198 results about "Ellipse" patented technology

The invention belongs to the field of cable eccentricity detection, and particularly relates to a cable eccentricity detection method and system based on X rays. The method comprises the following steps: calculating a gradient magnitude diagram and a gradient direction diagram through an X-ray image of a cable, screening a point with the local maximum gradient magnitude and low neighborhood divergence as a contour starting point, performing contour tracking to generate a contour point set, and selecting a next contour point based on a tangential prediction direction; performing ellipse fitting on the contour point set to obtain a geometric center, long and short axis parameters and a root-mean-square error of a fitting ellipse, dividing the fitting ellipse into an inner candidate ellipse and an outer candidate ellipse according to a long axis, and matching the inner candidate ellipse meeting the condition for each outer candidate ellipse; and screening out an outer candidate ellipse and an inner candidate ellipse which meet conditions from the candidate pairs, and calculating the eccentricity of the cable to be measured based on geometric center coordinates of the outer candidate ellipse and the inner candidate ellipse. According to the invention, the accuracy and reliability of cable eccentricity measurement results can be improved.

The invention provides a non-training burr detection method and device for a cover plate inner hole, relates to the field of burr detection, and solves the technical problem of non-target area interference caused by incapability of effectively focusing on an inner hole area. The method comprises the following steps: acquiring a current frame image of a target cover plate, and storing the current frame image as a grey-scale map; performing threshold segmentation on the grey-scale map, and extracting a maximum outer contour region in the grey-scale map; and carrying out convex hull calculation, and removing a concave part in the maximum outer contour region to obtain a regular convex hull contour. And generating an optimal ellipse boundary through an ellipse fitting algorithm. And carrying out segmentation fitting to remove outliers to obtain a final ellipse boundary. And generating a binary mask based on the ellipse fitting region, extracting a pixel set of which the gray value is zero in the mask, and outputting a burr region. And calculating the total defect area, comparing the total defect area with a dynamically adjusted area threshold value, judging whether the cover plate is qualified or not, and feeding back a judgment result to the detection control system. The device is used in the burr detection process of the inner hole of the cover plate.

The invention relates to the technical field of image processing, in particular to a rubber ring contour burr detection method and system based on geometric transformation, and the method comprises the steps: obtaining a rubber ring image, and extracting the outer contour of a rubber ring and the contour of each burr in the rubber ring image; fitting the outer contour of the rubber ring by adopting a least square method to obtain an ellipse, and mapping the ellipse into a standard circle: carrying out bilinear interpolation resampling on the rubber ring image, and carrying out polar coordinate transformation on the rubber ring image by taking the circle center of the standard circle as an original point to generate an expanded image; generating a reconstructed image with enhanced burr features from the expanded image through wavelet transform, determining burr parameters of the reconstructed image, mapping the burr parameters back to a Cartesian coordinate system of the rubber ring image, and generating a detection result containing burr number, position and size information; according to the invention, the accuracy and robustness of tiny burr detection can be improved.

The invention provides a gear peeling time-varying meshing stiffness prediction method and system based on a back propagation neural network, and the method comprises the steps: considering a tooth surface peeling fault based on a gear tooth bearing contact analysis method, and constructing a helical gear pair time-varying meshing stiffness calculation model; a real irregular tooth surface peeling area is fitted by adopting a least square ellipse fitting method to obtain an ellipse appearance representation, any peeling position is completely described through six key geometric parameters, the geometric parameters of the ellipse appearance are systematically traversed and fitted, and diversified peeling appearance samples are generated. Introducing a tooth profile deviation matrix corresponding to the peeling morphology sample into a tooth surface bearing contact analysis model, and constructing a training data set; and constructing a back propagation neural network model of multiple hidden layers, and performing end-to-end training by using the training data set, so that the back propagation neural network model learns a nonlinear mapping relationship from geometric parameters to a time-varying meshing stiffness curve, thereby predicting the time-varying meshing stiffness under any peeling morphology.

