183 results about "Planar projection" patented technology

The invention discloses a visual data-based automatic finite element modeling and performance evaluation method for an existing damaged hollow slab girder bridge. The method comprises the steps of S1, acquiring complete three-dimensional point cloud data of a multi-beam-slab model; s2, based on the three-dimensional point cloud data, extracting key geometric features of the structure by adopting a structure three-dimensional size automatic measurement method fusing plane projection and point cloud distortion correction; s3, for the damaged area of the multi-beam-slab structure, identifying the boundary of the damaged area and the non-damaged area of the multi-beam-slab structure through a point cloud neighborhood point height difference comparison and clustering analysis method, and carrying out detailed spatial position analysis on the damage; and S4, a damage unit set is automatically retrieved in combination with damage positioning quantitative information, and automatic updating of hinge joint damage of the multi-beam-slab structure is achieved through a life-death unit method failure damage area finite element grid. According to the method, automatic finite element modeling and evaluation of the existing hinge joint damage multi-beam-slab structure are achieved, and an efficient and accurate technical means is provided for health monitoring and performance evaluation of a bridge structure.

The invention provides a welding obstacle avoidance path planning method and system based on artificial intelligence, and relates to the technical field of data processing, and the method comprises the steps: carrying out the penetration depth detection of a dynamic convex hull body and a discrete space sampling set, and generating collision probability density distribution; the collision probability density distribution is subjected to quality evaluation, welding gun posture constraint and a kinematics error transfer chain are fused, and a welding quality deviation functional is generated; analyzing high-deviation nodes in the welding quality deviation functional, and executing local tangent plane projection on the associated spatial sampling subsets to obtain pose compensation parameters; and the pose compensation parameter and the joint space motion primitive sequence are input into a kinematics inverse solution module, and an optimized welding gun motion parameter set is generated through geodesic line construction and parameterized spline interpolation. The welding efficiency and the quality target are improved, and the automation level of the whole welding operation is improved.

The invention discloses a comprehensive identification method for unsafe behaviors of construction site personnel, and particularly relates to the field of construction site image analysis and identification, and the method comprises the steps: constructing a boundary line segment connection diagram through edge detection and Hough transformation, and generating a risk mask region based on a plane projection track and a buffer zone; performing instance segmentation and attitude estimation on the personnel, extracting joint points and calculating a gravity center point, screening key points according to operation types, and constructing a relative vector sequence; extracting an included angle between a main attitude axial direction of continuous frames and a boundary normal, and generating a direction consistency matrix and a camber behavior mark; and finally, identifying a resident section in the risk mask area and outputting a constriction violation approaching behavior label. A space compression judgment mechanism based on image feature recognition is achieved, and it is ensured that edge approaching type unsafe behaviors existing when constructors conduct different types of work are recognized in advance and subjected to risk early warning.

The invention discloses a rotating body ancient building part model reconstruction method based on a least square method, and relates to the technical field of model reconstruction analysis, and the method comprises the steps: obtaining ancient building part point cloud through employing a three-dimensional laser scanning technology; the historic building part point cloud is sliced and projected to a horizontal plane, a circle is fitted by using a least square method, circle center coordinates are extracted, and the position of a rotating shaft is determined. According to the method, the precision of model reconstruction is effectively improved by accurately extracting the rotating shaft and fitting the rotating generatrix, high-precision point cloud data is obtained by using a three-dimensional laser scanning technology, and accurate extraction of the rotating shaft and the rotating generatrix is ensured through the steps of slicing, projection, least square fitting and the like; a non-uniform rational B-spline curve is adopted to fit a rotating bus, the rotating bus is rotated around a rotating shaft to reconstruct a three-dimensional model, the three-dimensional model of the ancient building part model is parameterized, the geometric accuracy of the model is further improved, and the reconstructed model can more accurately reflect the actual shape and size of the ancient building part.

