28 results about "Density gradient" patented technology

The invention discloses a geometric spectrum coupling-based neural radiation field high-fidelity representation method and system. The method comprises the following steps of: obtaining sparse multi-view image data and calculating internal and external parameters of a corresponding camera; generating light based on internal and external parameters of the camera, and performing point sampling on the space along the direction of the light to obtain sampling points; constructing a differentiable coding layer, predicting the density of sampling points through forward propagation of a neural network, and obtaining a principal curvature, a density gradient and an included angle between a normal vector of the sampling points and an observation direction based on a density prediction result; constructing a spectrum-geometric coupling function, and calculating to obtain a spectrum coupling coding vector; the spectrum coupling coding vector is used as an input to be transmitted into a NeRF main network, and NeRF volume rendering is carried out according to a density and color prediction result; and performing difference optimization training on the rendering result and the real image to obtain a high-fidelity composite image. According to the invention, the expression ability of the neural radiation field model in the high-frequency detail area can be enhanced.

The invention relates to the technical field of nondestructive testing and intelligent manufacturing, and provides a weld defect intelligent identification system based on multi-source data fusion. The system synchronously obtains a visual image, a three-dimensional point cloud and ultrasonic array data of a welding seam through a multi-source data acquisition module; a hidden danger density field construction module generates surface and internal hidden danger density fields; the cross-space association and defect topology extraction module associates and binds high-density areas meeting spatial continuity and gradient consistency conditions in the two density fields into a cross-space association cluster through density gradient consistency analysis and a preset topology mode template, and generates a defect sign vector; and finally, the defect decision module outputs the defect type, position, size and confidence coefficient based on the sign vector. According to the method, multi-source heterogeneous data is innovatively unified to hidden danger density field characterization, collaborative, accurate and explainable recognition of internal and external defects of the weld joint is achieved through topology analysis of a cross-space correlation cluster, and the limitation of a traditional single detection means is overcome.

The invention provides a marine environment multi-dimensional time sequence prediction method and system based on a deep learning neural network. According to the invention, the deep learning neural network is utilized to predict the multi-dimensional time sequence change of the marine environment. And constructing a ship trajectory and collecting water body biological displacement information. And the neural network fuses the ship trajectory and the marine ecological parameters to generate interaction evolution characteristics. And mapping the sound pulse reflection intensity and the phase difference of the biological displacement into a three-dimensional motion vector, and constructing a biological activity intensity model after processing. And quantifying ship density gradient and course conflict as a space pressure coefficient, and combining with multi-ship disturbance superposition to form an ecological pressure diagram. Iteratively calculating the pressure time-varying law and the divergent characteristics of the biological model, and outputting an ocean disturbance matrix; and through adaptive weight fusion pressure propagation and biological response, generating spatial-temporal distribution prediction of marine ecological disturbance. According to the method, interaction between ship activities and marine organisms is quantified, and spatial-temporal distribution of marine ecological disturbance is predicted by fusing multi-dimensional data.

The invention discloses an unstructured grid adaptive sub-mesoscale hybrid parameterization method and system, and the method comprises the steps: calculating a sea surface horizontal density gradient defined on an edge in a sea model of an unstructured grid, correcting the sea surface horizontal density gradient according to an effective resolution ratio and a frontal surface scale, and carrying out the calculation of the submesoscale hybrid parameterization of the submesoscale hybrid parameterization of the submesoscale hybrid parameterization of the submesoscale hybrid parameterization of the unstructured grid. Calculating a sea surface horizontal buoyancy gradient; calculating the sea surface level Ekman buoyancy flux according to the sea surface level buoyancy gradient and the sea surface wind stress; and if the sea surface level Ekman buoyancy flux is a negative number, further calculating a mixing coefficient in the boundary layer. According to the method, the influence of the symmetrical unstable process on boundary layer mixing can be effectively introduced into the global unstructured grid ocean mode, and the simulation effect of the depth of the mixing layer under coarse resolution is remarkably improved.

