32 results about "Vertex number" patented technology

The invention discloses a polygonal and quadrilateral mesh automatic subdivision method based on deep reinforcement learning, relates to the field of computational geometry and mesh generation, and constructs an automatic subdivision framework fusing geometric priori knowledge and a data driving strategy. According to the method, nine basic topology filling templates covering triangles to hexagons are predefined as discrete action spaces, and continuous geometric segmentation is converted into a sequence decision problem; learning a mapping relation between the polygon state characteristics and the optimal template selection strategy by using a deep Q network, and balancing exploration and utilization through a dynamic epsilon-greedy mechanism; and in combination with a vertex number priority scheduling strategy and a multi-dimensional quality award function, guiding an intelligent agent to adaptively generate a high-quality quadrilateral grid. According to the method, full-automatic and high-robustness subdivision of the complex polygon area is achieved, the grid orthogonality and the length-width ratio quality are remarkably improved, manual intervention is avoided, and the method is suitable for engineering scenes such as finite element analysis.

The invention discloses a quantum-classical collaborative wireless link scheduling optimization method based on a divide-and-conquer QUBO model and inverse non-adiabatic driving, and belongs to the technical field of quantum computing and wireless communication. According to the method, link interference in wireless communication is modeled into a conflict graph, namely, vertexes represent links, interference represents edges, utility functions on the links represent weights of the vertexes (numbers on the left of the vertexes are numbers of the vertexes, and numbers on the right of the vertexes are weights of the vertexes), and optimal wireless link scheduling is a weighted maximum independent set (WMIS) on the conflict graph. According to the method, a divide-and-conquer QUBO model is provided, the whole space is divided into Dicke state subspaces with different Hamming weights, XY-Mixer is adopted as a hybrid operator, and evolution of QAOA in the subspaces is limited. On the basis, a DQAOA algorithm is provided; a greedy algorithm and an expanded Lov-alpha-sz positive semidefinite plan are called to obtain a lower bound and an upper bound of a WMIS solution respectively; an anti-non-adiabatic driving item is introduced to modify a QAOA evolution formula, an XY-Mixer angatz is matched to enable the algorithm to be subjected to parallel evolution in a subspace, convergence is accelerated, and an optimal wireless link scheduling scheme is obtained.

The invention provides a layout splicing method. The layout splicing method comprises the following steps: acquiring a list of vertexes and a list of edges of a plurality of slices of a layout; according to the list of the vertexes of the multiple slices, a list of the vertexes of the layout is obtained, and the list of the vertexes of the layout comprises the vertexes of the multiple slices; according to a vertex of a first graph of the first slice, determining a tangency point of the first slice, the first graph being a graph with at least one edge overlapping with at least one boundary of the first slice in the first slice, and the tangency point being a vertex located on the boundary of the first slice in the first graph; according to the tangent points of the multiple slices, a cross-slice edge of the layout is determined, and the cross-slice edge comprises a first tangent point and a second tangent point which are located on a first boundary and a second boundary which are overlapped of the adjacent slices respectively; and determining a list of edges of the layout according to the list of the cross-slice edges and the plurality of slice edges. According to the method, the number of vertexes and the number of edges involved in a scanning line algorithm in the layout splicing process can be reduced, so that the layout splicing efficiency is improved.

The invention discloses a BFS-like algorithm-oriented graph processing system caching method, a controller and a system, and belongs to the technical field of graph processing system performance optimizing.The method comprises the steps that based on the relation between cache page access popularity and the number of unaccessed vertexes in a BFS-like algorithm, more accurate popularity level-to-level management is carried out on cache pages; when the cache is fully loaded, pages with low access potential are effectively eliminated, so that the cache hit rate is increased; fragmented effective edge data are extracted from a cache page and are independently stored in a cache of fine-grained management; the scheduling sequence of the vertexes in the task queue is adjusted by obtaining the proportion of the edge lists of the vertexes in the BFS-like algorithm task queue residing in the cache and combining the attributes such as the out-degree of the vertexes, and the data residing in the cache is utilized to the maximum extent. According to the method, the cache hit rate of the graph processing system when the graph processing system processes the BFS-like algorithm task can be effectively improved, so that the access performance of the graph processing system is improved.