The invention relates to a photovoltaic monocrystalline silicon material resistivity uniformity evaluation method, and belongs to the technical field of photovoltaic material detection. The method comprises the following steps: evaluating all-form resistivity and doping uniformity of a photovoltaic single crystal silicon rod, a single crystal silicon wafer and a single crystal silicon square wafer; carrying out standardized point distribution on the monocrystalline silicon wafer by using a concentric circular ring and a small circle, and calculating in-plane uniformity by using a triple integral derivation equation; the monocrystalline silicon square pieces are distributed in the form of grid small squares, and in-plane uniformity is calculated by means of a triple integral derivation equation; and for the axial direction of the silicon rod, the uniformity is quantified by utilizing range and variance models through the resistivity of the head, middle and tail wafers. Meanwhile, a continuous grid is generated through interpolation, and a 3D color mapping curved surface diagram with plane projection is drawn to visually present distribution. According to axial and in-plane uniformity results, silicon wafers are classified and graded, the doping uniformity of monocrystalline silicon is accurately reflected, and a support is provided for quality control, process optimization and silicon wafer sorting of photovoltaic monocrystalline silicon.

The invention relates to the technical field of artificial intelligence and digital modeling, and particularly discloses an automatic equipment modeling method and equipment based on artificial intelligence, and the method comprises the steps: obtaining data to construct a multi-modal fusion data set; extracting target features and integrating the target features into a unified high-dimensional feature vector so as to generate a semantic feature map for modeling equipment; obtaining geometric modeling parameters and assembly constraint conditions of modeling equipment by using a parameter optimization model constructed based on a reinforcement learning framework; based on the fault data, optimization is carried out through a Markov decision principle to generate a preliminary 3D model; and performing key point detection and feature alignment on the planar projection of the model and the BIM drawing vector diagram through a hierarchical matching strategy, correcting model deviation based on vertex information to generate a 3D model, and generating a digital twin 3D model. Thus, by means of multi-source data collaborative acquisition and deep feature fusion, the precision, efficiency and adaptability of equipment modeling are remarkably improved in combination with dynamic optimization and a closed loop verification mechanism.

The present invention provides a method for extracting features of the nearshore wave breaking process based on time series video images; wherein, the method comprises: setting at least one pixel sampling area in a plane geographic coordinate system, collecting time series video images of ocean nearshore waves, quickly converting them into plane geographic coordinate images through a coordinate model, and then stacking cross-shore pixel values ​​of several pixel sampling areas within a set time to generate a cross-shore pixel value and time relationship sequence diagram, mining the time-varying signal of the wave propagating toward the shore, combining the geometric relationship between the camera angle of view and the plane projection of the wave breaking, and calculating key wave breaking features such as the wave breaking point position, wave breaking water depth, and wave breaking height; the method can continuously monitor the nearshore wave breaking features efficiently, automatically, and stably, effectively making up for the shortcomings of traditional monitoring and analysis methods, and providing strong technical support for the refined research and management of nearshore beach dynamic landforms.

The invention discloses a welding seam track identification method for impeller wrap angle welding based on point cloud data, and belongs to the field of machine welding seam identification, and the method comprises the following steps: carrying out filtering, down-sampling and clustering on original scanning point cloud; classifying the point cloud data through a region growing clustering algorithm; determining an optimal interception plane based on principal component analysis, and performing curve fitting on section data to obtain a preliminary main welding seam track; the main welding seam track is projected to a local approximate plane in a segmented mode, and accurate extraction of the main welding seam track is completed; and performing plane fitting and thickness calculation on the wrap angle surface, solving an intersection line in combination with an adjacent local approximate plane, calculating an intersection point of the intersection line and the main welding seam track, and finally generating a wrap angle welding seam track in combination with the direction of the intersection line and the wrap angle thickness. Through cooperative calculation of local plane projection and spatial intersection line solving, the whole process operation from recognition, planning to welding can be automatically completed, and unmanned intelligent welding in the true sense is achieved.

A depth image of items on a scale are captured. Depth information for the depth image is processed to produce a three-dimensional (3D) map of the depth information. The items are identified as blobs within the 3D map. A plane is generated and projected into the 3D map and each separate blob that intersects the plane is counted to determine an item quantity for the items depicted in the original depth image. The item quantity is provided back to a terminal for item quantity verification of the items during a checkout transaction at the terminal. In an embodiment, the plane is projected onto the 3D map and animated to move from a top of the 3D map to a bottom of the 3D map while the separate blobs are counted for the item quantity determination as the plane moves.

