13results about How to "High geometric accuracy" patented technology

This invention relates to the field of microfluidic control technology and discloses a method and system for detecting and controlling microfluidic droplet formation. The method first constructs an ideal concentric ring geometric model by acquiring the target parameters of the microcapsule and establishes a force-shape coupling response matrix. Based on this, a preset velocity triplet is solved to generate the initial droplet. Then, droplet image sequences are acquired and fitted with real-time concentric ring groups. These are geometrically superimposed with the ideal concentric ring geometric model to generate a deviation ring domain, which is then decomposed hierarchically to obtain geometric deformation characteristic components. Finally, a coordinated velocity adjustment vector is calculated using the force-shape coupling response matrix, a composite fluid correction field is constructed, and the deviation ring ablation cycle is iteratively executed until geometric convergence is achieved. This invention effectively solves the oscillation problem caused by strong parameter coupling in multiphase flow fields by constructing a quantitative mapping and inverse decoupling mechanism between fluid and geometric shape, achieving coordinated and precise control of the microcapsule's external dimensions and internal structure.

This invention discloses a method for constructing a realistic depth estimation training dataset based on a 3D mesh and 3D Gaussian splashing, relating to the field of UAV aerial surveying technology. The method involves acquiring aerial image sequences using a visible light camera mounted on a UAV platform, and filtering and preprocessing the image quality; generating a dense point cloud and a 3D mesh; training and generating a 3DGS model based on camera pose and image sequences consistent with the 3D mesh; unifying the 3D mesh, camera pose, and 3DGS model to the same world coordinate system; and using Z-buffer rasterization to output pixel-by-pixel depth and validity masks; generating RGB images of the corresponding viewpoint in the 3DGS renderer; and encapsulating the dataset according to a recommended data organization structure. This invention can accurately generate realistic RGB and geometrically accurate depth, with strict pixel alignment between the RGB images and depth maps, adapting to the needs of real-world application scenarios such as UAV aerial surveying and actual terrain mapping.

The present application relates to the technical field of simulation sandbox, and particularly relates to a simulation sandbox data base construction method and device, wherein the method constructs compatible domain object models in the localization BIM forward design stage; according to unstructured drawings, localization BIM models and other data types, SHP data, geometric feature data and structured topology data are extracted or generated; simulation element data is obtained through field-level direct mapping, SHP data is converted twice and coordinates are unified, and then geometric feature completion, line segment merging and topology reconstruction are performed, object construction and labeling are completed based on the simulation element data, and simulation sandbox data base is obtained. The present application solves the problems of low construction efficiency, poor compatibility and insufficient geometric accuracy, realizes standardized data processing and efficient construction, can be directly loaded into a simulation sandbox, is suitable for airport and other scenes, and improves simulation accuracy and reliability.

This invention belongs to the interdisciplinary field of computer vision and 3D reconstruction, specifically relating to a generative 3D reconstruction method and system based on global constraints of location information. The method includes the following steps: S1, inputting multi-view UAV image sequences into a pre-trained feedforward neural network, which predicts sparse point clouds and the camera pose for each image; S2, extracting GNSS location information from the image sequence and using it as a global constraint to jointly optimize the sparse point cloud and camera pose, obtaining optimized point clouds and optimized camera poses in an absolute geographic coordinate system; S3, based on the optimized point cloud, employing a 3D Gaussian splashing method and utilizing the optimized camera pose for differentiable rendering optimization, generating a realistic 3D model with absolute geographic coordinates. This method, while ensuring 3D reconstruction accuracy, rapidly generates a geographic coordinate system 3D model, providing an efficient and scalable technical solution for city-level realistic 3D construction.

This invention relates to the field of image recognition technology, specifically to a tumor detection and recognition method and system based on MRI images. The method includes the following steps: screening candidate lesion regions based on a gradient orientation stability matrix; constructing a spatial projection displacement map; establishing a dynamic boundary framework by combining boundary variation rate; dividing into levels according to a sequence morphological consistency matrix; and performing differential reshaping to generate recognition results. This invention, by constructing a gradient orientation stability matrix and an anisotropy scoring mechanism, quantitatively evaluates the distribution of pixel vector angles; utilizes spatial projection displacement maps and boundary variation rate analysis to dynamically capture structural continuity features between slices; automatically eliminates artifact interference and constructs a high-fidelity dynamic boundary framework; divides into differential levels by combining a sequence morphological consistency matrix; and performs mean adjustment and edge reshaping for regions with different confidence levels. This improves the geometric accuracy and structural integrity of tumor lesion recognition under complex imaging conditions.

The utility model discloses a kind of internal gear gear grinding machine workpiece main shaft device, comprising: worm gear mechanism, and worm mechanism, wherein, the worm gear mechanism includes: workpiece main shaft, workpiece main shaft box is installed on the workpiece main shaft, index worm wheel is installed on the workpiece main shaft;The worm mechanism includes: double floating worm, the double floating worm is engaged with the index worm wheel, the end of the double floating worm is connected with power mechanism, and the power mechanism is installed on the workpiece main shaft box. By designing a set of meshing side gap adjustable high-precision double floating worm gear mechanism inside headstock, the precision of main shaft can be adjusted during working process, so that transmission efficiency is high, can bear larger load and torque, realize smooth transmission, and adjustment is simple, convenient for later maintenance.

