Research on Detection Algorithm of Lateral Offset Characteristics of Rail Fasteners

Targeting the problem that the fasteners in ballastless track are laterally loosened and off the normal working position, a lateral offset detection method of the track fastener is proposed. Firstly, the algorithm solves the problem that the conventional fastener image positioning is not accurate enough. The k-means clustering and class-like algorithm are used to strengthen the segmentation of foreground, background and contour moment features to achieve accurate positioning of the fastener position in the captured image. Secondly, different from conventional fastener feature extraction using complex semantics, a machine vision based contour analysis method is proposed, which calculates the spacing of adjacent insulating caps and the spacing of adjacent nuts by extracting the contour features of the insulating cap and nut of the fastener. Compared with the safety distance threshold calculated by the fastener profile feature in the safe state, the offset is further calculated to determine whether the fastener is laterally loose. The experimental results show that the algorithm is fast and can accurately locate the position and offset of the spring. Compared with the conventional identification algorithm, the accuracy of the fastener is significantly improved, up to 98%.