Research On Key Issue Of Rail Corrugation Dynamic Measurement Based On Chord Measurement Method

With China continuously rapid developing the railway transportation network,especially the high-speed railway network,railway transportation has become one of the most important means of transportation.Rail corrugation detection need to be solved primarily in the construction and maintenance of railway trunk lines.The chord-based method is one of the common methods for rail co rrugation dynamic measurement,which is widely used by railway departments of various countries.However,the detection process still has room for improvement.On the one hand,during the process of continuous operation,it is hard to ensure that the measuring points on the rail surface can trace the railhead cent erline well the whole time.On the other hand,the data of rail corrugation contains the trend term of orbital fluctuations in complex rail lines.In this paper,the existing process is improved based on the studies in the problems.To solve the problem of the position deviations of chord-based measuring points,an automated method and the related system for position monitoring and correction of chord-based measuring points is constructed.The proposed method comprises the position monitoring method based on machine vision algorithm and the position correction method based on stepper motor system.According to given sampling interval,the monitoring method monitors and calculates the position deviati ons between the chord-based measuring points and the railhead centerline.Once the deviation exceeds the preset range,the position of the chord measuring point is corrected to the effective range by the correction method.Experiments show that the error of the monitoring method is limited within 0.5mm.Furthermore,with 15 cm image sampling interval,our system can run at 6.75km/h under our experimental setup,which is higher than that of rail maintenance train(up to 5km/h).In order to solve the problem of the extraction of the trend of rail corrugation in complex rail lines,a novel de-trending method named as EEMD-SVD is proposed which uses permutation entropy(PE)to select relevant singular-value components to reconstruct the trend.Compared with the existing methods based on EMD,the method considers the problem of mixed signal components in the or iginal IMFs,and proposes to use SVD to extract the trend accurately hidden in multi-dimensional IMF matrix.Then,considering the singular-value components are arranged in order of energy reduction without low-complexity and high-energy of signal,the proposed method modifies the EEMD-SVD and uses permutation entropy to select relevant low-complexity singular-value components.Finally,it reconstructs the trend with the relevant singular-value components selected above.The experimental results showed the proposed method outperformed the low-pass filter algorithm,the linear programming de-trending algorithm combined with EMD,and the WD de-noising algorithm.It is an effective signal de-trending method for de-trending the trend of rail corrugation.