Methods, systems and apparatuses may provide for technology that determines a major axis length of an ellipse in texture space based on a transformation matrix associated with a circle in screen space, inverts the major axis length, determines a product between the inverted major axis length and a determinant of the transformation matrix, and determines a minor axis length based on a modulus of the product between the inverted major axis length and the determinant of the transformation matrix. In one example, the technology selects a level of detail in the texture space based on the major axis length, the minor axis length, a direction of the major axis length, and a direction of the minor axis length.

According to one or more embodiments of the present disclosure, an ellipse model may be applied to detection results included in ultrasonic sensor data (USS data) to identify one or more objects that may be indicated by the detection results. The identification of the objects may include determining the locations, shapes, and / or classifications of at least portions of the objects. For example, in some embodiments, the ellipse model may be applied to detection arcs indicated in USS data and corresponding to detection of an object using multiple ultrasonic sensors. In some embodiments, the application of the ellipse model may include fitting an ellipse to the detection arcs. The resulting ellipse and / or its corresponding ellipsoidal parameters may indicate one or more properties about the object.

The invention belongs to the technical field of scanning measurement, particularly relates to a cable outer diameter and ovality measurement method and system based on line laser contour scanning, and aims to solve the technical problem of low measurement precision caused by the fact that an existing algorithm is sensitive to noise, asymmetry of light strips and contour discrete points. The measurement method comprises the following steps: S1, performing anisotropic Gaussian filtering on a pixel according to a local tangential direction of a preliminary center line; s2, calculating a second derivative value and a third derivative value of the sub-pixel center point in the normal direction; s3, performing initial weighted least square ellipse fitting by using the corrected contour point set and the corresponding fitting weight to obtain parameters of an initial ellipse; and S4, based on the lengths of the long axis and the short axis of the fitting ellipse, calculating to obtain the outer diameter and the ellipticity of the cable. According to the measurement method, the interference of abnormal data points introduced by local flaws such as oil stains and scratches on the surface of the cable is eliminated, and the accuracy and the stability of a fitting result are improved.

Embodiments are disclosed for determining a spin rate and axis of a ball using deep learning. In some embodiments, a method comprises: training a deep learning network on training images of spinning balls, each spinning ball having at least one feature point in a time series that forms a two-dimensional (2D) ellipse image in a 2D plane; capturing, with at least one camera, a series of images of a ball; predicting, with the trained deep learning network, spin measurements associated with the ball based on the series of images; determining a spin rate of the ball based on the spin measurements; determining coefficients of a 2D ellipse model based on the spin measurements and the spin rate; and determining, with the at least one processor, a spin axis of the ball in 3D space based on the 2D ellipse model and the spin rate.

The invention discloses a circular hole measurement method based on image feature recognition, a medium and a system. The method comprises the steps of S1, performing Gaussian filtering processing on an original image; s2, performing gray scale superposition projection through a sub-pixel circular boundary projection algorithm to generate a projection curve; s3, performing moving average filtering on the projection curve to generate a smooth curve; s4, performing differential operation based on the smooth curve to generate a differential curve; s5, screening an effective boundary feature point set on the differential curve; s6, for each extreme point in the effective boundary feature point set, calculating an adaptive threshold value in a neighborhood gray scale curve of the extreme point, and realizing sub-pixel-level positioning through gray scale straight line and smooth curve interpolation fitting; s7, generating an initial ellipse model from the sub-pixel feature points through a robustness ellipse fitting algorithm; and S8, iteratively optimizing a fitting result, removing abnormal points which deviate from the model and exceed a threshold value, and outputting an optimized ellipse parameter. The method has the advantages of high measurement precision and the like.