The application discloses a dimension reduction method for river hydrodynamic simulation, and specifically comprises the following steps: data collection; constructing a two-dimensional plane hydrodynamic model based on shallow water equation; adding the influence of curvature-induced secondary flow into the shallow water equation through a dispersion stress term; further introducing the contribution of the density gradient to the angular momentum into the angular momentum conservation equation; coupling the convection-diffusion equation of the dispersion stress to construct a two-dimensional plane hydrodynamic-matter transport finite element model; and calculating the average flow field of water depth and the secondary flow intensity. The three-dimensional effect of the secondary flow driven by the streamline bending and the density difference is added into the two-dimensional equation through the dispersion stress term, and the shallow water equation and the transport equation are coupled and solved, so that the simulation precision of the two-dimensional model is greatly improved, and fast and high-precision simulation of long-term evolution of the large river system topography is realized.

This invention discloses a fully automated method for identifying and classifying deep-sea landforms based on isobath morphological entropy, relating to the fields of marine geological exploration and topographic analysis. The method includes: extracting isobaths from a digital elevation model of the target area at predetermined intervals and constructing an isobath topology map to identify closed loops and bifurcation points; and calculating multi-dimensional isobath morphological entropy sub-factors based on the isobath topology map, including isobath topological complexity index, isobath geometric entropy, isobath density gradient anomaly, and isobath curvature spectrum characteristics. This invention, by calculating multi-dimensional morphological entropy sub-factors encompassing isobath topological complexity, geometric entropy, density gradient anomaly, and curvature spectrum characteristics, provides a quantitative description of the topological structure, spatial distribution, and frequency domain characteristics of deep-sea landforms. Compared to traditional single-topographic factor analysis methods, it can capture multi-level topographic information from microscopic morphology to macroscopic patterns, significantly improving the comprehensive characterization ability of complex landform structures.

The invention relates to the technical field of hydrological sediment monitoring, and discloses a sediment content calculation method, which comprises the following steps: acquiring a single-point flow velocity vector, a single-point original sediment content and a total water depth of a measuring point; constructing a non-constant inertia index combining the flow velocity change rate and the single-point flow velocity modulus; determining a dynamic lag time window by using a non-constant inertia index and acquiring a reference sand content; calculating a vertical density gradient and a gradient Richardson number by using the reference sand content, and determining a turbulence suppression factor; respectively correcting a vertical flow velocity distribution function and a sand content distribution function by using a turbulence suppression factor and a non-constant inertia index, and constructing a vertical flow velocity distribution data column and a sand content distribution data column through iterative calculation; and integrating to obtain the single-width sediment transport modulus. According to the method, sediment response lag is corrected by introducing a non-constant inertia index and a dynamic lag time window, the damping effect of density stratification on turbulent flow is quantified by using a turbulent flow suppression factor, and the full-water deep-water sediment structure under the non-constant flow condition is accurately inverted by using single-point data.

The invention discloses a dimension reduction method for river hydrodynamic simulation. The method comprises the following specific steps: collecting data information; constructing a planar two-dimensional hydrodynamic model based on a shallow water equation; the influence of curvature-induced secondary flow is added into a shallow water equation in a dispersion stress term mode; further introducing the contribution of the density gradient to the angular momentum into an angular momentum conservation equation; coupling a convection-diffusion equation considering dispersion stress, and constructing a planar two-dimensional hydrodynamic force-substance transport finite element model; and calculating a water depth average flow field and secondary flow intensity. According to the method, the three-dimensional effect of the secondary flow jointly driven by streamline bending and density difference is added into the two-dimensional equation in a dispersion stress term mode, the shallow water equation and the transport equation are solved in a coupling mode, the simulation precision of the two-dimensional model is greatly improved, and rapid and high-precision simulation of long-term evolution of the landform of a large river system is achieved.

The invention relates to the technical field of composite pipe detection, and discloses a bimetal composite pipe damage detection method and system based on multi-source information awareness, and the method comprises the steps: carrying out the denoising and curvature calculation of an original data set, extracting the characteristics of magnetic flux density fluctuation and wall thickness abnormity from the original data set, fusing the characteristics into a characteristic vector, and carrying out the filtering optimization, calculating a magnetic flux density gradient, dividing an abnormal area, obtaining a damage distribution characteristic, obtaining a defect type label based on a wall thickness change coefficient and a magnetic flux density abnormal point density, if the damage is a composite damage, iteratively optimizing a classification boundary by combining original data, determining a damage area, and determining a defect type label according to the damage boundary and position details. And combining the magnetic flux density gradient and the defect label to generate a final damage identification report. According to the method, the defect of insufficient detection precision caused by incapability of efficiently processing multi-source signals and accurately distinguishing damage types in the prior art is overcome.

