17 results about "Tree modeling" patented technology

The invention discloses a primary and secondary fusion ring main unit fault rapid isolation method and system, and relates to the technical field of power distribution network automation. The method comprises the following steps: acquiring topological characteristics of each node of the ring main unit and performing validity verification to generate an effective topological fingerprint; constructing a dynamic time sequence fault tree model based on the topological fingerprints, and obtaining a minimum cut set with time sequence constraints through space-time decoupling; based on the minimum cut set, a fault isolation strategy is generated through reinforcement learning, and safety verification is carried out; and based on the isolation strategy passing the verification, pre-judging a future topology state through topology deduction and generating a trigger signal. Through dynamic topological feature extraction and verification, reliable basic data is provided for the primary and secondary fusion ring main unit, and the adaptive capacity of the primary and secondary fusion ring main unit in a topological change scene is enhanced; by means of dynamic time sequence fault tree modeling, the fault evolution law is accurately captured, the limitation of a traditional static model is broken through, and the accuracy of fault positioning is improved.

The invention relates to the technical field of radar equipment guarantee and intelligent maintenance, in particular to a radar fault positioning method based on hierarchical fault tree modeling and probability analysis. According to the method, the radar system is comprehensively analyzed, the top event is determined, the middle event and the bottom event are derived step by step, the radar fault tree is constructed, and after arrangement and optimization, fault diagnosis is achieved in combination with qualitative and quantitative analysis. The radar fault diagnosis method can help maintenance personnel to quickly position radar faults, improves diagnosis efficiency and accuracy, is especially suitable for radar equipment with a complex structure, and solves the problems of high difficulty and low efficiency of existing radar fault diagnosis.

The invention discloses a microsystem single event effect risk assessment method, which comprises the following steps: constructing a device-level model and a circuit-level model, and performing single event effect simulation on a device to obtain single event transient current curves under different linear energy transfer values LET; performing double-index model fitting to obtain an LET threshold value of each module; establishing a fault tree model based on the system architecture, and carrying out quantitative analysis to calculate the fault rate, the unavailability and the average fault interval time of each bottom event; and establishing a fault transmission model based on a Bayesian network, and identifying key risk nodes. According to the method, a circuit-level and system-level combined risk assessment model is innovatively constructed, and comprehensive and accurate assessment of the single event effect risk of the astronavigation microsystem is realized. Through methods such as fault tree modeling and Bayesian network modeling, transmission paths and influence factors of the faults can be deeply analyzed, key nodes of the system faults are identified, and a scientific basis is provided for design optimization and risk prevention and control of the microsystem.

The utility model discloses a landscape tree modeling support which comprises a base, a shear type lifting mechanism is fixedly installed on the upper side of the base, a stand column of a circular tube structure is fixedly installed on the top of the shear type lifting mechanism, a clamping jaw assembly is fixedly installed on the top of the stand column, and the clamping jaw assembly comprises an installation base and two jaw bodies. A rotatable connecting arm a and a rotatable connecting arm c are symmetrically installed on the left side and the right side of the installation base, the outer ends of the connecting arm a and the connecting arm c are hinged to the tail of the claw body, gears concentric with the hinge point are fixedly installed at the inner end of the connecting arm a, a double-face rack is arranged between the two gears, and the left side and the right side of the double-face rack are meshed with the double-face rack. The lower end of the double-face rack is fixedly connected with a round rod, and the lower end of the round rod penetrates through the mounting base and is inserted into an inner cavity of the stand column. The clamping jaw assembly is used for clamping branches, opening and closing clamping can be controlled at the low position, and operation is very convenient. And the tensioning height and force are adjusted through the shear type lifting mechanism, and the supporting and restraining effect can be improved.

The invention discloses an entropy optimization individual tree skeletonization method driven by a water drop model, and belongs to the technical field of forest three-dimensional reconstruction and laser point cloud processing. According to the method, single-tree point cloud is regarded as a water drop model with mass difference, contraction, merging and evaporation are carried out under the action of attractive force, repulsive force and equivalent surface tension, and a preliminary framework with local details reserved is generated; a skeleton entropy is defined based on water drop evolution geometric feature distribution, and entropy reduction optimization is utilized to enable a water drop model to converge from disorder to a low-entropy ordered skeleton. And iteratively minimizing the residual sum of squares of the point cloud and the skeleton edge, and reconstructing the topology, so that the skeleton point is more centered, and the topology is more reasonable. According to the method, skeleton points and topological edges can be output at the same time, and a reliable basis is provided for accurate individual tree modeling, biomass estimation and forestry application.