The invention discloses an ultrasonic guided wave damage ellipse imaging positioning method and equipment for a layer decreasing composite material laminated plate. The method comprises the following steps: S1, acquiring thickness change direction information of the laminated plate and position coordinates of an excitation transducer and a receiving transducer; s2, according to the material characteristic parameters, simulating and calculating the propagation time of ultrasonic guided waves transmitted from an excitation transducer to any point to generate a first theoretical propagation time map, and simulating and calculating the propagation time of the ultrasonic guided waves transmitted from any point to a receiving transducer to generate a second theoretical propagation time map to generate a second theoretical propagation time map; coupling influence of thickness change and material anisotropy on guided wave propagation is considered in the simulation process; s3, transmitting an ultrasonic guided wave signal, and extracting the actual flight time of a damaged wave packet; s4, calculating theoretical total propagation time, and determining a candidate area where damage exists; and S5, on the basis of repeated operation of the multiple groups of transducer pairs, taking a plurality of candidate region intersections to determine a final damage position. The objective of the invention is to solve the positioning error problem caused by the structural characteristics of a laminated plate in a traditional algorithm, and to realize more accurate damage detection and positioning.

The invention discloses a high-rigidity structure target vibration recognition method and system based on computer vision, a terminal and a medium, and the method comprises the steps: constructing a training data set for target vibration recognition based on a bridge model, and training an EDVR model which is a video super-resolution network; obtaining a to-be-recognized image sequence, performing super-resolution processing on the to-be-recognized image sequence based on the trained EDVR model, and obtaining a fitting ellipse according to the to-be-recognized image sequence subjected to the super-resolution processing; and on the basis of the fitting ellipse, recognizing the displacement of the structural target spot and the vibration frequency of the structural target spot to obtain the vertical physical displacement of the target spot at each moment and the vertical vibration acceleration data of the target spot at each moment, and on the basis of the vertical physical displacement and the vertical vibration acceleration data, obtaining the deflection of the bridge and the frequency of the bridge. According to the invention, the EDVR model is adopted to carry out super-resolution processing on the structure target spot, so that the recognition effect on the vibration of the high-rigidity structure can be improved.

The invention discloses a shield segment splicing elliptic change detection method, relates to the technical field of shield segments, and breaks through the limitation that in traditional detection, elliptic change and slab staggering are detected separately, and judgment depends on artificial experience. An integrated design of circular seam point cloud accurate screening-double circular seam plane fitting correction-least square circle fitting and ellipsometry parameter linkage calculation is adopted, secondary correction is performed through a second circular seam plane equation, the problem that single circular seam plane fitting is easily influenced by model reconstruction errors is solved, the fitting precision is improved, and the fitting precision is improved. The technical closed loop of section geometric feature extraction-ellipse parameter quantization-slab staggering reference calibration is achieved, meanwhile, least square circle fitting of YZ section point clouds is combined with ellipse long axis, ellipse short axis, ellipse rate and deformation deviation calculation depth, ellipse judgment is achieved through double threshold values of ellipse rate grading and deformation deviation threshold values, the risk of misjudgment of a single parameter is avoided, and the method has the advantages of being high in practicability and high in practicability. And a high-precision reference surface is provided for subsequent slab staggering quantity calculation.

The invention relates to a nested identifier design and visual positioning method for target alignment in a complex scene. The method comprises nested positioning identifier design, concentric circle visual detection positioning and two-dimensional code visual detection positioning. The method comprises the following steps: firstly, designing an outer-layer positioning identifier by adopting a mode of eccentrically nesting two concentric circles with different sizes, and designing an inner-layer positioning identifier by adopting a mode of nesting a two-dimensional code; and secondly, obtaining a target ellipse set by adopting an ellipse detection method based on segmental arc detection classification, designing concentric ellipse constraints, obtaining a target concentric ellipse set, carrying out concentric circle center projection point positioning, and realizing identification positioning calculation. And finally, the target two-dimensional code is detected, and nested two-dimensional code pose calculation is realized by adopting an improved EPnP pose calculation method.