The invention relates to a large-scale point cloud denoising method based on longitudinal interlayer density and spatial connectivity constraint, and the method comprises the steps: carrying out the hierarchical division of large-scale point cloud data, obtaining a point cloud set of different height spaces, and solving a plane projection area; performing discrete noise removal on the point cloud set by using point density and connectivity clustering to obtain a denoised point cloud set; performing plane mapping on the denoised point cloud set to obtain a corresponding relation between each point cloud and a plane projection pixel; solving a density feature operator of each pixel of plane projection based on the corresponding relation, and calculating a point cloud interlayer projection matrix based on the density feature operators; summarizing all the point cloud interlayer projection matrixes and performing point cloud interlayer connectivity check to obtain an updated point cloud interlayer projection matrix; and performing point cloud restoration and splicing based on the updated point cloud interlayer projection matrix, and outputting large-scale point cloud data after noise reduction. According to the invention, the effect of the point cloud denoising technology is improved.

The invention discloses an overhead power line icing thickness detection method and system based on a structure perception framework, and the method comprises the steps: firstly obtaining point cloud data of a power transmission line, preprocessing the point cloud data, and inputting the preprocessed point cloud data into a structure perception semantic segmentation network; the network adopts a four-level encoder-decoder architecture, an encoder extracts multi-scale features through local space encoding, cross-scale space attention fusion and local aggregation operation, and a decoder realizes feature fusion in combination with a jumper connection mechanism and outputs a lead semantic segmentation result; extracting a conductor point set based on a segmentation result and carrying out Euclidean clustering strand splitting; performing biplane projection and polynomial fitting on each strand of wire to construct a three-dimensional center line; and finally calculating the distance from the point to the center line, selecting a peripheral point set to calculate the wire envelope radius, and combining the radius of the bare wire to obtain the icing thickness. Measurement deviation caused by point cloud shielding, wire bending and asymmetric icing is effectively solved, millimeter-level precision non-contact ice thickness detection in a complex environment is achieved, and reliable technical support is provided for power grid disaster prevention.

The invention provides a slope excavation engineering quantity calculation system and method based on point cloud, and the method comprises the steps: reading the slope geological data of hydropower engineering to construct an initial three-dimensional model, and collecting the multi-stage point cloud data through a three-dimensional laser scanner; performing equidistant gridding on the point clouds of the model region according to an X / Y axis, calculating the spatial similarity and color similarity of the point clouds in grids, and dividing sub-data sets according to threshold values; fitting an excavation surface through a Delaunay triangulation network, calculating an XY plane projection area, and calculating an average Z-direction distance from a subset to the surface of the initial model; the node weight of the triangulation network is corrected by fusing rock stratum interface parameters, finally, the excavation engineering amount is dynamically output through summation of the product of the projection area of each subset and the average distance, and when the deviation of adjacent stages exceeds 10%, cross validation is conducted in combination with a profile method. According to the method, the precision and the real-time performance of slope excavation engineering quantity calculation can be improved, and automatic integration of lithologic characteristics and mechanical attributes is realized.

The invention discloses a cylinder-like surface local defect detection method and a related device, and the detection method specifically comprises the following steps: obtaining three-dimensional point cloud data, dividing the three-dimensional point cloud data into a plurality of uniform slices according to a height range, and each slice only comprises data points belonging to a specific height range; carrying out plane projection on the sliced three-dimensional point cloud data, and carrying out gray processing and binarization processing on a projection image to obtain a binarized image; extracting upper and lower contour points in the binarized image, and performing circle fitting on the lower contour points by using a least square method to obtain a fitted circle; distance information between the upper contour point and the fitting circle and distance information between the lower contour point and the fitting circle are calculated respectively, the calculated distance information is compared with a preset threshold value, and cylinder-like surface local defect detection is achieved. According to the method, technologies such as slicing, projection and geometric fitting are comprehensively utilized, and the accuracy and efficiency of defect detection can be effectively improved.

