Research On Ball Track Detection And 3D Reconstruction Evaluation Technology Of Ball Screw Shaft Based On Machine Vision

The machining quality of the ball screw shaft determines the overall performance and service life of the ball screw pair.Using machine vision technology for ball screw track parameter testing has advantages such as non-contact,high precision,and automation.Existing track parameter testing systems mostly perform single cross-sectional parameter measurement,which cannot comprehensively reflect the track machining quality and status.By designing a measurement device with a high-precision motion control and position detection system,it is possible to accurately acquire track images and obtain the acquisition position of the image,thereby realizing the comprehensive detection and 3D reconstruction evaluation of ball screw track parameters.Establishing a machine vision track detection system and researching efficient and high-precision detection algorithms for track parameters is conducive to promoting the improvement of ball screw machining quality.This article focuses on the ball screw track,using image processing methods,and designs a machine vision-based ball screw track parameter detection system.Based on the detection principle,hardware design and algorithm research were carried out.The main content of this article can be summarized as follows:(1)According to the structural characteristics of the ball screw track,production site detection needs,and machine vision detection principles,a machine vision ball screw track detection scheme was designed.(2)Based on the detection system principle and scheme,the optical system,motion control system,and displacement acquisition system were designed to form a machine vision ball screw track detection experimental platform.(3)Based on the detection scheme and system hardware attributes,image acquisition and data processing methods were studied.To solve the problem that the screw cross-section image cannot be accurately obtained only through the screw helix angle,a method based on obtaining the position of the ball screw track normal cross-section through the image was proposed.In order to avoid the influence of track edge errors during fitting of the track arc,a virtual ball algorithm based on the edge was proposed.Based on research on the dimensional conversion of track image edge points and coordinate transformation algorithms,a track 3D reconstruction and track state evaluation method were proposed.(4)Based on the ball screw track images collected by the experimental platform,the effectiveness of the detection system and software algorithms was analyzed and verified by comparing the detection results of the track arc parameters.The experimental results show that the proposed detection method can effectively acquire track normal cross-sectional images and perform parameter calculation and 3D reconstruction.A track 3D evaluation experiment was performed,and the track quality was evaluated using pitch error and ball radial runout parameters.This article provides theoretical basis and feasible solutions for the comprehensive evaluation of ball screw track quality,enriches track detection methods,and improves track quality detection efficiency.