62 results about "Curve reconstruction" patented technology

The invention discloses a prediction and evaluation technology of 3D seismic optimum time window river channel sand body reservoirs, belongs to the technical field of the prediction and evaluation of the 3D seismic reservoirs, and aims at solving technical problem that the river channel predictive resolution of the traditional methods is not enough. The technical proposal is as follows: the 3D visualization scanning is performed on each reservoir at the interval of 1-2ms, the optimum time window is determined according to the scope shown by the target river channel, the corresponding subfield is cut out, clairvoyance and scanning are carried out on the time window properties, such as root-mean-square amplitude, wave impedance and the like, auto-tracing is performed, top surface and bottom surface are picked up, a time isopach map is calculated and converted into a sand body isopach map, a top surface structure diagram is formed by time-depth conversion, and the reservoir physical properties are evaluated by curve reconstruction, thus realizing the prediction and evaluation of the plane morphology, longitudinal thickness and the reservoir physical properties of the river channel sand body. The method adopts the optimum time window to effectively inhibit interference, is applicable to various data volumes, and can effectively predict and evaluate a thin river channel sand body with the thickness far less than 1 / 4 of a wavelength under the condition of frequent interbedding of sand and mudstone, the thin river channel sand body comprises the river channel sand body which is not corresponding to wave crest or wave trough, and the method has good application effect in petroleum exploration and development.

This invention disclosed a three-dimension measurement method which consists of preparation, picture intussusception, coding spot identification, camera location confirmation, target curve pick-up, homonymic curve matching and target curve reconstruction. It has the following characteristics: mark on the target curve before measuring to make the picture identification much more easy; place a guage and a set of coding spots around the target object; screen randomly to obtain a set of image by the camera; calculate automatically the position and gesture of the camera according to the images; pick up the marked curve and match the homonymic curve in different images so that the information of three-dimensional spot line was automatically calculated.

A system and method for modifying a curved cut plane of a 3D volume to locate objects or sections of interest within the 3D volume intersected by the cut plane. A cross-section of the 3D volume along an initially estimated curved cut plane is projected onto a flat viewing plane, and a panorama image of the cross-section is displayed to the user. If the initially estimated curved cut plane does not exactly intersect the object or section of interest, the user manipulates a user input device to modify the curve of the plane inward or outward in the 3D volume away from the projected plane. As the user manipulates the user input device, an affected portion of the curve is recalculated and a modified curved cut plane is reconstructed based on the recalculated curve for re-projecting a modified cross-section of the 3D volume in real time with the movement of the user input device. The user is therefore provided with instant visual feedback as the user moves the user input device to browse in and out within the 3D volume from the current projected plane.

A dynamical image of is an array of black-and-white images, or frames, of arbitrary dimension. Dynamical images are constructed from gray scale and color images, video sequences etc. A method of topological analysis and decomposition of dynamical images through computation of homology groups of the frames is provided. Each frame is partitioned into a collection of components, which, in turn, have tunnels, voids, and other higher dimensional cycles. The cycles in each frame are linked to the cycles in each adjacent frame to record how they merge and split. Further, the dynamical image is simplified by removing from frames all cycles that are small in terms of length, area, volume, etc, or lifespan. Applications of the method lie in image enhancement and restoration, motion tracking, computer vision, surface and curve reconstruction, scientific image analysis, image recognition and matching.

The invention discloses a point cloud based quick reconstruction STL digital model generation method. The method includes performing simplified filtering and characteristic extraction on input point cloud; performing curve reconstruction on surface point cloud on a digital model; establishing a model topologic relation on the STL digital model and performing grid simplification; performing hole detection and repair on the simplified STL digital model so as to remove defects in the model. According to the invention problems of laser scanning point cloud based STL model reconstruction can be solved effectively. The STL model is generated through steps including point cloud characteristic extraction, model reconstruction and the like and automatic repair of surface defects of the generated STL model is realized through grid simplification and hole repair technology, so that quick reconstruction of the STL digital model is realized and the availability of the reconstructed STL digital model is improved in the premise of keeping basic characteristics of point cloud, and great demands in different fields such as robot offline programming technology, automatic track planning technology and the like in a smart manufacture process can be met.

