5 results about "Full tensor" patented technology

The application belongs to the technical field of image processing, and provides an intelligent carrier image completion method based on image cutting and tensor interconnection completion, which comprises the following steps: storing an RGB format picture shot by a camera in the form of a tensor as a target tensor; according to the size and gray value of a current frame tensor, pre-processing a prior tensor, and simultaneously cutting the pre-processed prior tensor to generate a reference tensor by using an AIP algorithm, and stacking the reference tensor and the target tensor into a synthetic tensor; processing the synthetic tensor by using an ITSC algorithm to obtain a processed tensor after interconnection completion; extracting a tensor of a current image corresponding region from the processed tensor to obtain a completion tensor, and completing image completion. The application is superior to the current main intelligent flight carrier completion method in stability and effectiveness of image completion, and application of the method can greatly improve the stability and effectiveness of image completion of the intelligent flight carrier in a bad weather and poor communication scene.

The application discloses a kind of conversion methods from aeromagnetic three-component to gradient full tensor, it is related to the technical field of aerogeophysical exploration data processing.Data includes: obtaining aeromagnetic three-component data;The three-component data of aeromagnetic is preprocessed, and corrected three-component data is obtained;In spatial domain, according to corrected three-component data, adaptive multilayer equivalent source initial model is constructed;Frequency domain-space domain mixed iteration conversion is executed to corrected three-component data, and through adaptive multilayer equivalent source initial model, gradient tensor is modified, and spatial domain gradient tensor that meets convergence condition is obtained;Converged spatial domain gradient tensor is output as final full tensor magnetic gradient data.The application realizes high-precision, high-efficiency conversion from vector three-component to gradient full tensor by mixed domain processing strategy and adaptive constraint mechanism, provides reliable technical means for data processing and geological interpretation under the condition that full tensor gradient cannot be directly measured.

This invention discloses a method for predicting the production capacity of deep coal and rock gas considering complex fracture networks. First, the method establishes a fracture network topological tensor matrix based on fractal geometry and non-Euclidean topological manifolds. Second, it introduces a nanoscale confined multi-state desorption operator to construct a cross-scale gas release source term and integrates continuum damage mechanics and phase field theory to generate a full-tensor permeability evolution functional. Subsequently, a kinetic model is established to quantify the conductivity attenuation boundary caused by coal powder bridging. Combining the above parameters, a spatiotemporal fractional derivative is introduced to construct a comprehensive flow field control equation characterizing nonlocal anomalous diffusion of fluids. Finally, this equation is mapped to a hypergraph network system for global order reduction solution. This invention effectively eliminates the computational singularity of multiphysics rigid equation sets, achieving efficient and high-precision prediction of deep gas well production capacity under time series, providing reliable support for formulating scientific drainage and production systems.

The present application belongs to the field of silicon-based optoelectronics, and particularly relates to a method for full tensor characterization of dielectric constant of magneto-optical film. The present application is based on transfer matrix method and modification of ellipsometer, and differential Mueller matrix of magneto-optical film under positive magnetic field and negative magnetic field is obtained by measurement of ellipsometer according to the characterization principle of transfer matrix method. Diagonal elements of dielectric constant tensor are obtained by fitting ellipsometric parameters according to structure model and dispersion model, and non-diagonal elements of dielectric tensor are obtained by parameter inversion of transfer matrix method. The present application firstly combines transfer matrix method and 4*4 Mueller matrix, and non-contact ellipsometric spectrum measurement is carried out under the condition of applied magnetic field by ellipsometer, so that full tensor characterization of dielectric constant of wafer-level magneto-optical film is realized without destroying wafer or carrying out sample processing, the vacancy of full tensor non-destructive characterization of dielectric constant of wafer-level magneto-optical film is filled, and the present application has great significance for further industrial application of magneto-optical film.

The invention discloses a cubic miniature full-tensor magnetic gradient sensing chip, which comprises a cubic base and twelve micro electro mechanical system single-axis fluxgate sensing devices arranged on the surface of the cubic base, the cubic base is formed by splicing and fixing six substrates through concave-convex sockets; the upper surface and the lower surface of each substrate are respectively bonded and fixed with a single-axis fluxgate sensing device, so that a cross-shaped twelve-unit fluxgate sensing array which is completely symmetrical about the center of the cube and is distributed at equal intervals is formed on the cubic base. The micro-electro-mechanical system fluxgate geomagnetic tensor sensing chip is manufactured by adopting the MEMS technology, compared with a traditional fluxgate tensor instrument, the micro-electro-mechanical system fluxgate geomagnetic tensor sensing chip is good in stability, high in consistency, firmer and not prone to being influenced by environment temperature changes and external stress, the scale factor error of the micro-electro-mechanical system fluxgate geomagnetic tensor sensing chip can be effectively reduced, and the performance of the micro-electro-mechanical system fluxgate geomagnetic tensor sensing chip is enhanced.