The utility model relates to the technical field of tree modeling, in particular to a garden landscape tree modeling fixing device. The branch pulling device can meet branch pulling and shaping requirements of trees with different diameters, the applicability is improved, and the structure is more scientific and reasonable; comprising a hoop and a plurality of jacking and stretching mechanisms, the inner diameter of the hoop is larger than the trunk diameter of a tree to be modeled, the jacking and stretching mechanisms are evenly distributed in the circumferential direction of the hoop, and each jacking and stretching mechanism comprises a jacking rod installed on the hoop in a hinged mode and a traction assembly used for being connected with a tree branch. The traction assembly at least comprises a pull rope and a connecting piece installed at one end of the pull rope, and the other end of the pull rope is connected with the end, away from the center of the hoop, of the jacking rod. The connecting piece comprises a clamping seat hinged to the pull rope and a rotary wrapping piece hinged to the clamping seat, the rotary wrapping piece comprises a fixing frame and a flexible belt, a plurality of evenly-distributed clamping teeth are arranged at the position of the flexible belt, a sliding groove allowing the flexible belt to be inserted is formed in the clamping seat, and a clamping hook is hinged to the position of the sliding groove.

The application provides a fault tree generation method and computer equipment for cloud computing services, acquires heterogeneous spatio-temporal data of a first cloud platform, which includes spatial data and monitoring time series data from different data sources, then determines each fault event existing in the first cloud platform and the causal logical relationship between each fault event based on the heterogeneous spatio-temporal data, carries out fault tree modeling on each fault event and the causal logical relationship, obtains at least one logical fault tree, and at least based on the heterogeneous spatio-temporal data, carries out attribute labeling on each event object contained in the at least one logical fault tree, generates a target fault tree for the first cloud platform, and is used for reliability analysis of cloud computing services.

The application discloses a non-complete information game intelligent processing method and system based on secure multi-party computation, a terminal and a storage medium, relates to the technical field of data processing, and comprises the following steps: acquiring a participant set of a game, an initial game state, a historical action set, a terminal history set, a preset game strategy based on a secure near-end strategy optimization algorithm, and an action set, an information set and a profit function corresponding to each participant; modeling is performed based on an extended game tree modeling framework according to the participant set, the initial game state, the historical action set, the terminal history set, the game strategy, and the action set, the information set and the profit function corresponding to each participant; and a safe extended game model is constructed. According to the preset optimization target and the leaf nodes in the safe extended game model, the game results between the participants are determined and output. In this way, the data security is improved, and the security of the game process is improved.

The application provides a cultivation method of a hovering type tree modeling, and belongs to the technical field of tree modeling cultivation. The method is characterized in that: a main stem of a tree with branch stems is cut off, and the main stem is grafted with a tree root; a sandwich rooting facility is built to cultivate a main modeling root system; a prolong stem is grafted at the end of the branch stem, and a secondary rooting facility is used to cultivate a secondary modeling root system; after the root system grows to a standard, various rooting facilities are gradually removed, and finally a hovering type tree modeling with a lower solid and an upper empty is formed. The cultivation method of the hovering type tree modeling breaks the inherent form of a lower solid and an upper empty in traditional tree modeling, greatly shortens the cultivation period, and makes the root system and the branch stem modeling follow the aesthetic principle of straightness being simple and beauty being in curves. The modeling tree cultivated has artistic beauty, cultural connotation and emotional value, can be used as a characteristic landscape of landscaping, and has a significantly improved input-output ratio.

The present application relates to a kind of tree modeling methods based on unmanned aerial vehicle collection image and image recognition, comprising: according to the scale of target area and tree distribution planning flight path of unmanned aerial vehicle, collect multi-angle image of tree;Then, through pre-processing, image is denoised, cropped and enhanced, and using pre-trained neural network, image is semantically segmented, and the semantic label of each pixel is obtained;Through SIFT algorithm, image feature points are extracted and matched, and COLMAP incremental reconstruction method is used to construct preliminary three-dimensional point cloud model;According to the semantic segmentation result of image, the semantic label of each pixel is transmitted to point cloud data, and the semantic labeling of point cloud is completed;Again, by traversing point cloud data, according to label, point cloud is segmented, and three-dimensional point cloud model of tree is obtained;The method can be widely applied in vegetation monitoring, forest resource investigation and ecological environment protection and other fields, with the advantages of high precision, automation and high efficiency.

The application discloses a fractal growth model and a fine tree modeling method, and belongs to the technical field of three-dimensional reconstruction, which comprises the following steps: acquiring original point clouds of single trees in a reconstruction area, an image set and ground height information of each spatial position; data preprocessing and point cloud data segmentation; extracting the skeleton of the tree from the non-ground point cloud based on graph theory, Dijkstra algorithm and cubic spline interpolation algorithm; hierarchically reconstructing the tree to generate a three-dimensional grid model of the trunk, a branch cylinder model and a small branch model, and fusing them into a tree model; and performing texture mapping based on NeRF to obtain a comprehensive tree model. The application introduces a graph theory method as a key link in the skeleton extraction process, accurately extracts the tree skeleton from the non-ground point cloud, adopts a hierarchical reconstruction method, realizes accurate extraction of the skeleton and tree modeling, introduces the NeRF technology in texture mapping, and improves the modeling accuracy and texture quality.

