Linear Motor Mover Position Measurement Based on the Matching of Captured and Sample Images

Abstract

This article presents a linear motor mover position detection method based on an image sample database to achieve high-precision measurement of the position of a long-stroke linear motor mover. First, the aperiodic fringe image is constructed with a chirp signal as the target shooting source, and an image sample database is established by capturing the target image with a certain acquisition frequency using a line-scan camera. Second, a normalized correlation coefficient (NCC) matching method is proposed to search for the position of the current image in the database. A coarse positioning method based on velocity estimation is also employed to improve the efficiency of position matching in the sample database. Third, to overcome the position measurement error caused by incomplete matching between the current image and the image in the database, a subpixel measurement algorithm based on local upsampling NCC is proposed to improve the measurement accuracy. Finally, the actual displacement of the actuator is obtained by combining the calibration coefficients. To verify the feasibility of the proposed method, an experimental platform is built using a line-scan camera, a linear motor, an adjustable light source, and a target source image. Comparison tests, speed adaptation experiments, and light adaptation experiments are set up. The experimental results show that the average time of the proposed method is approximately 1 ms, and the average absolute measurement error is approximately 0.005 mm under various working conditions, which shows that the proposed method has real-time performance and strong environmental adaptability.