This invention relates to the field of multi-sensor fusion technology, and more particularly to a method for precise monitoring of stored materials based on the fusion of lidar and millimeter-wave radar. The method includes the following steps: simultaneously scanning a material pile using lidar and millimeter-wave radar in both modes to obtain penetration echo data and surface measurement data; dividing the material pile into depth layers using the penetration echo data and calculating the interlayer dielectric parameters of the depth layers; detecting density gradient anomalies based on the interlayer dielectric parameters to obtain a layered density feature map; determining the reliability of the point cloud from the surface measurement data, and using the layered density feature map to fill in missing areas and reconstruct the surface contour to obtain a fused surface contour; calculating the support stress distribution on the layered density feature map and the fused surface contour to obtain the vertical pressure distribution field and support strength matrix. This invention significantly improves the accuracy of calculating the storage capacity of stored materials through deep layered analysis and coupling analysis of internal and external structures.

The invention discloses a product positioning and identification method for a sponge curing process, and the method achieves the non-contact internal detection of a cured sponge product through a near-infrared transmission imaging technology, builds a gray scale and density corresponding relation, and provides a quantifiable structural data basis for the subsequent feature extraction. A dynamic threshold-guided semantic segmentation fusion algorithm is combined to construct a recognition model jointly driven by local gray statistics, settlement gradient correction and U-Net semantic segmentation, so that the limitation that single threshold segmentation is easily interfered by noise is broken through, high-precision recognition and boundary maintenance of a high-density settlement area are realized, and the method is suitable for large-scale popularization and application. The robustness and consistency of an image segmentation result are improved, meanwhile, through characteristic parameter systematic modeling, the centroid position of a high-density settlement area is defined as a first characteristic parameter, the weighted gray gradient extreme value in the vertical direction is defined as a second characteristic parameter, and quantitative characterization is established in the two aspects of macroscopic position distribution and microcosmic density gradient.

This invention provides a method and apparatus for simulating surging waves in deformable landslides. The method includes: Step 1, constructing geological, landslide, and water body models; Step 2, setting model boundary conditions; Step 3, performing deformable landslide calculations, using the DEM method to simulate the landslide, where the entire landslide area is composed of DEM particles, and the forces between particles are calculated based on different contact models, with acceleration and velocity updated; Step 4, performing surging wave calculations, using the SPH method to simulate the water body, where the entire water body area is discretized into several fluid SPH particles, and parameters such as density gradient and acceleration are calculated; Step 5, directly adding the calculated acceleration of the coupling force of the landslide DEM particles and the acceleration of the reaction force acting on the SPH particles to Steps 3 and 4 for overall iterative calculation and displacement update; Step 6, performing displacement correction, directly adding the displacement correction term to the displacement calculation in Step 5 to update the particle positions within one time step.

The application discloses a kind of artificial upwelling high-efficiency tidal current velocity range transport calculation method and device, comprising: according to injection depth, injection depth corresponding injection amount, seawater density gradient, the diameter of injection nozzle, the environmental water density at injection nozzle position, the density of injected gas is, bubble slip velocity, plume target height, plume effective range and plume efficiency standard, calculate initial buoyancy flux, buoyancy frequency;Calculate critical horizontal cross-flow velocity;When horizontal cross-flow velocity is less than the critical horizontal cross-flow velocity, calculate the range of artificial upwelling high-efficiency tidal current velocity;When horizontal cross-flow velocity is greater than the critical horizontal cross-flow velocity, calculate the range of artificial upwelling high-efficiency tidal current velocity;Calculate artificial upwelling high-efficiency tidal current velocity range.It can make artificial upwelling system run when artificial upwelling plume can be efficiently transported to target position, realize artificial upwelling system efficiency maximization.