The invention relates to a method for reconstructing an interval transit time curve by virtue of multiple logging curves. The method mainly comprises the steps of selecting a plurality of logging curves obvious in response to reservoir characteristics by performing reservoir sensitivity and correlation analysis on the logging curves; performing discrete wavelet decomposition on the logging curves together with a sonic wave curve to form 8 decomposition layers; enabling all the layers of high-frequency decomposition results of other logging curves except the sonic curve to form matrices respectively, obtaining the corresponding characteristic values and characteristic vectors of the matrices; taking the characteristic vectors corresponding to different characteristic values as new components, which, at the moment, have orthogonality (correlation ); performing multivariate regression analysis on the high-frequency components of the corresponding layer of wavelet decomposition of the sonic curve by utilizing characteristic vectors of each layer, calculating a weighting coefficient corresponding to each vector, returning a regression significance analysis result and determining the quality of regression; next, determining the number of layers of the sonic high-frequency components to be reconstructed by virtue of the characteristic vectors according to the regression significance analysis result, selecting multiple regression results as the high-frequency components for a part having more layers than selected layers, and remaining the high-frequency decomposition results of the sonic logging curves for a part having less layers than the selected layer, and then carrying out curve reconstruction by using the low-frequency components of the sonic logging curves and the high-frequency components obtained through regression so as to obtain a final sonic reconstructed curve.

The invention provides a well logging characteristic curve reconstruction method of a gravel rock based on rock core scale well logging. The method comprises the following steps of dividing a core taking segment into a mudstone clamping thin layer sandstone segment, a gravel rock and mudstone interbedding segment and a gravel-rock thick layer segment; dividing the mudstone clamping thin layer sandstone segment, the gravel rock and mudstone interbedding segment and the gravel-rock thick layer segment on a well logging curve; comprehensive analyzing a characteristic of each well logging curve and searching characteristics of the above three segments on each curve; finding a sensitive curve reflecting different lithology of the three segments; carrying out baseline rotation on a special segment which is obviously inclined of a mudstone baseline in the sensitive curve; and based on special segment mudstone baseline rotation, carrying out reconstruction of a full well segment of the well logging characteristic curve. By using the well logging characteristic curve reconstruction method of the gravel rock based on rock core scale well logging, a problem that a measured curve can not represent a reservoir layer characteristic is solved; precision of gravel rock reservoir layer inversion is guaranteed and gravel rock reservoir layer inversion quality is increased.

The invention provides a lane line reconstruction device based on Bezier curve. According to the lane line reconfiguration device based on the Bezier curve, an initial point search module receives front road environment images of vehicles and searches blocks where initial points of a left line and a right line are located, a forward search module searches blocks where outer side edge lines of all lane lines are located, an interruption search module searches blocks where initial points of interrupted are located, a direction-changing search module searches blocks where outer side edge lines of turning lane lines are located, and all the blocks are processed by an adaptive binaryzation module to obtain a plurality of points on the outer side edge lines of the lane lines, a lane sort module sorts the lanes, and a Bezier curve fitting module fits and constructs the lane lines by using a quadric Bezier curve. The lane line reconstruction device based on the Bezier curve can well adapt to complex environments such as illumination variation, road shadow, lane line interruption and obstacles, does not need preprocessing of images and improves the instantaneity and the accuracy of variable curvature curve reconstruction.

The invention provides a lane line reconstruction method based on Bezier curve and used in the field of safe auxiliary driving of intelligent vehicles. The method provided by the invention comprises the following steps: searching the position of a starting block of a lane line in images inside an interested region on the basis of gradient characteristic and grayness characteristic, extending the searching in a block form, introducing a lane line intermittent searching mechanism and a curve searching mechanism, so as to achieve intermit and curve recognition; carrying out self-adaptive binaryzation treatment to all recognized blocks respectively so as to obtain points on the lane line; and respectively adopting one or two secondary Bezier curve fitting lane lines according to degree of crook of lane line. The method provided by the invention can well adapt to complex environment such as lighting variation, road shadow, lane line interruption, barriers and the like, pretreatment to images is not required, the real-time performance is improved, segmental Bezier curve fitting lane lines are adopted for improving the accuracy of variable camber curve reconstruction.