This application relates to the field of intelligent mining technology and discloses a method for constructing a digital model of an automated mining face. The method includes: collecting the coordinates of roadway targets and the dip control points of the cutting face; selecting three points to construct a reference plane reflecting the strike and dip of the coal seam; calculating the normal offset of the dip control points relative to the reference plane, constructing an interpolation function and performing spatial mapping to generate a coal seam floor surface; recursively generating multi-segment surfaces along the advancing direction and constructing a three-dimensional solid model in conjunction with the coal thickness; during the mining process, calculating the error between the measured data and the model, decomposing the error into trend and fluctuation terms, and introducing spatial attenuation weights to dynamically correct unmined areas. This invention, by combining a reference plane and offset mapping, takes into account both macroscopic occurrence and local undulation characteristics, and achieves closed-loop updating of the model through error decomposition, thereby improving the accuracy and environmental adaptability of the geological model.

This invention discloses a multi-objective Bayesian process parameter optimization method for selective laser melting (SLM) based on geometric feature weighting, belonging to the field of laser selective melting additive manufacturing technology. The method involves inputting an STL model of the part, extracting its geometric features, and assigning corresponding sensitivity weights based on these features to construct a spatial weight field. A weighted multi-objective function coupled with the spatial weight field is established with the optimization objectives of maximizing density, minimizing dimensional error, and minimizing surface roughness as the goals. Experiments are conducted on the process parameters based on Bayesian optimization to search for the Pareto front solution set under the weighted multi-objective function. The Pareto front solution set is then sorted using multi-objective decision-making to select the optimal parameter combination and generate a processing card for forming and manufacturing in a laser selective melting device. By explicitly writing geometric sensitivity into the weighted multi-objective function, a Pareto front that considers ρ, δ, and Ra can be obtained with a small number of experiments. Furthermore, the method can automatically weight parameters according to geometric features, simultaneously optimizing ρ, δ, and Ra while also considering geometric feature sensitivity.

This invention provides a method for processing a tapered roller bearing cage. Step one: The sheet metal is cut, stretched, punched with window holes, edge-machined on the large end face, and then the bottom is cut to form a cage blank. Step two: The window beam is beveled to create a guide slope that contacts the rolling elements. The guide slope of the cage meets a first surface roughness requirement, while the remaining non-working surfaces of the cage only need to meet a second surface roughness requirement, which is higher than the first. Step three: A protective component is placed over the window holes of the cage blank, with the coverage area of ​​the protective component being larger than the beveled surface after finishing. Step four: The covered cage blank undergoes two shot blasting treatments. If the surface quality of the cage does not meet the requirements, the surface treatment process parameters need to be adjusted for a third shot blasting treatment. This method solves the problems of low efficiency and high cost associated with the existing all-around finishing process for bearing cages.

This invention provides a bridge-building machine and its operating method, relating to the field of bridge-building machines. The bridge-building machine includes at least two parallel main beams, the ends of which are supported on corresponding traveling devices. Each traveling device includes a traveling beam anchorable to the top surface of the bridge. The traveling device also includes two hanging wheel assemblies, at least two supporting wheel assemblies, and a drive assembly. The drive assembly is mounted on the traveling beam and includes a drive motor and gears, the gears meshing with a rack at the bottom of the main beams. Hydraulic support legs are also provided on both sides of the main beams, capable of supporting the ground. This invention improves the stability and efficiency of the bridge-building machine's movement.

The invention relates to the technical field of semiconductor product processing, and discloses a silicon wafer grinding machine for semiconductor manufacturing, which comprises a lower fixing piece and an upper fixing piece, a drum; a driving assembly; and a plurality of groups of grinding assemblies are mounted in the rotary drum, the grinding assemblies are located on the outer side of the silicon wafer, and the drum body drives the grinding assemblies to be close to the edge of the silicon wafer. By arranging the rotary drum, the driving assembly and the multiple sets of grinding assemblies, under the action of the rotary centrifugal force of the rotary drum, gravity balls move outwards in the radial direction to drive the drum body to move downwards, and therefore the multiple grinding tiles are synchronously driven to be fed inwards in the radial direction at equal intervals, and uniform grinding of the edge of a silicon wafer is achieved; when ovality or local protrusions exist in the silicon wafer, only the protruding part makes contact with the grinding tile and is removed preferentially, so that the edge roundness of the silicon wafer is synchronously corrected in the grinding process, and the geometric accuracy of the silicon wafer and the alignment reliability of the follow-up process are effectively improved.

This invention belongs to the field of image processing technology, specifically relating to a method and system for detecting defects in drainage pipes based on image processing. The method includes: acquiring an image of the drainage pipe surface; extracting the highlight center skeleton line of the highlight region in the image; selecting multiple sampling points along the skeleton line; generating a vertical cross-sectional line at each sampling point and extracting cross-sectional data; fitting a Gaussian function model based on the cross-sectional data of each sampling point to obtain the optimal standard deviation and calculating the light band width; calculating the kurtosis coefficient based on the cross-sectional data of each sampling point; and weightedly fusing the light band width and kurtosis coefficient to generate a flattening factor, which is then compared with a threshold to determine the defect. This invention effectively decouples the three-dimensional deformation information from the two-dimensional grayscale features, significantly improving the accuracy of detecting flattening defects in drainage pipes.

This invention discloses a transmission line sag monitoring system based on multimodal fusion, comprising: a multimodal data acquisition and preprocessing module for acquiring multimodal raw data sets, performing data preprocessing, and generating a multimodal observation set; a physical parameter set calculation module for calculating and generating a physical parameter set; a multimodal collaborative feature modeling module for constructing and running an improved MCAT model to generate fused feature representations and initial geometric reconstruction results; a parameter-differentiable physical error supervision module for calculating observation residual terms and generating differentiable losses; a joint iterative optimization module for performing joint iterative updates; a sag and external damage discrimination module for generating a set of sag and external damage monitoring results; and a data fusion and alarm output module for performing visualization, historical trend query, and alarm output. This invention improves the accuracy and reliability of transmission line sag monitoring.