The invention relates to the technical field of oil and gas drilling and production, and discloses a method for determining the sphericity of rock debris, computing equipment and a machine readable storage medium. The method for determining the sphericity of the rock debris comprises the following steps: acquiring an original image of a rock debris sample, and preprocessing the original image to obtain a target image; according to the target image, edge detection is carried out, rock debris adhesion particles are separated, the rock debris contour is determined, geometric parameter calculation is carried out according to the rock debris contour, target geometric parameters of the rock debris sample are determined, and the target geometric parameters comprise the actual area, the perimeter, the minimum circumcircle area, the equivalent ellipse long axis length and the equivalent ellipse short axis length; and determining the rock debris sphericity of the rock debris sample according to the target geometric parameter and the lithology type of the rock debris sample. Finally, high-precision, high-efficiency and low-cost rock debris sphericity measurement is realized.

The invention discloses a fly-around path autonomous planning method, which comprises the following steps of: 1, drawing up a mark track in a fly-around process as an elliptical track, and solving a minor semi-axis, a major semi-axis and a total fly-around angle of the elliptical track according to the current relative position and the preset tail end relative position of a tracking satellite and a target satellite; step 2, obtaining a motion mode of the aircraft on an elliptical orbit, and obtaining a formation vector design of an elliptical fly-around plane according to a minor semi-axis, a major semi-axis, a total fly-around angle, a total fly-around time and a current fly-around time of an ellipse, the formation vector comprising a position and a speed of a tracking star under a target star orbital coordinate system; and step 3, rotating the formation vector of the fly-around plane into an expected plane according to three parameters of the set fly-around elliptical arch line argument, the fly-around ascending intersection angle and the fly-around inclination angle. According to the method, the planned path is used as a nominal track, and flying-around approaching to the target or flying-around evacuating from the target can be realized by applying control.

A phase difference sheet including a substrate and a phase difference film as a tilt film, wherein, in a biaxial refractive index ellipsoid exhibiting a refractive index anisotropy, of three principal refractive indexes nx, ny, nz, the principal refractive index in the length direction of a columnar structure, i.e., the X-axis direction, is nx, the principal refractive index in the major axis direction of an ellipse perpendicular to the X-axis, i.e., the Y-axis direction, is ny, and the principal refractive index in the minor axis direction, i.e., the Z-axis direction, is nz, the following conditional expression (1) is satisfied, and, in a case where the incident angle of a direction tilted to the X-axis side with the normal as a reference is positive, the phase difference of incident light at an incident angle of +30° is Re(+30), the phase difference of incident light at an incident angle of -30° is Re(-30), and the ratio of Re(+30) to Re(-30), i.e., the phase difference ratio, is Re(30) ratio, the following conditional expression (2) is satisfied, ny > nx > nz (1), Re(30) ratio = Re(30) / Re(-30) = 1.1 to 4.0 (2).

The application discloses a laser frequency modulation interferometer phase measurement error correction method, system and device, relates to the field of photoelectric precise measurement technology, and comprises the following steps: acquiring a laser frequency modulation interferometer quadrature phase measurement signal, and expressing the quadrature phase measurement signal by using a standard ellipse equation; defining variables in Kalman filtering, discretizing and normalizing the equation; acquiring a time update equation of a Kalman filter, and measurement noise covariance and process noise covariance according to the normalized standard ellipse equation; acquiring a phase measurement update equation; introducing four points in the vicinity of four axes of the ellipse to perform iterative fitting; initializing iteration by rotating the ellipse through scanning laser temperature; and correcting the quadrature phase measurement signal by using posterior estimation. According to the conversion relationship between the quadrature signal characteristics and the ellipse parameters, the unequal amplitude and the bias of the quadrature signal are corrected in real time, so that the correction of the nonlinear error of the phase measurement is finally realized.