The present invention discloses a robust optimization method for autonomous optical navigation landmarks for planetary landing, which belongs to the field of deep space exploration technology. The implementation method of the present invention is as follows: using the height information of the lander to determine the scale of the image plane projected onto the planetary surface, and deriving the quadrilateral vertex expression of the field of view based on the geometric relationship; using the relationship between the field of view vertex deviation and the lander posture error, converting the posture uncertainty to the field of view vertex uncertainty, and using the error ellipse to describe the field of view vertex uncertainty distribution; screening the quadrilateral area formed by the intersection of common tangents, which is the field of view intersection under the lander posture uncertainty; using the nominal trajectory and camera parameters to estimate the field of view sequence, combining the field of view intersection acquisition method to obtain the field of view intersection sequence, the field of view intersection sequence is obtained by offline estimation, and the amount of onboard calculation of the lander is reduced; using the observability of the navigation system to establish the landmark optimization index, optimize the selection of the landmarks in the field of view intersection sequence, and reduce the influence of posture uncertainty on the selected landmarks.

The invention discloses a vision and inertial navigation integrated navigation method, system and equipment in a weak vision environment and a medium, and belongs to the technical field of navigation, by fusing an inertial measurement unit and landmark focal plane projection data, the navigation precision of the system under the adverse conditions of low texture, dynamic shielding and the like is remarkably improved, and the navigation continuity can be maintained; according to the method, an indirect Kalman filter is used for carrying out feedback correction on initial navigation parameters, noise interference and inertial navigation accumulative errors are effectively inhibited, navigation errors are remarkably reduced for state estimation, and the robustness and adaptability of the system are enhanced; the method does not depend on complete visual resolving, landmark projection coordinates are directly used, dependence on visual information integrity is reduced, and the system can stably operate even if only a small number of landmarks or a single landmark is visible.

A large-scale point cloud-oriented two-dimensional regularized planar projection method and an encoding and decoding method are disclosed. The two-dimensional regularized planar projection method includes: obtaining original point cloud data; initializing a two-dimensional projection plane structure of a point cloud; and determining a mapping relationship between the original point cloud data and the two-dimensional projection plane structure to obtain a two-dimensional regularized projection plane structure corresponding to the point cloud. The encoding and decoding method includes: predicting based on the two-dimensional regularized projection plane structure of the point cloud to obtain to-be-encoded data; dividing the to-be-encoded data into a first type of to-be-encoded data and a second type of to-be-encoded data; and encoding different data in the first type of to-be-encoded data separately in a preset encoding manner, and correspondingly encoding the second type of to-be-encoded data, to obtain a geometric information bitstream.

The invention relates to a power transmission line icing thickness measurement method based on a YOLOv8 segmentation algorithm. The method comprises the following steps: S1, obtaining a group of icing pictures with positioning information; s2, acquiring the total number P2 of icing pixel points and the total number of picture lead pixel points; s3, calculating a plane projection distance d between the unmanned aerial vehicle and the iron tower; s4, counting the total number P1 of manually labeled lead mask pixels; s5, acquiring related parameters according to a camera imaging principle; s6, according to the triangle similarity principle and the related parameters, calculating the proportion of the image wire diameter X to the actual wire diameter Wr; s7, calculating the diameter D of the actual wire; s8, calculating the ice coating area S of the actual wire; and S8, calculating the actual conductor icing average thickness b. According to the method for measuring the icing thickness of the power transmission line, the danger of manual observation is avoided, the operation risk of personnel in a severe environment is reduced, and compared with a traditional method, the cost is low, and application and popularization are easy.

The invention discloses a power transmission line multi-mode cooperative sensing method, a mechanical intrusion early warning method and system and a storage medium, and the sensing method comprises the steps: constructing a reference coordinate system, and projecting multi-source data into the reference coordinate system; calling a tension-length coupling correction operator, and carrying out static equilibrium iteration solution on the design span to obtain a three-dimensional conductor sag physical prior curve; inputting the conductor sag physical prior curve and a historical curve in a sliding window of a preset period into a space-time continuous network, and outputting a conductor continuous sag curve in a span range; the method comprises the following steps: respectively cutting interest areas in a visible light image frame and a 4D three-coordinate radio frequency radar frame by taking plane projection of a conductor continuous sag curve as guidance, respectively extracting conductor optical anchor points and conductor radar candidate points, and generating a conductor fine three-dimensional point array in a span range through a medium radian conservation progressive registration operator; according to the invention, centimeter-level precision sensing can be maintained under extreme high-low temperature and complex load conditions.