The application discloses an individualized partition method and device based on brain surface geometric features, a medium and a product, and relates to the technical field of neuroimaging. The method comprises the following steps: dividing each vertex into sulcus seed points, gyrus seed points and remaining vertices based on the shape index of each vertex, thereby obtaining a plurality of sulcus seed initial regions and gyrus seed initial regions; merging each connected sulcus seed initial region and each gyrus seed initial region, thereby obtaining a plurality of merged regions; determining each initial region that is not connected as an independent region; determining all vertices in the merged region and the independent region and all remaining vertices that have a number less than a preset number as transition vertices; determining the merged region and the independent region that have a number greater than and / or equal to the preset number as initial inclusion regions; iteratively including each transition vertex, thereby obtaining a personalized brain partition map, and achieving the partition of the brain. The application improves the accuracy of brain region partitioning.

The invention relates to a method and device for eliminating graphic quantization sawteeth in GDI and a medium, and the method comprises the steps: obtaining vertex data of a to-be-processed graphic, and caching the vertex data after affine transformation; constructing an integer straight line according to the slope and intercept of a straight line formed by two adjacent vertexes, and selecting the first vertex and the last vertex to calculate an initial vertex coordinate correction vector; traversing each vertex, circularly correcting the adjacent next vertex coordinate according to a vertex coordinate correction vector calculated according to the previous vertex coordinate, rounding off the corrected vertex coordinate to obtain an integer vertex coordinate, and updating the vertex coordinate correction vector for correcting the next vertex; and if the traversal is completed, writing the integer vertex coordinate value back to the graphic data, and cleaning the cache. Compared with the prior art, the method has the advantages of automatically eliminating the sawtooth deformation of the graph, improving the drawing efficiency and the like.

The application discloses a graph data partitioning method based on a cache mechanism, comprising the following steps: obtaining graph data, obtaining the total number of graph vertices, the neighbor list of each vertex, the initial vertex partition set and the initial partition number according to the graph data; calculating the upper limit of the load; calculating the correlation score of the vertex in each vertex set which does not reach the upper limit of the load according to the vertex and the neighbor list of the vertex; judging whether the vertex meets the cache condition, if yes, partitioning according to the correlation score; if not, the vertex is partitioned into the cache module, when the cache module reaches the maximum capacity limit, the cache module returns the vertex and the neighbor list which are most suitable for the current partitioning, and the process returns; judging whether all vertices have been partitioned, if yes, the final graph data partition set is obtained; if not, the process returns. The application improves the partitioning precision of the Fennel algorithm under the condition that the size of the graph data is too large.

The invention discloses a dynamic modeling method and system for a three-dimensional model, and the method comprises the steps: recognizing an interactive operation, and obtaining coordinate point data in a three-dimensional scene in real time according to the interactive operation, so as to complete vertex assignment and form a vertex list; calculating a geometric center point of the vertex list based on the vertex list; connecting the vertexes in the vertex list with the geometric center point in a clockwise sequence to generate a planar triangular surface index array, and forming an initial plane; copying a vertex list of the initial plane and offsetting a target numerical value along a specified direction to generate a target plane; and connecting the vertex of the initial plane and the vertex of the target plane in sequence to generate a side triangular surface so as to complete modeling of the three-dimensional model. According to the method, the user interaction track is directly converted into the vertex data and the geometric calculation logic, so that the user can independently complete the whole-process modeling from plane to three-dimensional without relying on a modeler, the Unity scene development efficiency is remarkably improved, and a low-cost and high-flexibility solution is provided for interactive three-dimensional application.

Provided are a distributed parallel computing based graph computing method, a distributed parallel computing system and a computer readable medium. A graph computing method comprises: obtaining data of a graph to be computed, the graph comprising a plurality of vertices and edges; storing the graph according to a compressed sparse row format, and storing the graph in a sparse matrix form, wherein all adjacent edges having a same vertex are continuously stored, and an offset array is used to support an index function thereof; and for subgraphs in which the degrees of both source vertices and target vertices are greater than a predetermined threshold, in forward graphs, performing segmentation according to target vertices, i.e., the column of a matrix, and in reverse graphs, performing segmentation according to source vertices, i.e., the row of the matrix, and further dividing the subgraph into a plurality of segmented subgraph (SSG) components, so that a target vertex in each SSG is limited within a preset range. According to the SSG method of the embodiment for a high-degree vertex, the conventional problem that the space-time locality of accessing data of an adjacent vertex is poor due to a large vertex range of a single large graph is avoided or relieved.

