Abstract: With the rapid development of China's high-speed railways, traditional contact-based rail wear detection methods have limitations in measurement efficiency and are easily affected by rail deformations and surface damages, failing to meet the demands of the rail maintenance. To quickly and accurately measure the rail profile and assess rail wear, a contour extraction method based on machine vision is proposed. A monocular machine vision system for rail profile extraction has been established. After positioning with a free planar target, a two-level rail profile extraction method based on structured light color and the Steger algorithm is employed. A double circle fitting rail profile matching algorithm based on particle swarm optimization is introduced to align the measured profile with the standard profile and derive the wear value. Experimental results demonstrate that this system achieves a detection accuracy of 0.128 mm and offers high measurement efficiency.

Key words: high-speed rail, rail contour extraction, linear structured light, optical plane calibration, image processing