The invention discloses a battery SOH evaluation method, which comprises the steps of performing charging and discharging test on a battery, and recording test data; performing data processing on thetest data to obtain a V-dQ / dV data point set, and performing filtering and noise reduction; identifying a peak value of the data point set, carrying out segmenting according to the peak value point, and performing polynomial regression on each segment of the V-dQ / dV to obtain an IC curve for qualitatively analyzing a battery attenuation mode; and integrating and then converting the IC curve to obtain a Q-V curve numerical model, performing data verification, and quantitatively analyzing the battery attenuation behavior by calculating optimal voltage curve reconstruction model parameters. According to the method, filtering and nonlinear regression operations are carried out on test data and a calculation result; influence of measurement noise on an analysis result is reduced, the method ishigh in adaptability and is used for various types of lithium ion battery systems, the battery attenuation mode is analyzed in a set and quantitative mode, a reasonable independent variable step length can be set for quantitative analysis, and the calculated amount is greatly reduced. The invention further provides a battery SOH evaluation system.

The invention provides a three-dimensional displaying method for synthetic aperture radar imaging data. The method includes: step A conducting noise reduction and interpolation on received original three-dimensional synthetic aperture radar data M0 (x, y, z, v) to obtain three-dimensional synthetic aperture radar data including target three-dimensional space coordinate information (x, y, z) and back scattering information v; step B conducting three-dimensional curve reconstruction on the three-dimensional synthetic aperture radar data subjected to noise reduction and interpolation to obtain three-dimensional grid data; step C utilizing a three-dimensional graph drawing assembly line to draw the three-dimensional grid data to obtain a three-dimensional graph to achieve three-dimensional displaying of the three-dimensional synthetic aperture radar data. According to the method, the three-dimensional graph drawing assembly line is utilized to draw the three-dimensional grid data to obtain the three-dimensional graph to achieve the three-dimensional displaying of the three-dimensional synthetic aperture radar data.

The invention discloses a multi-level laser-point cloud building boundary regularization method, which is characterized in that filtering is performed on original airborne point cloud, building point cloud is extracted, and orderly boundary points of a building are extracted by adopting an alpha-shape algorithm; and then line segment segmentation and extraction, curve reconstruction and global optimization processing are performed on the boundary point cloud. The method disclosed by the invention solves a problem of regularization for various types of boundaries, and well overcomes influences imposed on regularization by noises.

The invention provides a method for calculating the shale content of a conglomerate oil reservoir based on log curve reconstruction. The method comprises the following steps of (1), measuring the shale content of a rock core sample; (2), optimal selection of sensitivity curves of shale: determining the shale content of the conglomerate oil reservoir and a compensated neutron porosity log curve as well as a compensated density log curve as sensitivity curves for calculating the shale content; (3), normalization processing of the curves: on the basis of the sensitivity curves for calculating the shale content, which are determined in the step (2), carrying out the normalization processing on the compensated neutron porosity log curve and the compensated density log curve respectively; (4), constructing a shale content calculating parameter (NZCS (New Zealand Computing Solution)); (5), establishing and optimizing a calculation model. By using the method for calculating the shale content of the conglomerate oil reservoir based on the log curve reconstruction, which is provided by the invention, the influences of lithology and heterogeneity on a calculation result of the method in the process of calculating the shale content of the conglomerate oil reservoir are eliminated; the calculation precision of the shale content of a reservoir stratum is improved.

A logging curve reconstruction method includes the following steps: firstly, preparing basic data of a logging curve; secondly, rectifying the logging curve, conducting curve standardization and removing abnormal values; thirdly, utilizing a moving smoothing method to conduct high and low frequency separation on the curve; fourthly, carrying out curve high frequency fitting; fifthly, adding the high frequency curve in the fourth step and curve wave low frequency information in the third step together to form a new curve; sixthly, carrying out cross analysis on the curves obtained in the thirdstep, the fourth step and the fifth step; and seventhly, carrying out inversion on wave impedance. No human factor intervention exists during the whole process, no prerequisites are needed, and the method is widely applicable. The method provides explanation workers a universally applicable curve reconstruction technology.