The invention discloses a semi-supervised segmentation method based on graph prototype learning, and the method comprises the steps: collecting a data set, carrying out the preprocessing of the data set, carrying out the mapping of a pixel space to a graph semantic space for the bottom features of an encoder, carrying out the multi-stage graph convolution compression of the number of vertexes, and carrying out the alignment to a labeled image category prototype; sending an unlabeled image into the segmentation network to obtain a category prototype of a pseudo label, and aligning the centroid of the most similar subclass after the category prototype of the unlabeled image is subjected to self-clustering with the category prototype of the labeled image; fusing the structure information of the image with the label and the style information of the image without the label to obtain a composite image; screening prediction results of a non-label image and a plurality of weak disturbance images through a voting strategy, determining reliable and fuzzy pseudo labels, and optimizing a segmentation model and category prototype sampling; and updating network parameters through training to obtain a final segmentation network. According to the method, accurate segmentation can be realized in scenes of scarcity of high-quality labeled data, complex structure and shape of a target and the like.

The present disclosure relates to a method, apparatus, device and medium for identifying characteristic regions of a vehicle model file. The method comprises: obtaining geometric information of each triangular facet in the vehicle model file; numbering the vertices of each triangular facet based on vertex coordinates to obtain three vertex numbers corresponding to each triangular facet, with the same vertex coordinates corresponding to the same vertex number; determining the shared edges between each triangular facet and adjacent triangular facets and the first characteristic edge of the vehicle model file based on the three vertex numbers corresponding to each triangular facet; identifying the shared edges that do not meet preset requirements as second characteristic edges; determining the characteristic region to which each triangular facet belongs based on the first characteristic edge and the second characteristic edge, with the characteristic region being a closed figure formed by connecting multiple first characteristic edges and / or multiple second characteristic edges end to end. When identifying characteristic regions, the present disclosure does not need to calculate the curvature of the surface at the vertex, which greatly saves computational effort and improves computational efficiency.

The invention relates to route planning and optimization. In some embodiments, the invention includes obtaining vertex data describing target attributes, including at least one target location, and process dynamics data describing system constraints of a process: defining vertex functionals, describing attribute requirements, and edge functionals, which use the system constraints to determine cost requirements, for cost objectives; and using the data, the functionals, and the cost objectives to construct a T-graph that includes a label space representing the target attributes. Next, the T-graph is solved to construct a label space trajectory by determining waypoints such that the process (1) travels through all target locations and (2) satisfies the attribute requirements, dynamically calculating travel cost by applying the cost requirements to each intervening edge, and minimizing the travel cost according to the cost objectives. The optimal space trajectory is executed to navigate the process through the target locations.

This invention discloses a maximal biclique enumeration method based on hybrid storage. It obtains a bipartite graph G(U,V,E), where U and V are two disjoint vertex sets and E is an edge set. A threshold t is set to determine the storage method of the subgraph during runtime. If the number of vertices in U is greater than t, G0 is stored using an adjacency list; otherwise, G0 is stored using a bitmap. The BicliqueFind(L,R,C,G) function is recursively called with U, V, and G0 as initial parameters. The count results of all maximal bicliques are output to the user. This invention employs a hybrid storage method, retaining the low storage overhead of adjacency list storage while combining the computational efficiency of bitmap storage. For tasks in biclique enumeration that require calculations only on small graphs, this invention significantly improves the execution speed of the biclique enumeration task by dynamically constructing sub-bitmaps.

The application discloses a kind of polygon quadrilateral grid automatic subdivision methods based on deep reinforcement learning, it is related to the field of computational geometry and grid generation, the application constructs a kind of automatic subdivision framework of fusion geometry priori knowledge and data-driven strategy.The method predefines 9 kinds of basic topological filling templates covering triangle to hexagon as discrete action space, converts continuous geometry segmentation into sequence decision problem;The mapping relationship between polygon state characteristics and optimal template selection strategy is learned using deep Q network, and exploration and utilization are balanced through dynamic epsilon-greedy mechanism;Combining vertex number priority scheduling strategy and multidimensional quality reward function, guide agent to adaptively generate high-quality quadrilateral grid.The application realizes the full-automatic, high robustness subdivision of complex polygon region, significantly improves the grid orthogonality and aspect ratio quality, avoids manual intervention, and is suitable for finite element analysis and other engineering scenarios.