The invention discloses an airborne laser radar point cloud inverted tree detection method and device and electronic equipment, and the method employs a deep learning semantic segmentation model to process a first point cloud, can precisely distinguish an inverted tree trunk from ground cover objects, rocks and other sundries, remarkably reduces the false detection rate, and guarantees the accuracy of target recognition. And then, a two-dimensional plane projection image is generated based on the second point cloud, so that the problem of discontinuity caused by bending and fracture of the three-dimensional point cloud can be avoided, structured input is provided for subsequent target detection, and the continuity of the detection process is ensured. Afterwards, target detection is carried out on the two-dimensional plane projection image, fragmented missing detection caused by point cloud discontinuity can be avoided, and the overall recognition capability (high recall rate) of the inverted tree is greatly improved while high detection accuracy (low false positive) is kept. And finally, mapping a two-dimensional detection result back to a three-dimensional space, so that three-dimensional point cloud data of a complete inverted tree can be obtained, and a high-density point cloud environment can be adapted more effectively.

Disclosed are a point cloud encoding and decoding method and device based on a two-dimensional regularization plane projection. The encoding method includes: acquiring original point cloud data; performing two-dimensional regularization plane projection on the original point cloud data to obtain a two-dimensional projection plane structure; obtaining a plurality of pieces of two-dimensional image information according to the two-dimensional projection plane structure; and encoding the plurality of pieces of two-dimensional image information to obtain code stream information.

A projection image adjustment method includes: acquiring a first captured image corresponding to a first device including a first lens by capturing an image of a plane projection surface on which a first pattern image including at least four unit images is projected from a first projection device; acquiring a second captured image corresponding to a second device including a second lens by capturing an image of the projection surface; acquiring, based on the first captured image and the second captured image, a projective transformation matrix indicating transformation from a first coordinate system in a first device to a second coordinate system in a second device; and acquiring a plane parameter of the projection surface by using the projective transformation matrix.

The present application discloses an image stabilization correction method for capsule gastroscopy image acquisition, which relates to the technical field of medical diagnosis, and includes the following steps: image acquisition: taking the original image of the stomach wall through a capsule endoscope; image preprocessing: performing data enhancement processing on the original image, and then performing plane projection processing to obtain a two-dimensional projection plane image; generating a coordinate sequence: extracting a feature point sequence of the two-dimensional projection plane image, and generating a matching feature point pair coordinate sequence; correcting the lens posture: by calculating the lens posture, generating an image data sequence after posture correction, and correcting the lens posture; generating a stable image sequence: by calculating the path of the device, forming a lens space posture control sequence, thereby eliminating images that deviate from the predetermined path, and forming stable and reliable image data. The present application can make the acquired image more stable and reduce the impact of rotation and shaking on the image.

The present application belongs to the technical field of catheter positioning, and relates to a precise positioning method based on a catheter model. The core technology of the present application is to determine the position of a positioning clamp through plane projection of a three-dimensional model of the catheter and basic data measurement, and to complete the manufacturing of the positioning clamp after adjusting the positioning clamp device to the target position according to the data calculated after measurement. The method can accurately and effectively control the shape of the catheter part, and the positioning devices can be repeatedly assembled and utilized.

The invention discloses a non-line-of-sight positioning method based on obstacle vectorization and distance measurement cross validation, which belongs to the technical field of wireless positioning and comprises the following steps: step 1, calculating a height difference according to the installation height of a base station and the preset height of a to-be-estimated label, and calculating a plane projection distance value according to the height difference and a TOF distance measurement value; 2, constructing a signal path according to a to-be-estimated label positioning result at the previous moment and the position of each base station, judging the penetration condition of the path by combining a vectorized obstacle map, and performing compensation and reliability screening on the plane projection distance based on the penetration condition to obtain a credible distance measurement value set; 3, solving and calculating a positioning residual error through multi-base-station combined positioning, and carrying out weighted fusion on a solving result according to the residual error to obtain an initial positioning result at the current moment; according to the invention, high-precision positioning can still be kept near the base station and in complex scenes such as multi-shielding and the like, and the application requirement of a shielding environment is met.