The invention relates to a method for separating, measuring and collecting a density gradient ultracentrifugal sample. The method comprises the following steps: S1, preparing a density gradient solution by utilizing a full-automatic density gradiometer; s2, adding a to-be-detected sample to the top of the density gradient solution, and then carrying out overspeed refrigerated centrifugation; after ultracentrifugation is completed, all components in the sample are separated into a specific density layer; s3, separating and dropwise adding the centrifuged density gradient solution into a 96-hole ultraviolet permeable elisa plate by using a density gradient solution separation system according to a siphon principle, so that target components in the density gradient sample are accurately separated into specific sample holes; s4, putting the 96-hole ultraviolet permeable elisa plate into a full-wavelength microplate reader, reading and measuring an OD value, and determining target component sample holes; s5, calculating the sample concentration; and S6, selecting required sample holes, and collecting and separating the solution in the corresponding holes to obtain the purified and concentrated density gradient ultracentrifugation sample target component. The method is simple, easy to operate, accurate and reliable.

The invention discloses an airborne laser radar sea surface point cloud water depth inversion method, and particularly relates to the technical field of airborne laser radar water depth measurement. The method comprises the following steps: acquiring an echo point cloud and a waveform energy sequence, constructing a three-dimensional point cloud energy matrix, calculating a point cloud local density gradient and a waveform attenuation coefficient, generating a composite scattering characteristic field, constructing a sea surface perturbation constraint model, and performing curved surface fitting on a sea surface echo cluster to obtain a sea surface dynamic fluctuation parameter; performing refraction path reconstruction on the underwater echo cluster to obtain a corrected underwater point cloud depth sequence; calculating a point cloud density change rate in a depth direction, performing coupling operation with the composite scattering characteristic field to generate a water body attenuation compensation coefficient matrix, and calculating a water depth value of the target area through depth statistical regression to obtain a water depth inversion result; the method can effectively weaken the influence of sea surface perturbation and water body scattering on echo signals, and improves the precision and stability of airborne laser radar water depth inversion under complex sea conditions.

1. Name of the designed product: Sealer and its main body of gradient dispenser. 2. Overall use of the product: The designed product is used as a tube sealer or heat sealer of a gradient dispenser. Gradient dispenser is a laboratory instrument used to create and dispense density gradient for sample separation and purification. The gradient dispenser is configured to automate a gradient containing reagents of different densities for a centrifugation process to separate sample components according to their different densities. The designed product is used to seal the container (e.g. test tube) after the gradient is dispensed into the container. Partial use of the product: The partial design of claim 2, 3, 4 is used as the main body of the sealer. 3. Design points of the designed product: The shape of the solid line shown in each view. 4. Picture or photo that best shows the design points: The perspective view of claim 1. 5. Claim 1 is designated as the base design. 6. Other circumstances that need to be explained: The dotted line in each view is shown for illustration purposes and does not constitute part of the claimed design of this design application. The dashed line in each view represents the boundary between the claimed part and other parts.

The present application relates to the technical field of remote sensing data processing, and provides a kind of ground surface identification method based on photon point cloud in polar sea ice observation scene, comprising: obtaining single-photon laser altimetry data to construct two-dimensional photon profile;Divide first scale window, determine threshold based on density gradient field to filter out low-density noise to get intermediate signal set;Construct elevation window in second scale window, remove high-density and low-density tailing double-end outlier subset outside the window to get high-confidence signal set;Extract resampled elevation and sliding classification features;Screen candidate centroid and optical high-resolution image registration and gate filtering;Use multi-temporal image to check label consistency and combine spatial continuity optimization;Combine ice and snow radiation transfer model to complete physical verification to construct training set;Input classifier outputs sea ice, ice channel and thin ice identification result.The present application improves the physical reliability of training set label, reduces the influence of optical label mismatch, and improves the accuracy of polar ground surface identification.

The utility model discloses a density gradient centrifugal sample separation and collection device which comprises a body, a separation analysis part, a recovery part and a main control part, wherein a sample groove is formed in the body; the separation analysis part is arranged at the top of the body, a sample channel is formed in the separation analysis part, and the inlet end of the sample channel corresponds to the sample groove; the recovery part is arranged at the top of the body and corresponds to the outlet end of the sample channel; the main control part is arranged on the body, controls the sample groove to move towards the separation analysis part so as to enable the density gradient centrifugal samples of different layers to sequentially enter the sample channel for separation, and controls the recovery part to respectively receive the separated density gradient centrifugal samples. The device is controlled by the main control part to work, so that a density gradient centrifugal sample is quickly separated after passing through the separation analysis part, the operation is simple, the flow time is short, the sample separation accuracy can be ensured to the greatest extent, the pollution in the whole separation process is reduced, and the separation and storage of a biological sample are facilitated.