The feature preserving surface reconstruction method based on optimal transport involves three-dimensional geometric processing. 1) input the three-dimensional point cloud model, construct the convex hull of the point cloud and re-mesh as the initial mesh; 2) sampling on the initial mesh, calculating the optimal transport plan between the point cloud and the sampling points according to the transport cost function; 3) calculating the transformation matrix between the sampling points of the triangular face and the point cloud corresponding to the transport, calculating the new position of the triangular mesh vertex according to the transformation matrix, and moving each vertex to the new position to obtain the initial fitting mesh; 4) point relocation, edge flipping and edge collapse operations are performed on the initial fitting mesh to reduce the optimal transport cost of the point cloud and the mesh, until the number of reconstructed mesh vertices reaches the target vertex number. The triangular mesh with sharp edges and sharp point features is obtained. By using the optimal transport theory, the feature preserving result can be reconstructed with less number of faces, and it is robust in the case of noisy and missing point cloud data.

The invention discloses an individualized partitioning method and device based on brain surface geometric features, a medium and a product, and relates to the technical field of neuroimagines.The method comprises the steps that all vertexes are divided into brain sulcus seed points, brain gyrus seed points and remaining vertexes based on shape indexes of all the vertexes, a plurality of cerebral sulcus seed initial areas and cerebral gyrus seed initial areas are obtained; respectively merging the communicated brain sulcus seed initial regions and brain gyrus seed initial regions to obtain a plurality of merged regions, and determining the non-communicated initial regions as independent regions; and determining all the vertexes and all the remaining vertexes in the merged region and the independent region of which the number of the vertexes is smaller than a preset number as transition vertexes. Determining the merging areas and the independent areas with the vertex number greater than and / or equal to the preset number as initial inclusion areas; and iteratively incorporating the transition vertexes to obtain a brain personalized partition map so as to realize the partition of the brain. According to the invention, the accuracy of brain region partitioning is improved.

To effectively reduce the number of apexes of a mesh of an object.SOLUTION: An information processing system simplifies a plurality of apexes to each of which at least one kind of material is set, which are apexes constituting a mesh defined in a virtual space, and draws a mesh based on the apexes in which simplification is reflected, on the basis of drawing settings based on a material of each apex. The simplification is achieved when a plurality of apexes of an apex group are replaced by one apex to which a total number of kinds of materials are set when a simplification condition at least including a fact that a total number of kinds of materials of each apex included in the apex group is a first number or less is satisfied for each of a plurality of apex groups including a plurality of adjacent apexes respectively.SELECTED DRAWING: Figure 19

The invention provides a group search method and device based on maximum group search on an uncertain graph, and relates to the field of data processing, and the method comprises the steps: obtaining an initial graph corresponding to a to-be-processed social network; determining a reference value of each vertex in the initial image; deleting vertexes of which the corresponding reference values are not greater than the heuristic solution values in the initial image to obtain a vertex set corresponding to the heuristic solution values, and determining a middle sub-image based on the vertex set; all the vertexes in the middle sub-graph are traversed to execute multiple search operations, a target sub-graph with the maximum number of the vertexes is determined based on candidate sub-graphs obtained through the search operations, an edge exists between any two different vertexes in the target sub-graph, and the product of the existence probabilities of all the edges is larger than a preset probability value; and determining a target social user group in the to-be-processed social network based on the target sub-graph. According to the method, the social user group can be searched based on the uncertain associated data between the social users.

The present disclosure relates to an induction range calibration method, device, ceiling appliance, equipment and storage medium. The induction range calibration method determines the standing position of the target object as the vertex of the required calibration area, obtains the position of the vertex and determines the coordinates of the horizontal plane projection of the point. When the number of vertices obtained is equal to 2, the rectangle surrounded by the straight line where the horizontal coordinates of the two vertices are located and the straight line where the vertical coordinates are located is taken as the induction working range or the induction non-working range. When the number of vertices obtained is greater than or equal to 3, the polygon surrounded by connecting all the vertices in turn is taken as the induction working range or the induction non-working range. In this way, the range that needs to be calibrated can be determined, and the user can be prevented from accidentally triggering the induction device, thereby causing resource waste. At the same time, this method is simple and does not require manual measurement and calculation, thereby improving the user experience.

