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Rail corrugation (RC) is one of the most important indicator to evaluate the quality of rail, which is used to describe the irregularity of rail surface, also known as rail’s vertical flatness. However, the definition of RC is still an empirical description for low-speed measurement devices. In this paper, the process of RC measurement is divided into two steps, sampling and extraction, which helps the users to understand more clearly. Then a new mathematic model is proposed to make the process of RC’s extraction be an executable operation for machine calculation. The model adopts a new concept of flexible virtual ruler to perform sliding filtering on an overall rail and extract the instantaneous RC with a successive approximation algorithm according to user’s requirements and national standards. The proposed FVR model can not only be fully compatible with the traditional extraction method of RC, but also provide a new idea for evaluating RC’s quality. Comparing with the current popular methods, the proposed model gives a meaningful strategy for rail maintenance with a complete mathematic description having more degrees of freedom. Experiment results demonstrate its validity and reliability for both indoor simulation and actual outdoor experiments. [ABSTRACT FROM AUTHOR]

Rail corrugation is the geometric structure of the rail top surface, and it directly related to the safety and comfort of rail transportation. The monitoring of rail corrugation is the key work for rail maintenance department. Currently, the 2D laser displacement sensor is being used to measure the rail corrugation. However, the 2D sensor is easily affected by pitching vibration under complex measurement environment, which leads to large errors in the final measurement results. For solving the problem of pitching vibration in dynamic measuring rail corrugation, a data splicing method based on deviation recognition and calibration is proposed in this study. Firstly, the blind recognition of sensor deviation is applied to identify the measurement state of sensor in each data sampling. Then, a mapping method is proposed to position the actual repeated measurement interval according to geometric relationship between the deviation angle and the offset in the longitudinal direction. Finally, the modified DTW model is proposed for data registration and the data splicing can be achieved according to the registration results. Extensive experiments are carried on both indoor experimental platform and outdoor platform. The experimental results indicate that our proposed method can accurately recognize the deviation of sensor and can calibrate the deviated data set, and its performance on the rail corrugation measurement under the pitching vibration case outperforms previous data splicing work. Thus, it is with the potential engineering application. [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]

• A novel rail corrugation measurement system by using 2D laser displacement sensors is proposed. • The rail corrugation is effectively restored by the method of coarse-to-refine data splicing. • The sensor deviation and pitching vibration calibrating are achieved via a simple searching method. • Achieving accurate splicing via the MPGA-based refine splicing method. • The proposed measurement system owns high accuracy in measuring the waveband of rail corrugation varied from 10 mm to 1 m. Rail corrugation dynamic measurement techniques are essential to guide rail maintenance and ensuring the safety of railway transportation. However, the effective measuring wavebands covered by traditional techniques are limited. Hence, this paper constructs a novel measurement system by using 2D laser displacement sensors for accurate measuring rail corrugation (2D-RCM). At first, original discontinuous data of rail irregularities are sampled by 2D sensors, and then the accurate restoring of rail corrugation is completed by the coarse-to-refine data splicing method. Coarse splicing mainly extracts and calibrates the data of overlapping measurement area. The refine splicing is achieved by rigid transformation and multiple population genetic algorithm. The validity and repeatability of the 2D-RCM is tested by extensive experiments. The experimental results demonstrate that it owns high-precision on measuring the wavebands of corrugation varied from 10 mm to 1 m, and robust to deviations of 2D sensors and pitching vibrations of the 2D-RCM system. [ABSTRACT FROM AUTHOR]