The invention discloses a Hash partitioning method based on a document multilevel structure, which realizes high matching of Hash blocks and document logic units, and improves the accuracy and efficiency in scenes such as document evidence storage, copyright protection, intelligent retrieval and the like. According to the technical scheme, multi-level structure analysis and tree modeling are carried out, wherein a document is analyzed into a'chapter-paragraph-sentence 'three-level structure tree for the first time, and a complete logic unit basis is provided for partitioning; parallel calculation and verification of double Hash: ensuring uniqueness by main Hash, realizing semantic and structure verification by auxiliary Hash, and solving the problem of cross-logic unit splitting; hierarchical hash index construction: constructing a four-level hash index based on a Merkle tree thought, supporting multi-level difference positioning from documents to sentences, and improving comparison and retrieval efficiency; and dynamic partitioning strategy switching: supporting a coarse / fine / mixed partitioning strategy, and adapting to multi-scene requirements of version comparison, copyright verification and the like.

The application discloses a kind of digital irrigation area engineering information tree model modeling method and system, it is related to irrigation area water network data processing technical field, including according to river source estuary engineering instance subset, based on spatial intersection algorithm and the key node set of engineering information tree based on recursive depth-first traversal algorithm is constructed, according to associated engineering instance subset set and key node set, based on spatial near neighbor algorithm, shortest distance point algorithm constructs the main subsidiary node set of engineering information tree;According to associated engineering instance subset set and main subsidiary node set, based on spatial near neighbor algorithm constructs the secondary subsidiary node set of engineering information tree;According to the key node set of engineering information tree, main subsidiary node set and secondary subsidiary node set, the engineering information tree model of irrigation area engineering is constructed.The application realizes irrigation area engineering information sharing, improves the collaborative management efficiency of irrigation area engineering information.

The invention relates to the technical field of stocker fault detection, in particular to a stocker fault tree diagnosis and grading response method and system. The method comprises the following steps: acquiring historical fault information of a stacker, and constructing a stacker fault tree model and a fault case library; operating data of the stacker are collected in real time, and fault feature parameters are extracted; according to the real-time monitoring data and the fault tree model, carrying out fault diagnosis on the stacker; establishing a fault risk level, outputting a grading response strategy according to the fault risk level, and providing a diagnosis decision; collecting fault diagnosis and processing results of each time; the stacker fault tree diagnosis and hierarchical response system comprises a data management module, a fault tree modeling module, a data acquisition module, a fault diagnosis positioning module, a hierarchical response decision module and an optimization module. According to the method, the stacker can be dynamically analyzed, the fault positioning error rate is reduced, the fault processing mode can be dynamically adjusted according to the real-time operation state, and the maintenance time and cost are greatly reduced.

The invention discloses a test path determination method, device and equipment based on tree modeling, and the method comprises the steps: carrying out the analysis of related information of a printed circuit board (PCB), carrying out the tree modeling of a signal link in the PCB according to an analysis result, and obtaining a signal link topology tree comprising nodes and edges; obtaining a test set based on the signal link topology tree, wherein the test set comprises a plurality of signal paths; selecting a group of signal paths from the test set as test paths based on a coverage optimization strategy and a diversity optimization strategy; wherein the coverage optimization strategy is used for optimizing the coverage of the selected test path in the signal link topology tree, and the diversity optimization strategy is used for optimizing the topology diversity of the selected test path. Therefore, the problems that an existing test path selection method is insufficient in coverage and diversity, key links are prone to being omitted or local concentration of test paths is caused, and the test effectiveness is reduced are solved.

This invention relates to the field of tree modeling technology and discloses a method for 3D modeling of large-scale trees. The method includes: acquiring a multi-scale digital image set of the target tree using an image acquisition device; the multi-scale digital image set consists of image data captured by the user at different viewing distances; processing the multi-scale digital image set to identify and match visual feature points between images, and generating an initial 3D point cloud based on these visual feature points; performing density enhancement processing on the initial 3D point cloud to generate a dense 3D point cloud representing the surface morphology of the tree; performing meshing processing on the dense 3D point cloud to construct a 3D mesh model of the tree surface; and applying color information from the multi-scale digital image set to the 3D mesh model to establish a virtual 3D model of the trees in the park. This method achieves high-fidelity, refined, and efficient 3D modeling of large-scale trees through multi-scale image acquisition and a series of point cloud and mesh processing steps.

The utility model discloses a Christmas tree modeling LED display device. The Christmas tree modeling LED display device comprises an LED display module and a Christmas tree modeling frame. The LED display module is used for displaying information or images, and the LED display module is attached to the Christmas tree modeling frame. According to the technical scheme, the LED display module can display different patterns or animations so as to fully meet individual requirements of users. The Christmas tree modeling LED display device does not need complicated and time-consuming manual arrangement by a user, so that the decoration time of the user is shortened, and the user experience is improved.