The invention provides an incremental calculation optimization method for dynamic graph point pair analysis. The method comprises the following steps: executing edge adding and edge deleting operations through a preset hardware accelerator; the hardware accelerator comprises a prefetching module, an identification module, a scheduling module and a propagation module, and adopts an assembly line technology to process multi-batch dynamic changes in parallel. During edge adding operation, whether a source point can reach an edge adding starting point or not is judged, only edge topology changes are recorded if the source point cannot reach the edge adding starting point, and state calculation is not conducted; if yes, recording the topology change and updating the reachable vertex state of the edge-adding end point topology; during edge deletion operation, judging whether the edge deletion end point state depends on the edge deletion starting point state, if not, only recording edge deletion, and not triggering state update; and if yes, recording the change of the edge topology, and updating the edge deletion end point topology to reach a vertex state. The invention further provides a corresponding hardware accelerator. Therefore, the number of activated (traversed) vertexes can be effectively reduced, so that the calculation overhead is reduced to a great extent; and the processing efficiency can be further improved based on the preset hardware accelerator.

The invention discloses a method and a device for checking legality of vertex matching relations among sections. The method comprises the following steps: analyzing multiple groups of vertex matching relations among multiple sections from a modeling instruction; constructing a vertex matching table based on multiple groups of vertex matching relationships; on the basis of each column in the vertex matching table, generating a corresponding vertex sequence column representing the use sequence of all vertex numbers of the section for each section so as to form a vertex sequence table; respectively forming a corresponding two-dimensional coordinate for each vertex number in the vertex matching table according to the row number and the column number of each vertex number in the vertex sequence table in the vertex matching table; based on the formed two-dimensional coordinates, respectively constructing corresponding edges for each group of vertex matching relationships, and judging the legality of the multiple groups of vertex matching relationships by detecting whether the constructed edges are crossed or not; according to the method, legality verification can be rapidly and accurately carried out on the vertex matching relation between the sections before the lofting model is constructed.

The invention relates to the field of connectivity and the technical field of network design, and discloses an algorithm for constructing a support tree of a connected graph. Comprising the steps that a connected graph G is acquired, the number of vertexes of the connected graph G is n, and the maximum degree is delta; for a vertex u of G, recording a vertex set adjacent to u as N (u), and letting N [u] = N (u) U {u}; the number of the vertexes in N (u) is called the degree of u, and the maximum value of the degrees of all the vertexes in G is called the maximum degree of G; a vertex subset S = {v1, v2,..., vk} of the connected graph G is obtained, so that for any vertex vi (i > = 2) in the vertex subset S, N (vi) nN (Si-1) < = 1 exists, and Si-1 = {v1, v2,..., vi-1}; calculating the number of vertexes # imgabs0 # contained in the vertex set S, using a breadth-first algorithm to obtain a support tree T of a connected graph G, and constructing another support tree T'of the connected graph G from T by using the transformation of the support tree, so that each vertex in the S is a vertex with consistent degree; the method has the advantage that degree consistent vertexes of T are as many as possible.

To provide a mesh decoding device, a mesh decoding method, and a program which decode a basic mesh or a displacement when the number of vertices is different between a current frame or a current submesh and a reference frame or a reference submesh.SOLUTION: In a mesh decoding device 200, an inter-decoding section 202E decodes the number of motion vectors of a current frame or a current submesh from a bitstream, and adjusts the number of vertices and a part of vertex coordinates in the current frame or the current submesh when the decoded number of the motion vectors is different from the number of vertices of a reference frame or a reference submesh.SELECTED DRAWING: Figure 7

The application provides a dynamic graph point pair analysis incremental calculation optimization method, which performs edge adding and edge deleting operations through a preset hardware accelerator; the hardware accelerator contains pre-fetching, identification and scheduling, and propagation modules, adopts a pipeline technology to process multiple batches of dynamic changes in parallel; when the edge adding operation is performed, whether the source point is reachable to the edge adding starting point is judged, the edge topology change is recorded only if the source point is not reachable, and no state calculation is performed; the topology change is recorded and the edge adding ending point topology reachable vertex state is updated if the source point is reachable; when the edge deleting operation is performed, whether the edge deleting ending point state depends on the edge deleting starting point state is judged, the edge is deleted only if the edge deleting ending point state does not depend on the edge deleting starting point state, and the state update is not triggered; the edge topology change is recorded and the edge deleting ending point topology reachable vertex state is updated if the edge deleting ending point state depends on the edge deleting starting point state. The application also provides a corresponding hardware accelerator. Therefore, the application can effectively reduce the number of activated (traversed) vertices, thereby greatly reducing the calculation cost; and the preset hardware accelerator can further improve the processing efficiency.