The invention discloses an optical fiber shape reconstruction method based on a Beta frame. The method comprises the following steps: firstly, respectively carrying out bending-free state measurementand bending state measurement on a to-be-measured optical fiber by utilizing a distributed three-dimensional shape sensing system based on an optical frequency domain reflectometer (OFDR), and carrying out cross-correlation demodulation on two groups of signals obtained by measuring whether bending exists or not to obtain a frequency spectrum offset of the whole optical fiber; solving strain values of all positions of the optical fiber by using the spectrum offset, and solving the curvature and the bending angle of the optical fiber by using the relationship between the strain and the curvature and the bending angle; substituting the curvature and the bending angle of the optical fiber into a differential equation of a Beta standard frame to solve the Beta standard frame of each point on the optical fiber; and finally, carrying out tangent vector integration on the curve in the Beta frame to obtain the shape of the optical fiber. According to the method, good curve reconstruction performance can be obtained, and especially when turning point exists in optical fiber bending, reconstruction precision can be obviously improved.

The invention discloses a cross section curve reconstruction method for three-dimensional model reconstruction, which comprises the steps of carrying out segmentation on data points according to curvature information of discrete data, determining corresponding characteristics, and determining an area in which an ideal segmentation point is located; referring to the density of data sampling, determining a reasonable grid division spacing, and carrying out gridding on a target area; firstly fitting a straight line as for each node of the current grid, then fitting a B spline curve based on boundary constraint conditions, and calculating the total error of all data points to the curve and the number of control vertexes of the B spline curve; comprehensively analyzing the two groups of calculated data, and determining a current optimal segmentation point; outputting the optimal segmentation point if the density of the current grid node satisfies the precision; and otherwise, reducing the target area by taking the current optimal segmentation point as a center, reducing the spacing, dividing the grid, and reconstructing a cross section curve according to the current optimal segmentation point.

The invention discloses a three-dimensional road curve reconstruction method based on a vehicle-mounted mobile laser scanning point cloud. The method comprises the following steps: S1, dividing a vehicle-mounted mobile laser scanning original point cloud into a plurality of sections of sub-point clouds; S2, performing road surface extraction on each section of sub-point cloud to obtain a road surface point set; S3, performing road sign extraction on the road surface point set to obtain a road sign point set; S4, clustering the road sign point set to obtain a plurality of road sign sub-point sets; S5, performing shell extraction on each road sign sub-point set to obtain a shell point set; S6, respectively carrying out model fitting on the basic three-dimensional road curve model and the shell point set specified by the standard to obtain candidate curves; and S7, comparing the candidate curves to obtain an optimal curve. According to the method, the type of the road curve can be automatically and robustly recognized and the parameters of the three-dimensional road curve meeting the geometric design standard of the road can be accurately estimated under the condition that a large number of outliers are contained in the data. The method can be applied to the fields of road construction quality evaluation and the like.

The invention discloses a beam structure form reconstruction method based on optical fiber strain measurement. The method comprises the following steps: step 1, acquiring a section torsion angle of the tail end of a circular-section beam and arranging a plurality of measuring points in an axis direction of the circular-section beam to obtain the surface strain in the axis direction of the beam; step 2, calculating a beam section torsion angle corresponding to each measuring point, and carrying out strain decomposition by combining the surface strains obtained at the measuring points to obtaina surface strain generated by making bending deformation of the beam structure in two orthogonal directions perpendicular to the axial direction; step 3, according to the obtained orthogonal strain information, calculating bending deformation deflections of the beam in the two orthogonal directions respectively based on a Ko displacement theory, thereby completing three-dimensional form reconstruction. Compared with other spatial three-dimensional curve reconstruction methods, the disclosed method considers the influence of torsional deformation and has advantages of high calculation speed andhigh precision under the condition of small deformation.