A computer-implemented method and system relate to an image encoder that receives a digital image as input. The image encoder generates a weight map using the prior feature map. A prior feature map is generated using pixels of the digital image. A weight map is generated based on Lie data associated with the digital image. The homography is interpolated between the two planar projections of the digital image using at least the weight map and the homography matrix. The homography matrix provides a mapping between two planar projections of the digital image. A homography kernel is generated by applying homography to the convolution kernel. A homographic transform kernel is applied to the prior feature map to convolve different planar regions appearing in the digital image, and a new feature map is generated for computer vision tasks involving three-dimensional (3D) perception.

This invention provides a method for measuring the depth of ultrasonic welding craters based on three-dimensional point clouds, belonging to the field of engineering measurement technology. The method combines two-dimensional and three-dimensional point cloud data fusion detection, overcoming the poor anti-interference capability of traditional two-dimensional image measurement methods. It can operate stably in complex welding environments, ensuring the reliability of the detection results. Simultaneously, by employing a spectral confocal sensor and three-dimensional point cloud technology, the three-dimensional morphology of the welding surface can be accurately captured. Noise is effectively eliminated through point cloud quantile filtering and MAD denoising technology, improving the accuracy of crater depth measurement. Furthermore, this invention automates the crater depth measurement process through various advanced algorithms (such as point cloud quantile filtering, percentile interpolation screening, and plane projection segmentation), reducing the need for manual intervention and improving detection efficiency.

This invention discloses a chemical plating batch clamping fixture based on structural constraint and its application method, belonging to the field of fixture technology. The fixture includes at least one clamping unit, comprising an upper frame, a lower frame, and isolation columns connecting the upper and lower frames. After assembly via the isolation columns, the upper and lower frames have corresponding hollow structures. The contour of the hollow structures matches the planar projection contour of the workpiece. A sandwich structure exists between the upper and lower frames. Longitudinal and transverse protrusions are provided around the hollow structures to constrain the parts within the hollow structure area. Based on the principle of physical interference, the fixture is highly effective in preventing the flipping of lightweight, small parts, eliminating damage to the parts, and is particularly suitable for precision parts.

Tray (21) having a cardboard base (1) and at least a first wall (3a) and a second wall (3b) formed by a first layer and a second layer each having at least one hole (6), the second layer of the first wall having a first planar projection (12), forming an angle with the first wall of between 30° and 90° arranged to retain a first embossing of a lid, the second layer of the second wall having a second planar projection forming an angle with the second wall of between 30° and 90° to retain a second embossing of the lid.

The present invention relates to the technical field of three-dimensional plane projection. Specifically disclosed are a plane projection method and plane projection apparatus on a surface of a three-dimensional object. The method comprises: determining a projection distance of a projection apparatus; determining a projectable range on the basis of the projection distance; performing plane segmentation on a three-dimensional object for projection, so as to obtain a plurality of sub-planes; on the basis of the sub-planes and the projectable range, determining an arrangement mode of the projection apparatus; and arranging a plurality of projection apparatuses on the basis of the arrangement mode, and executing a screen projection operation on said three-dimensional object by means of the plurality of projection apparatuses. By improving a conventional screen projection method, a surface of a three-dimensional object is segmented, and projection is separately performed on different sub-planes, thereby ensuring sufficient projection clarity and satisfying actual requirements.

The invention discloses a CT image-oriented implant space attitude estimation method, and belongs to the technical field of biomedical engineering and computer science. The method comprises the following steps: extracting a target three-dimensional model based on a CBCT image; the CBCT image is obtained by performing cone beam scanning on a target part where an implant is placed during or after an operation; obtaining an implant theoretical model pre-constructed for the implant; the mass center of the target three-dimensional model and the mass center of the implant theoretical model are calculated respectively, and the mass center of the target three-dimensional model and the mass center of the implant theoretical model are aligned; registering the target three-dimensional model and the implant theoretical model of which the mass centers are aligned by utilizing a main shaft rotating mode; and evaluating the registration precision based on multi-plane projection and similarity measurement, and outputting spatial attitude parameters of the implant. According to the method, the registration speed can be increased, the calculation complexity in the registration process is reduced, and the space registration precision can be further improved through a two-stage optimization strategy of centroid alignment and main shaft rotation.