The application discloses a system and method for configuring stable density stratified water environment by free fall method, which comprises an upstream liquid supply barrel A, an intermediate mixing barrel B and a target water tank C which are sequentially connected, and realizes gravity-driven perfusion without external pumping by using orifice free drainage; the upstream liquid supply barrel A supplies liquid to the intermediate mixing barrel B through a bottom orifice, the intermediate mixing barrel B is continuously stirred to keep the water fully mixed and change the density in the intermediate mixing barrel B over time, and the intermediate mixing barrel B injects the water changing over time into the target water tank C through a bottom orifice, so that the density time history of the intermediate mixing barrel B is mapped to the height density profile of the target water tank C and a density gradient is formed. Meanwhile, a liquid surface disturbance reduction scheme for the target water tank C is disclosed. Compared with the traditional double-barrel method, the application can reduce the dependence on accurate flow ratio adjustment, improve the mixing uniformity in the later stage, shorten the preparation time, and thus realize stable, repeatable and more efficient density stratified water environment construction.

A system performs a non-destructive measurement of a density gradient to automatically replicate and dispense the density gradient. The system obtains measurements at points along a length of the density gradient and generates a profile of the density gradient based on the measurements. The system uses the profile to replicate the density gradient of components in a second container. The system inserts a distal end of a probe into the second container, and pumps separate components into a manifold and mixing chamber connected to a proximal end of the probe to automatically dispense the density gradient in the second container.

The present application relates to the field of earth science, specifically relates to a method and product for isopach-stress field-geological structure analysis of the crust, the method comprising determining stratum layered structure and establishing a physical parameter model, the layered structure comprising a crust layer, a plastic layer and a magma layer; based on the change of the magma density gradient, a magma flow model is constructed to analyze the laminar flow characteristics and the flow velocity distribution in the crust thickness variation area; combined with the regional crust thickness contour map, the stress field distribution of magma flow in different crust thickness areas and its driving effect on fracture tectonic activity are analyzed, and the dynamic coupling relationship between magma flow and fracture tectonic activity is obtained; the present application can provide an accurate basis for the analysis of the influence of magma flow on crustal tectonic activity. The flow model established based on the change of the magma density gradient determines the flow characteristics and flow velocity distribution characteristics of the magma layer, especially the complex flow behavior in the crust thickness variation area.

The invention provides an underground space construction path adaptive control system based on multi-field information fusion. The method comprises the following specific steps: deploying a microgravity sensor array through a space mapping module, collecting gravity anomaly data of different depths underground, and constructing a three-dimensional geological topology model; the navigation decision module is used for coupling the optical flow signal and the continuous resistance distribution function, generating a guide vector field and realizing dynamic deviation correction according to the equipment pose error and concrete sound velocity feedback; the collaborative execution module calculates the inclination angle and the energy compactness of the vibrating rod and outputs a vibrating execution evidence packet; and the closed-loop monitoring module performs error analysis on the vibration effect and executes local interpolation or global reconstruction to realize adaptive optimization of the model. Compared with an existing floor construction system which only depends on static design and experience operation, the system can achieve high-precision recognition of the density gradient of the underground structure, dynamic cooperation of a path and energy control and real-time feedback closed-loop adjustment of construction quality, and the construction precision and consistency are remarkably improved.

The application discloses a kind of unstructured grid adaptive mesoscale mixing parameterization method and system, the method includes: in the ocean model of unstructured grid, the sea surface horizontal density gradient defined on the edge is calculated, after the sea surface horizontal density gradient is corrected according to effective resolution and frontal scale, the sea surface horizontal buoyancy gradient is calculated again;Then, the sea surface horizontal Ekman buoyancy flux is calculated according to the sea surface horizontal buoyancy gradient and the sea surface wind stress;If the sea surface horizontal Ekman buoyancy flux is positive, then the mixing coefficient in the boundary layer is further calculated.The application can effectively introduce the influence of symmetric instability process on boundary layer mixing in global unstructured grid ocean model, and significantly improve the simulation effect of mixed layer depth under coarse resolution.