The invention provides a pixelated digital core tetrahedral mesh generation preprocessing method and device, and belongs to the technical field of digital image processing, and the method comprises the steps: constructing a list containing all pixel mesh vertex coordinates of a digital core; determining boundary surfaces of the digital core, and continuously numbering vertexes of the boundary surfaces in the list to obtain a new list; the boundary surface is a quadrilateral unit surface; splitting the boundary surface into two triangular units, and storing vertex numbers corresponding to the two triangular units into a triangular unit list based on the new list; determining adjacent vertexes of the numbered vertexes in the new list, and performing coordinate adjustment on the numbered vertexes by using the adjacent vertexes to obtain new coordinates of the numbered vertexes; and adjusting the new list based on the new coordinates of the numbered vertexes to obtain a target list, and obtaining a preprocessing result based on the target list and the corresponding triangular unit list. According to the invention, the purpose of preprocessing the digital core to obtain effective information of digital core numerical simulation can be achieved.

According to one aspect of the present disclosure, a method of decoding by a decoder is provided. For each hierarchical subdivision level of a plurality of hierarchical subdivision levels, the following operations may be performed. The method may include decoding a first syntax element to determine a vertex count associated with a hierarchical subdivision level. The method may include decoding a second syntax element to determine whether the hierarchical subdivision level is subdivided into subblocks. The method may include, in response to the second syntax element indicating the hierarchical subdivision level is subdivided into subblocks, decoding a third syntax element to determine a number of subblocks associated with the hierarchical subdivision level, determining a number of vertices per subblock based on the vertex count and the number of subblocks, and decoding the hierarchical subdivision level based on the number of vertices per subblock.

The application discloses a graph processing system cache method, a controller and a system for a BFS algorithm, belongs to the technical field of performance optimization of a graph processing system, and comprises the following steps: based on the relationship between the access heat of a cache page and the number of unvisited vertices in the BFS algorithm, more accurate heat grading management is implemented on the cache page, when the cache is full, the page with low access potential is effectively eliminated, and the cache hit rate is improved; fragmented effective edge data is extracted from the cache page and separately stored in a cache managed in a fine granularity; by acquiring the proportion of the edge list of the vertex in the BFS algorithm task queue that has been resident in the cache, and in combination with the vertex out-degree and other attributes, the scheduling order of the vertex in the task queue is adjusted, and the data that has been resident in the cache is maximally utilized. The application can effectively improve the cache hit rate of the graph processing system when processing the BFS algorithm task, and further realizes the improvement of the access performance of the graph processing system.

The invention provides a feature-free point cloud matching method based on weighted subgraph isomorphism, and belongs to the technical field of three-dimensional data processing and point cloud registration. According to the method, robust matching and spatial registration between the source point cloud and the target point cloud are realized without depending on feature point extraction and initial pose estimation. The method comprises the following steps: respectively constructing weighted undirected graphs of a source point cloud and a target point cloud based on Euclidean distances between points in the point clouds; generating a source sub-graph set and a target sub-graph set with a fixed vertex number in the weighted undirected graph; performing weighted approximate isomorphic search on a source sub-graph and a target sub-graph by constructing a sub-graph distance vector and combining kd-tree retrieval, and extracting a candidate point corresponding relation; according to the method, a global constraint mechanism of a weighted sub-graph isomorphism and corresponding relation consistency graph is introduced, so that accumulative diffusion of local matching errors is effectively avoided, and matching robustness and accuracy in point cloud sparsity, noise interference or structure repetition scenes are remarkably improved.

The present application relates to the technical field of data processing and analysis, and further relates to a topological electrical parameter mixed fault diagnosis method and device for blasting networking, comprising the following steps: step S1: abstracting the blasting networking as a directed graph structure and deploying intelligent acquisition nodes containing Kelvin double-arm bridge arrays and switching matrices at each vertex; step S2: applying multiple rounds of excitation at the root node position and synchronously acquiring the node voltage values of each vertex, and constructing a topological voltage distribution matrix according to the vertex number; step S3: calculating the measured resistance value sequence of each edge according to the topological voltage distribution matrix, inputting the edge abnormal scoring model according to the layer number of hops to generate an abnormal edge candidate set; and step S4: performing switching matrix isolation measurement and insulation detection on the abnormal edge candidate set according to the abnormal scoring order. The present application realizes systematic modeling and fine perception of the electrical state of complex blasting networking, effectively improving the accuracy and localizability of pre-explosion fault diagnosis.