The invention discloses a two-dimensional conversion method for a multi-dimensional spatial relationship between GNSS ambiguity vectors, and the method comprises the steps: constructing a GNSS double-difference mathematical model, and obtaining a multi-dimensional ambiguity vector floating solution and a variance-covariance matrix through a least square method; according to the ambiguity vector floating solution and the variance-covariance matrix thereof, obtaining an optimal integer solution and a suboptimal integer solution of the ambiguity vector by means of a least square ambiguity decorrelation adjustment method; by taking the ambiguity vector floating solution, the optimal integer solution and the suboptimal integer solution as end points, calculating the ellipse norm side length of a side formed by any two end points and an A-inner product included angle between any two sides; constructing a two-dimensional Euclidean triangle based on an elliptical norm side length and an A-inner product included angle, and converting a complex and abstract multi-dimensional space relationship among an ambiguity vector floating point solution, an optimal integer solution and a suboptimal integer solution into a simple and visual two-dimensional triangle relationship; the method provides important method support for analyzing the GNSS ambiguity confirmation reliability influence mechanism.

The invention discloses an AUV (Autonomous Underwater Vehicle) pose correction method and system based on perspective conversion and a storage medium, and belongs to the field of underwater robots. The method comprises the steps that an underwater circular light source lamp array image is shot through a monocular camera, and initial circle center feature points are extracted after preprocessing and contour screening; using a P3P algorithm to preliminarily solve the relative pose and constructing a perspective transformation matrix; carrying out ellipse fitting on the contour and sampling on an ellipse, and projecting sampling points to a virtual plane through inverse perspective transformation; calculating an average circle center coordinate on the virtual plane, and re-projecting the average circle center coordinate to the image plane to obtain a corrected feature point; and finally, calculating a high-precision final pose by using the correction point through a P3P algorithm. According to the method, the virtual world plane is constructed by adopting a perspective conversion-based method with relatively small operand, the circle center coordinate is obtained in a circle correction mode by utilizing the characteristic that the inclination angle between the virtual world plane and the real world plane is relatively small, the influence of an eccentric distance phenomenon on the extraction of the circular target feature point is reduced, and the AUV pose resolving precision is effectively improved.

The application discloses a two-dimensional rotary table obstacle avoidance topology relationship modeling and planning method and belongs to the technical field of satellite task planning. The method comprises the following steps: according to intersection information of an original task planning trajectory and a sun circle and a rugged limiting curve, an obstacle avoidance ellipse trajectory curve of a two-dimensional rotary table is planned; a plurality of equally spaced key path points are selected on three curves, namely the obstacle avoidance ellipse trajectory curve, a fitting curve of an original task planning trajectory starting point and an obstacle avoidance ellipse trajectory curve starting point and a fitting curve of an original task planning trajectory ending point and an obstacle avoidance ellipse trajectory curve ending point; and according to a minimum jerk algorithm, a path segment composed of all adjacent two key path points is fitted and calculated to obtain an optimal task planning trajectory of the two-dimensional rotary table. The application can realize trajectory planning of the two-dimensional rotary table for simultaneously avoiding sunlight and limiting ruggedness, so that a task can be smoothly executed.

An adaptive rotation detection and measurement method for a small-scale aurora structure comprises the following steps: step 1, carrying out preliminary detection on an aurora arc in an all-sky aurora image through an aurora arc structure sensing module, and obtaining an ellipse approximation reconstruction region by adopting shape fitting; estimating the inclination angle of the aurora arc relative to the horizontal position by using the elliptical main axis direction; step 2, carrying out space correction on the coordinates of the all-sky aurora image and the labeling frame of the small-scale aurora structure, namely, carrying out anticlockwise rotation on the aurora image by taking the inclination angle as an angle, and simultaneously carrying out coordinate conversion on corresponding labels in the same direction; and step 3, establishing a target detection model of the small-scale aurora structure on the corrected spatial domain, realizing positioning and region identification of the small-scale aurora structure under the condition of direction alignment, rotating the detected small-scale aurora structure back to the original direction, and measuring the detection frame under the original spatial coordinates to obtain a target detection result of the small-scale aurora structure. And the spacing, the length-width ratio, the height and the width parameters of the small-scale aurora structure are obtained.