The invention discloses a deep sea landform full-automatic identification and classification method based on isobath form entropy, and relates to the technical field of marine geological exploration and terrain analysis, and the method comprises the steps: extracting isobaths from a digital elevation model of a target area according to a set interval, constructing an isobath topological relation graph, and identifying a closed ring and a bifurcation point; on the basis of the isobath topological relation graph, multi-dimensional isobath form entropy sub-factors including an isobath topological complexity index, isobath geometric entropy, isobath density gradient anomaly and isobath curvature spectrum features are calculated; according to the method, the multi-dimensional morphological entropy sub-factors covering the isobath topology complexity, the geometric entropy, the density gradient anomaly and the curvature spectrum characteristics are calculated, and the deep sea landform topological structure, the spatial distribution and the frequency domain characteristics are quantitatively described; and multi-level topographic information from a micro form to a macro pattern can be captured, and the comprehensive characterization capability of a complex landform structure is remarkably improved.

A system for supplying a density gradient into a container is described. The system pumps a volume of sample particles and a density modifier into a mixing chamber that is in fluid communication with the proximal end of the probe. The mixing chamber mixes the sample particles and the density modifier together to form at least a partial density gradient. The system supplies the density gradient into the container through the distal end of the probe. The density gradient has a variation in density between the first and second ends, and at least a portion of the density gradient between the first and second ends includes the supplied volume of sample particles.

The application discloses a kind of lotus root field cultivation remote automation management system and method thereof, it is related to cultivation automation management technical field, by underwater ultrasonic wave array obtains the reflection wave data of silt layer;According to the echo delay time in the time domain feature and the main frequency attenuation rate in the frequency domain feature, construct three-dimensional density field;When the density gradient value exceeds preset threshold and duration reaches critical value, it is determined that the hardening risk area, and generates soil loosening path planning data;The soil loosening path planning data is sent to water unmanned ship, and triggers soil loosening unmanned plane to execute soil loosening operation according to planning path.The application can identify hardening area in real time, improve monitoring accuracy, generate soil loosening path planning data based on density gradient value and oxidation-reduction potential data, and adopt water unmanned ship and soil loosening unmanned plane cooperative operation, realize accurate soil loosening.

The invention relates to the technical field of powder compact density gradient detection, and particularly discloses a terahertz spectral imaging-based powder compact density gradient detection method, which comprises the following steps of: pre-establishing an environment interference compensation model and a signal-density correlation model, and transmitting multi-angle terahertz detection pulses to a compact preset point during detection, so as to detect the density gradient of a compact; synchronously applying high-frequency micro-amplitude mechanical vibration to mark a signal, and generating an original multi-dimensional feature packet in combination with real-time environmental parameters; then, environment interference is quantized by using a preset compensation lookup table, a pure signal feature set is constructed, and a three-dimensional density gradient map is generated through spatial interpolation; according to the invention, through an active marking and compensation mechanism, the stability of detection under complex working conditions is improved, a data processing link from original signal acquisition to density value output is established, and a three-dimensional density map is reconstructed by combining multi-angle detection with spatial interpolation. And an effective technical means is provided for quality control and process improvement of powder metallurgy manufacturing.

A flow-dependent three-dimensional variational data assimilation method based on a rotating mixed tensor comprises the following steps: acquiring seawater density gradient vector information: calculating a density background field by a seawater state equation based on seawater background field temperature and salinity information to obtain density distribution of each grid node, and calculating the density distribution of each grid node by using gradient components of the density field in three directions to obtain the density gradient vector information of each grid node; obtaining a density gradient vector; the rotation of the vector in the three-dimensional coordinate system is constructed, the rotation of the vector is the rotation hybrid tensor of which the direction is automatically adjusted along with the inclination angle direction of the isodensity surface, and a tensor rotation formula is combined with the symmetry of the rotation hybrid tensor, and then the rotation hybrid tensor on which the flow depends is obtained through conversion; through an improved three-dimensional variational data assimilation framework, a flow-dependent three-dimensional variational data assimilation framework is formed. According to the method, the flow dependence characteristic in the ocean mixing process is captured by utilizing the rotating mixing tensor according to the characteristic that the density gradient of seawater dynamically changes along with the flow field structure and density distribution.