The present invention belongs to the cylinder data analyzing and processing field, in particular relates to a rotation speed-based cylinder pressure curve reconstruction method. The rotation speed-based cylinder pressure curve reconstruction method is characterized by calculating and reconstructing the cylinder pressure data rapidly by the data that can be measured and obtained externally and rapidly, such as the instantaneous rotation speed, the angular displacement, a top dead center signal, etc., and by utilizing a private function and a comparator, is little in data needing to be measured, simple in needed devices, high in acquisition efficiency, little in post processing calculation amount and good in cylinder pressure reconstruction effect, and has low requirements for the performances of a calculation system.

The invention relates to the technical field of machine manufacturing and the technical field of image measurement in mechanical engineering, and in particular relates to the field of three-dimensional metallographic testing. A three-dimensional modelling measurement method of a microscopic multi-phase structure based on a section profile sequence comprises the steps of: making a microscopic multi-phase structure material specimen into a specimen for metallographic testing, trying to grind through a first grinding wheel, a second grinding wheel and a third grinding wheel, simultaneously, acquiring an upper surface image of the specimen through a first microscopic lens, a second microscopic lens and a third microscopic lens, determining profile data of each phase boundary in a faultage image by using edge detection and sub-pixel subdivision algorithms, performing three-dimensional model reconstruction of the closed boundary of each phase by using eight-field joint mark tracking and NURBS freedom curve reconstruction methods, and obtaining a three-dimensional entity model of each phase through Boolean operation.

The invention provides a multi-physical model logging shear wave velocity curve reconstruction method and system and electronic equipment. The method comprises the following steps: acquiring logging data and lithologic physical property parameters of a target stratum; calculating the shale content, the stratum density and the stratum porosity of the target stratum according to the logging data; according to the shale content, the stratum density and the lithologic physical property parameters, the rock stratum matrix modulus of the target stratum is calculated through a preset rock physical model; substituting the formation porosity and the rock stratum matrix modulus into the Chapman model to obtain the rock stratum equivalent modulus of the target formation; according to the rock stratum equivalent modulus and the preset relational expression between the rock stratum equivalent modulus and the stratum longitudinal and transverse wave velocities, the shear wave velocity curve of the target stratum is constructed. According to the method, the logging shear wave velocity curve can be calculated more accurately, and large errors of the shear wave velocity curve result caused by limitation of experimental conditions are avoided.

The invention relates to the field of geophysical data processing, in particular to a logging curve reconstruction method based on a genetic neural network algorithm. The method mainly comprises the following steps of: 1, standardizing a logging curve; standardizing a conventional logging curve to be unified to the same dimension level; 2, establishing a neural network structure and training a network; determining neural network input and output, establishing a neural network structure according to the number of network layers, and training the network; 3, performing genetic manipulation; calculating a training error and a fitness function, and optimizing a network structure and a weight threshold by utilizing three genetic operators of selection, crossover and variation; and 4, performingwell logging curve reconstruction by utilizing the optimized network structure until the precision requirement is met, and outputting a result. Compared with a traditional well logging curve reconstruction method, the method has higher precision, the production cost can be reduced, the operation efficiency is improved, and the well logging curve reconstruction effect is improved.

The invention discloses a composite position error compensation method and device. The method comprises: correcting obtained original discrete actually-measured position data in a multi-dimensional non-uniform distributed manner into a plurality of sets of corrected position data storing error data that are generated by correction and are in a one-dimensional non-uniform distributed manner; carrying out curve reconstruction on the corrected position data in a one-dimensional non-uniform distributed manner in all sets to form corresponding corrected position data in a one-dimensional uniform distributed manner; carrying out curve reconstruction on all corrected position data in a one-dimensional uniform distributed manner, acquiring subdivision position data of uniform grid points, and thusacquiring a reconstructed curved surface; and generating a corresponding compensation table based on the reconstructed curved surface to realize composite position error compensation. According to the invention, the original discrete actually-measured position data in a multi-dimensional non-uniform distributed manner are corrected, error reconstruction is carried out based on the corrected data,and thus the compensation table is generated. Therefore, the high-precision and high-complexity composite position error compensation is realized.