The invention provides a high-temperature and drought composite disaster monitoring and early warning method and system, and relates to the technical field of disaster monitoring and early warning, and the method comprises the steps: 2, extracting a data subset from a fusion data set, constructing a feature analysis region according to a preset reference relation, selecting a core analysis unit in the feature analysis region as a focus of an ellipse, and carrying out the calculation of the data subset; selecting an external reference unit as another focus of the ellipse in an adjacent spatial range, and calculating the spatial form and dynamic change of an eccentricity quantization region of the ellipse; according to the incidence relation of the core analysis unit and the external reference unit along with the time change, an analysis path is generated, an environment parameter correction coefficient is calculated to calibrate related elements in the fusion data set, and a calibrated fusion data set is obtained. According to the invention, probability prediction and dynamic early warning of high-temperature drought composite disasters are realized, and the reliability and real-time performance of disaster early warning are improved.

The application discloses a kind of based on multi-focal sharpness analysis's stacked cell hierarchy determination method and system.Acquire Z-stack multi-focal image sequence and extract each focal plane cell contour;Based on centroid coordinates and area features, establish the profile correlation data table of the same cell in different focal planes;Ellipse fitting algorithm is used to complete the shape of the profile of the cell that is blocked;Based on complete geometry mask, screen potential stacked candidate cell pair and locate overlapping area profile;With gradient function as evaluation index, calculate the overlapping area profile sharpness of each cell under multiple focal planes, determine the best focus focal length and judge cell hierarchy relationship;Attribute graph is constructed and topological sorting is executed, and global stacked hierarchy sequence is output.The application establishes hierarchy reasoning rule with rigorous physical basis according to the physical law that upper cell best focus focal length is higher, is compatible with existing Z-stack imaging process, adapts to basic laboratory high-throughput analysis demand.

The application discloses a kind of workpiece inner hole profile ellipse detection method, computing device and storage medium, method includes: based on predetermined angle step, obtain inner hole profile point set from the inner hole image of workpiece;Randomly obtain a predetermined number of profile points from inner hole profile point set;Whether the distance between any two profile points is greater than the first distance threshold value is judged;If yes, then based on the predetermined number of profile points fitting forms initial ellipse;Next profile point is randomly obtained from inner hole profile point set, whether the distance of next profile point to initial ellipse is less than the second distance threshold value is judged;If yes, then determine the target coverage angle value of all target profile points in inner hole profile point set to initial ellipse distance less than the second distance threshold value;Whether target coverage angle value is greater than the first coverage angle threshold value is judged, if yes, then according to initial ellipse obtains ellipse parameter.According to the technical scheme of the application, it is favorable to improve ellipse detection efficiency and precision.

The invention relates to an industrial CT scanning geometric structure detection result evaluation and process parameter setting method. The detection result evaluation method comprises the steps that a uniform blank is adopted to manufacture a test block with the diameter being D; the test block and the detected sample are both placed on a rotary table, the test block is located on the extension of the long edge of the scanning section face of the detected sample, an X-ray machine is started to conduct CT scanning on the detected sample and the test block, and a CT image is obtained; in a CT image, an image of an area where a test block is located is intercepted, a gray threshold is set, threshold segmentation processing is carried out on the intercepted image, edge contour lines of the threshold segmentation image of the test block are extracted, ellipse fitting is carried out on position information of all the contour lines, an optimal fitting result is calculated, and the lengths of a long axis and a short axis of an ellipse are obtained. Dividing the length of the long axis of the ellipse by the length of the short axis to obtain the shape degree value of the ellipse; if the shape degree value of the ellipse is smaller than a set shape degree threshold value, it is judged that the geometric structure precision of the current CT detection result meets the requirement.

