6 results about "Global structure" patented technology

The invention specifically relates to a deep learning coupled layered rock mass structural plane parameter inversion method, and relates to the technical field of geotechnical engineering and artificial intelligence, and the method comprises the steps: deploying an initial system coupling a deep learning proxy model and a forward numerical simulator, cooperatively laying a monitoring network, and determining an engineering digital baseline and a model performance reference through initial inversion. According to the invention, the hybrid network architecture constructs the deep learning agent model, and the efficient coupling inversion engine is formed by combining the forward numerical simulator of secondary development, so that the problems that the traditional inversion method is low in efficiency and easy to fall into local optimum are solved; the model takes similar engineering cases and indoor rock mechanics test data as a training basis, constructs a digital baseline of global structural plane parameters for engineering, and effectively overcomes the defects of indoor test scale effect, limited field investigation range and the like of a traditional method.

The present application relates to the technical field of laser cladding, and particularly relates to a laser cladding cross-section size prediction method and system for an inclined base surface. In view of the problems of boundary fracture, holes and noise in the prediction results of a deep learning model, an endpoint extension repair algorithm based on graph structure analysis is proposed, and through morphological operation, connected domain analysis and path reverse extension and other steps, the boundary defects are effectively repaired. In order to improve the prediction accuracy of the cladding layer cross section, the Pix2Pix model is applied to the cladding layer cross section shape prediction for the first time, and the perception loss is introduced to enhance the perception ability of the model to the boundary details and global structure. In addition, the structural similarity index is introduced, and the high-similarity molten pool images are extracted from the molten pool videos under different parameter conditions as an expanded training set, so that the generalization ability and robustness of the model are effectively improved.

The invention discloses a prestressed beam simulation method based on an incomplete bonding theory and a vector finite element, which comprises the following steps: calculating the mechanical response of the section of a prestressed beam under the action of different loads based on an incomplete bonding theory model so as to construct a bending moment-corner relationship; dispersing a prestressed beam structure where the section of the prestressed beam is located into a plurality of mass points by adopting a vector type finite element method, and connecting the plurality of mass points by using a mass-beam-free unit to construct a global structure analysis model; and taking the bending moment-rotation angle relation as a force-deformation relation of the mass-free beam unit in the global structure analysis model, calculating displacement response of each mass point in the global structure analysis model, updating internal force in the calculation process according to the deformation of the mass-free beam unit and the bending moment-rotation angle relation, and outputting a simulation result of the prestressed beam structure. The method provided by the invention can accurately simulate the complete stress behavior of the beam from elasticity, cracking, yield to limit damage, and provides data support for subsequent research.

The present application relates to the field of building structure safety analysis, and particularly relates to a building structure safety analysis method fusing point cloud data. First, based on the obtained three-dimensional point cloud data, a three-dimensional space grid is constructed, and fixed space anchor points are determined. Then, based on the fixed space anchor points, the three-dimensional point cloud data is mapped into the anchor domain, an improved structure tensor neighborhood difference method is introduced, and a structure change intensity index is obtained. Finally, based on the structure change intensity index, an improved time-symmetry second-order difference structure evolution evaluation method is introduced, and a global structure safety index is obtained. The technical problems of being difficult to depict the dynamic evolution process of the structure over time, lacking the ability to identify gradual damage, being sensitive to point cloud data noise and prone to misjudgment, lacking a unified and stable spatial reference system, being difficult to align cross-frame data and affecting the overall analysis accuracy, and relying on experience rules for overall evaluation indexes and lacking data-driven quantitative expression are solved.

The application discloses a multilevel system model construction method, system, device and medium, and relates to the technical field of system engineering and system modeling. The method comprises the following steps: acquiring information data of a multilevel system to be constructed; determining a structure undirected graph according to the structure relationship and the construction objects between construction objects; performing regional segmentation according to a set path step based on the level corresponding to the construction objects and the structure undirected graph, and obtaining a plurality of regional network structures; for any regional network structure, determining the dependency relationship between the construction objects by using a data structure learning algorithm, and determining a graphical network according to the dependency relationship; determining a structure network model of the multilevel system to be constructed according to the structure undirected graph and all the graphical networks; and the structure network model is used for representing the mechanism characteristic information of the multilevel system in cooperative interaction. The application can perfect the global structure of the system and realize the construction of a global static model.

The invention discloses a corundum spinel material microstructure intelligent analysis method and device, and the method comprises the steps: obtaining an original microstructure image of a material, carrying out the standardization preprocessing, and inputting the image into a pre-trained material analysis model, so as to obtain a sintering temperature type and a prediction probability; the model comprises an input receiving module, a double-branch feature extraction module, a multi-modal feature fusion module and a classification decision module, wherein the double-branch feature extraction module comprises a local feature extraction branch and a global feature extraction branch which are arranged in parallel; and the model performs classification decision by fusing the local detail features and the global structure features which are extracted in parallel. The method also generates a decision thermodynamic diagram based on a model classification result, and reveals a microstructure basis of a model sintering temperature classification decision. According to the method, the problems of feature extraction limitation and black box decision making of an existing single model are solved, high-precision and interpretable intelligent analysis of the sintering temperature of the corundum spinel material is achieved, and reliable guidance is provided for material process optimization.