A case study on vision-based measurement of transverse vibration displacements of multiple hoisting ropes in a mine

This paper presents a case study of vision-based transverse vibration measurement of multiple hoisting ropes on an operational mine hoist. Based on field image data, we propose a multi-point vision measurement method. The method adds a reference line to an image sequence using digital image processing (DIP), allowing it to distinguish the measured points on hoisting ropes with similar surface features from other points. The common digital image correlation (DIC) algorithm is then used to track the hoisting rope without any physical labels. Furthermore, a motion estimation (ME) algorithm is integrated with the DIC algorithm to track multiple identical targets simultaneously. Applied to the field case, the method successfully measures the vibration displacements of four hoisting ropes. Since ground-truth values are unavailable, three groups of laboratory tests validate the method, showing good agreement with laser displacement sensor (LDS) measurements. This case study demonstrates that the proposed method is effective for determining transverse displacements of multiple identical hoisting ropes, providing a reference for solving similar engineering problems.