The invention discloses a logging curve reconstruction method based on a nonlinear autoregressive neural network model. The logging curve reconstruction method comprises the following steps: dividing an existing logging curve data acquisition depth into training curve data and test curve data; establishing an NARX neural network model according to the training curve data; performing initial optimization on the NARX neural network model through a particle swarm algorithm; substituting training curve data into the NARX neural network model by using a Levenberg-Marquardt algorithm so that training can be completed; substituting the test curve data into the NARX neural network model for testing; and using the tested NARX neural network model to obtain reconstructed logging curve data. According to the method, the problem of falling into local optimum is effectively avoided, a nonlinear logging curve reconstruction system can be approximated with high precision, the nonlinear and sequential characteristics of logging data are fully utilized, the corresponding relation between curves can be accurately reflected, and the method has a good logging curve reconstruction capability.

The invention belongs to the technical field of geometric modeling, and particularly relates to a geometric parametric modeling method and device for an aircraft fuselage frame structure. The method comprises the steps: intercepting a curve on the inner profile geometry and the outer profile geometry of a fuselage frame according to a frame position plane, and obtaining a first inner profile geometry curve and a first outer profile geometry curve; constructing a first characteristic equation of the inner shape surface and the outer shape surface, intercepting discrete point coordinates on thefirst inner shape surface geometric curve and the first outer shape surface geometric curve, and performing curve reconstruction according to the first characteristic equation to obtain a second innershape surface geometric curve and a second outer shape surface geometric curve; constructing a coefficient control equation, respectively adjusting the second inner surface geometric curve and the second outer surface geometric curve, and obtaining a contour curve of the fuselage frame according to the two adjusted curves; and constructing a second characteristic equation, intercepting nodes on the contour curve of the fuselage frame according to the second characteristic equation, and taking the nodes as positions for arranging frame reinforcing ribs.

The invention discloses a tool radius directional compensation algorithm for slow slide servo turning of a complex curved surface. The tool radius directional compensation algorithm comprises the following steps of: firstly, establishing an XZ coordinate system on a contour section curve; carrying out point position discrete processing on the contour section curve to obtain discrete point positions, representing a Z coordinate value with Di,j, wherein in subscripts, i represents times of compensation and j represents a point sequence; then obtaining a subdivided radius compensation point D1,jat a compensated point D0,j; repeating the steps until obtaining a final compensated point Dn,j; and finally, obtaining the Z coordinate value of Dn,j at D0,j. according to the invention, the curve isdirectly subject to discrete subdivision, and the compensated point is obtained on the basis of the rapid directional compensation algorithm; and compared to existing algorithms in the current literature, the tool radius directional compensation algorithm only needs to carry out square and radication operations without carrying out equation solution or curve reconstruction, meanwhile, is also applicable to directional compensation of a first-order discontinuous function, meets the requirements of actual ultraprecision machining engineering application and solves problems of solving efficiencyand solving accuracy.

The invention provides a lithium ion battery charging curve reconstruction method based on artificial intelligence, so that estimation of multiple states of a battery can be achieved. According to themethod, charging segment data is used as input, a complete charging curve is reconstructed by using a deep learning method, and then multiple states of the battery, including the maximum capacity, the maximum energy, the state of charge, the energy state, the power state, the capacity increment curve and the like of the battery, can be extracted from the complete charging curve. The battery stateestimation method provided by the invention can be self-adaptively updated along with the change of the working state of the battery.

The invention relates to a carbonate fractured-vuggy reservoir emptying leakage well section logging curve reconstruction method. The method comprises the following steps that firstly, a seismic inversion attribute body is resampled; a seismic attribute parameter geologic model is established, and then seismic attribute parameter curves are extracted from all drilling wells in a target stratum along a wellbore; taking the obtained key wells of all complete curves of the target layer as sample data, and constructing a deep neural network model of a plurality of hidden layers; and a neural network model is trained through multiple iterations, so that a nonlinear mapping relation between a seismic attribute parameter curve and a logging curve is established, and finally, seismic attribute parameters of well drilling without the logging curve serve as input, and a missing logging curve of a target well is generated by applying the trained neural network model. By means of the method, the problem that basic information of the fracture-vug type oil reservoir leakage anti-empty section is lost can be effectively solved.