Measurement method for bogie steel spring parameters based on 3D structured light principle

Bogie Steel Springs require regular maintenance, with spring height and radius being critical inspection parameters. To address current issues such as poor measurement accuracy and low automation in bogie steel spring measurements, this paper proposes a bogie steel spring parameter measurement method based on the 3D structured light principle.First, the method captures 3D point cloud data of the steel spring using a binocular camera, then extracts the end-face and bottom-surface point clouds using the elevation method and projection-based dimensionality reduction method. Subsequently, an improved density-based clustering algorithm is employed to segment the end-face point cloud of the steel spring. The end-face point cloud then undergoes iterative plane fitting, and the spring height is determined by combining this with a projection-based height measurement algorithm. Finally, a boundary extraction method is introduced to process the end-face point cloud data, where the spring radius is obtained through a circle-fitting algorithm. Furthermore, a test platform was established to evaluate the reliability and stability of the measurement algorithm. Experimental results demonstrate that for eight sets of steel springs, the maximum measurement error remains within 0.2 mm. Multiple measurements performed on four spring specimens show a repeatability less than 0.1%, meeting maintenance specification requirements. These findings provide significant insights for the intelligent inspection of bogie components.