9 results about "Circle fitting" patented technology

The application discloses a point-circle distance visual measurement method based on weighted circle fitting and uncertainty evaluation, comprising the following steps: S10, initial circle estimation and local region of interest (ROI) definition; S20, adaptive weighted circle fitting based on measurement point guidance; S30, point-circle distance calculation and uncertainty evaluation. The application realizes higher point-circle distance measurement precision and robustness than traditional methods; significantly reduces measurement errors caused by edge occlusion, noise and non-ideal circle deformation; provides quantitative evaluation (uncertainty) of the reliability of each distance measurement result; while ensuring high precision, maintains or improves calculation efficiency, so that it is suitable for online detection.

This invention discloses a method for estimating the rotor position of a robot servo motor based on circle fitting. The method includes: in each control cycle of the robot servo motor, using a Hall sensor to detect the absolute position of the servo motor rotor in real time and outputting two Hall signals; using a fitted Taubin circle and its parameters to perform debiasing and normalization processing on the two Hall signals output in each control cycle, and calculating the corrected rotor position angle for each control cycle using an arctangent function; wherein the Taubin circle is constructed based on data digitization and robust fitting using the RANSAC algorithm. This invention improves the accuracy of robot joint motor position detection and control performance by fitting a Taubin circle based on data digitization and the RANSAC algorithm, correcting the Hall signals in real time, and calculating the rotor position angle.

This invention belongs to the field of integrated radar signal processing technology, specifically involving a two-stage clutter suppression method based on the space-time domain, which solves the problem of clutter suppression in complex low-altitude environments. First, the first stage, based on CLAM (Clear-and-Field Analysis), eliminates the dependence on the radial velocity difference between the target and clutter, directly and accurately shielding clutter from the physical space dimension, efficiently eliminating strong static ground object interference while preserving the energy of low-speed UAVs without loss. Second, the second stage, with its candidate angle traversal and circle fitting algorithm, accurately estimates and reduces the DC bias caused by residual static clutter, successfully overcoming the blind spot problem when the target and clutter spatial angles are close, enabling accurate extraction of weak, low-speed UAV targets at close range.

The application discloses a circle fitting method and device and a storage medium. The circle fitting method comprises the following steps: performing edge detection processing on a to-be-fitted circular target in a target image to obtain edge detection points; selecting target detection points in the edge detection points to perform iterative fitting processing to obtain an iterative fitting circle; determining fitting weights corresponding to the target detection points according to the fitting matching degrees of the iterative fitting circle and the target detection points; and performing weighted iterative fitting processing according to the fitting weights and the target detection points to obtain target circular parameters of the to-be-fitted circular target. The above scheme can improve the circle fitting precision when the circular target is recognized.

This invention relates to the field of precision measurement technology, and more particularly to a method and system for measuring the diameter of a test tube. The method includes: acquiring point cloud data of the cross-sectional profile of the test tube and splitting it into a test tube surface point set and a label surface point set; calculating the diameter of the test tube after performing optimal circle fitting using an improved bee colony algorithm. The optimal circle fitting using the improved bee colony algorithm includes: A10, defining the objective function and initializing the food source population and parameters; A20, sequentially executing the hired bee stage and the observation bee stage, updating the food sources and their corresponding stagnation counts; A30, entering the scout bee stage, checking the stagnation count of each food source, initializing food sources with stagnation counts exceeding the abandonment threshold according to a mixing strategy, and updating the food source population; A40, incrementing the current iteration count by 1 and returning to step A20, until the iteration termination condition is met. This invention improves the accuracy of test tube diameter measurement.

The application discloses a multi-class circle special-shaped target resisting heart drift and a binocular vision positioning method thereof, and belongs to the technical field of industrial vision measurement and precision positioning. The target comprises a white background substrate and seven symmetrical black circles, wherein a large circle is arranged at the center, a standard normal small circle is arranged above and below the large circle respectively, and four specially-made class circles are arranged at four corners respectively. The specially-made class circles are designed according to a cylindrical surface nonlinear projection formula. The positioning method comprises the following steps: a binocular camera collects a target image and extracts two-dimensional circle center coordinates; three-dimensional point clouds are solved through stereo matching; a cylindrical space axial vector is extracted and a normal plane is constructed, and three-dimensional feature points are orthogonally projected to the normal plane for two-dimensional circle fitting; and the coordinates of an internal anchor cylinder center and a surface highest axial reference point are solved through coordinate inverse transformation. The application effectively overcomes positioning errors caused by cylindrical curvature deformation, space inclination and rotation around an axis, and significantly improves the positioning robustness and universality under complex working conditions.

The application discloses an axial slice-based underground mine pipeline point cloud completion method, relates to the technical field of point cloud data processing, and is used for data completion of pipeline point cloud, and comprises the following steps: slicing a pipeline point cloud data after preprocessing along an axial direction, reducing three-dimensional point cloud to two-dimensional plane processing, calculating related geometric parameters of the pipeline, extracting a pipeline center line based on improved DBSCAN clustering and least square circle fitting, constructing a skeleton model under geometric topological constraints, combining local geometric features and global topological constraints, realizing geometric reconstruction of a missing area through a rotary surface generation and local interpolation algorithm, and realizing robust repair of the missing area. The application extracts the pipeline center line and geometric parameters in combination with a convex hull and a RANSAC method, realizes completion of the pipeline point cloud data through a continuous rotation correction method, and significantly improves the completion quality of the pipeline point cloud.

This invention discloses an automatic detection and sorting process for ball track dimensional defects within a ball cage shell, relating to the field of ball track dimensional defect detection. The process includes: acquiring an original contour point cloud dataset; obtaining a robust ball track contour dataset using random sampling circular arc fitting; establishing a spatial radial dimension compensation model to obtain the radial dimension correction value at the bottom of the ball track and the corrected ball track contour coordinates; obtaining the compensation value for the ball track arc radius based on a least-squares circle fitting algorithm; calculating the angular deviation and straightness error of each ball track to generate a multi-dimensional dimensional defect feature vector; and sorting the workpieces into qualified, reworkable, or scrap bins using a pneumatic sorting mechanism based on the comparison results. The advantages of this invention are: by combining anomaly point suppression and clamping posture calibration compensation, the influence of surface interference and clamping errors on measurement accuracy is eliminated, achieving high-precision automatic detection and reliable grading and sorting of ball track dimensions within the ball cage shell.

A complex structure workpiece drilling parameter measurement method based on a shrinking neighborhood circle boundary point clustering algorithm, applying computer vision and machine learning technology, proposes a shrinking neighborhood circle boundary point clustering algorithm, improves the accuracy of boundary point clustering, and an iterative circle fitting method based on fitting degree improves the accuracy of drilling recognition and fitting, so that the constructed three-dimensional measurement model can be used for workpiece drilling parameter acquisition, and the measurement error is less than 0.05mm, meeting the engineering requirements.