The present application relates to geodetic and engineering surveying technical field, specifically to a kind of plane coordinate point cloud fitting arbitrary close degree error ellipse in control network design stage.The method includes: the pre-processing of control point coordinate point cloud, removes abnormal value;Accurate spatial precision evaluation density field is constructed to calculate grid point density value;According to the specified confidence, the density threshold value is calculated, the contour is extracted and the error ellipse parameter is fitted.The present application solves the ellipse fitting problem of any specified confidence of non-normal distribution point cloud by adaptive bandwidth kernel density estimation, and significantly improves the reliability of precision evaluation under complex scene.

The present application belongs to the field of cable eccentricity detection, and particularly relates to a cable eccentricity detection method and system based on X-ray. The method calculates gradient amplitude graph and gradient direction graph through X-ray image of the cable, screens points with local maximum gradient amplitude and low neighborhood divergence as contour starting points, generates contour point set through contour tracking, and selects next contour point based on tangent prediction direction. Then, the contour point set is subjected to ellipse fitting, the geometric center, long and short axis parameters and root mean square error of the fitted ellipse are obtained, the fitted ellipse is divided into inner and outer candidate ellipses according to the long axis, and each outer candidate ellipse is paired with the inner candidate ellipse meeting the condition. The outer candidate ellipse and the inner candidate ellipse meeting the condition are screened from the candidate pair, and the eccentricity of the cable to be measured is calculated based on the geometric center coordinates of the two. The present application can improve the accuracy and reliability of the cable eccentricity measurement result.

The application discloses a kind of positioning method and related equipment based on image, method includes: shooting environment, obtain the mark image for the positioning image of pre-set, wherein the positioning image includes DM code from inside to outside, circular mark and several mark blocks;Based on the circular mark, the mark image is carried out ellipse detection, and ellipse position information is obtained;According to the ellipse position information, the mark three-dimensional coordinates corresponding to the DM code are extracted;And, according to the ellipse position information, the block coordinate information corresponding to the mark block in the mark image is determined;According to the block coordinate information, the mark two-dimensional coordinates corresponding to the positioning image are calculated;According to the mark two-dimensional coordinates and the mark three-dimensional coordinates, the positioning information corresponding to the mark image is calculated.The application can significantly improve the speed and accuracy of positioning.

The invention discloses a method for determining the actual steel ball size of a ball cage type universal coupling, and belongs to the technical field of ball cage type universal coupling design. The method comprises the following steps: coupling parameter analysis; calculating the center difference between the wheel sorting steel ball and the ellipse and the actual center difference between the steel ball and the ellipse; and calculating the actual center size of the steel ball. According to the method, mechanical professional knowledge is combined, the tangent between the elliptical orbit and the steel ball is analyzed, the actual center size of the steel ball is directly calculated according to different conditions of the inner star wheel and the outer star wheel, repeated modeling work of three-dimensional model analysis in the prior art is avoided, the measurement efficiency is remarkably improved, meanwhile, the universality of the method is enhanced, and the application range is expanded.

The invention discloses a method for calculating an approximate circle diameter in a touch algorithm, which comprises the following steps of: 1, calculating a central physical coordinate according to original data obtained by touch, and taking the central physical coordinate as an expected value; step 2, calculating a covariance; step 3, constructing a covariance matrix; 4, performing eigenvalue decomposition on the constructed covariance matrix to obtain eigenvalues; step 5, calculating an initial ellipse semi-axis length through the characteristic value; step 6, calculating an equivalent diameter; step 7, simulating a curve equation by using a plurality of samples; and step 8, when actual touch occurs, obtaining the equivalent diameter through the steps 1-6, and calculating to obtain the diameter of the touch object. According to the method, eigenvalue calculation processing is carried out on the original covariance matrix, the contour of a real touch area can be accurately fitted, coordinate distribution characteristics in a theoretical model are considered, original data and physical size factors of a sensor are combined, and therefore the accuracy of touch size calculation is remarkably improved.