a chip are all the same, all pin types and corresponding quantities contained in the chip are accurately recognized, subsequent chip packaging recognition and chip measurement are facilitated, the pins are one of important standards for judging the integrity of the chip, and the pin recognition is helpful to finding defects of the chip at the first time, reduces the defective rate in the whole process, and improves the overall mounting efficiency of the SMT chip mounter.

The application discloses a complex curved surface robot track generation method and device based on streamline field reconstruction and geodesic line offset, and comprises the following steps: S1: obtaining three-dimensional point cloud data of a target complex curved surface part, extracting minimum principal curvatures and principal directions of any point, and establishing an optimal feed direction field of the curved surface; S2: reconstructing a discrete optimal feed vector field into a continuous vector field, solving a streamline equation through numerical integration, and performing topological reconstruction to generate a structured two-dimensional streamline field on the curved surface; S3: calculating average Hausdorff distances of each streamline in the two-dimensional streamline field, and screening out a starting path line; S4: mapping the starting path line to a curved surface parameter domain, constructing a Riemann metric with internalized relative curvature, and expanding geodesic line integration along the orthogonal direction of the Riemann metric in the parameter domain to generate an offset path point set; and S5: reconstructing the parameter domain offset path point set to a three-dimensional physical space, performing path self-intersection truncation and continuity filtering processing, and obtaining a final robot motion track.