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Fasteners are an important part of railway security. The application of computer vision and image processing on fastener detection has become a research hot spot. However, most of the researches have focused on the missing and damage detection of fasteners up to now. In this paper, a method based on image processing is proposed to locate the center of the hexagon nut in the railway fastener. The precise position of the hexagon nut can be used for the automatic replacement of the nut, which is of great significance for the automatic railway construction and maintenance. The locating method proposed in this paper can be divided into two steps. First, the improved Canny detector which combines surrounding suppression and iterative excitation is used to extract the contours of the fastener. Then, a multifeature hierarchical locating (MHL) algorithm is proposed, which integrates the circle contour of the gasket and the hexagon features of the nut. The experimental results show that the improved Canny detector suppresses noises effectively and highlights the contours of fastener. The MHL algorithm in the next step improves the locating accuracy remarkably while guaranteeing the robustness meantime. [ABSTRACT FROM AUTHOR]

Rail corrugation dynamic measurement techniques are critical to guarantee transport security and guide rail maintenance. The chord-based method is one of the most common methods nowadays. However, for corrugation broadband measurement varied from 30 mm to 60 m, this method is faced with two severe challenges in actual applications: one is that the effective measuring range of traditional single chord models cannot cover the required broadband, and the other is that the common frequency sampling method (FSM) is unavailable to design the FIR inverse filters for asymmetrical chord and multipoints chord models. To solve the two problems, a practical combination-chord model (CCM) is proposed in this paper. For the first problem, the model is constructed on the existing three-point asymmetrical chord platform. Through the flexible combination of three sensors, CCM integrates the advantages of long-wave measurement from the two-point chord model and shortwave measurement from the three-point asymmetrical chord model, and realizes the corrugation broadband measurement in one platform successfully. For the second problem, the least square (LS) is employed to design the inverse filter. Compared with FSM, the design process is more unlimited and easier for the user. More important, even with the same output filter order, the filter performance designed by LS is better than that by FSM. The efficiency of CCM and the superiority of inverse filter designed by LS were verified by vast experiments. The results could achieve the design target. [ABSTRACT FROM PUBLISHER]

Dynamically measuring rail profile using the structured-light vision suffers from random vibrations on the line laser projector, which would cause distorted rail profiles. This paper presents a simple and effective distortion rectifying method to address this issue. The distorted rail profile is rectified by easily projecting it onto an auxiliary plane which is parallel to the cross section of rail. In order to establish the auxiliary plane, three profiles formed by radiating multiline structured light on rail are used to fit the rail longitudinal axis. More importantly, only one of the light planes is required to be calibrated beforehand. The others are calibrated online with the proposed self-calibration method, which is based on collinearity and parallelity constraints on the scene points of different rail profiles and requires only one image of the scene. Apart from evaluating the implementation with comprehensive experiments, we compare our method against other published works. The results exhibit its effectiveness and superiority in terms of the dynamic measurement of the rail profile. [ABSTRACT FROM AUTHOR]

Rail section profile accurate measurement techniques are critical to guarantee the transport security and reduce the maintenance cost. However, the profile may make an affine transformation under vehicle vibration. It is a challenge to identify and calibrate the affine distorted profiles in the 2-D laser displacement system (LDS). By profound observation and discussion on triple primitives including rail jaw, railhead inner line, and rail waist curve, we found the difference between normal profiles and distorted ones. To measure the difference quantitatively, we proposed a novel curve similarity measurement method, i.e., point set mapping (PSM), in this paper. By constructing PSM from the standard profile to the measured one on the triple matching primitives, the fast recognition and accurate calibration of rail profile under affine distortion were implemented. The accuracy and efficiency of the system were verified by experiments and comparisons with related methods. The results show that the PSM is faster and more robust than the universal Hausdorff distance on the similarity measure, and the performance of the modified particle swarm optimization is superior for profile distortion calibration. Furthermore, the LDS can run at a speed of 12.86 km/h under our experimental setup, which is far higher than that of the rail maintenance train (up to 5 km/h). [ABSTRACT FROM PUBLISHER]