Damage detection for constituents of track-bridge systems from driving component of vehicle-rail contact response

Yang, Y.B.; Hu, Xiaoyang; Shi, Kang; Mo, X.Q.; Zhang, B.; Wang, Z.L.; Xu, H.

doi:10.1016/j.engstruct.2022.114143

Cited by 9 publications

(3 citation statements)

References 53 publications

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“…This finding reaffirms the need to have reliable position systems for the success of data-driven approaches. Yang et al [58] demonstrated that the squared amplitude computed from the signal's envelope derived from the Hilbert transform is also a very powerful feature for rail damage identification. One aspect hardly addressed in most works involving damage to rails is th comparison of the performance of different damage features against various interferences Lederman et al [57] conducted parametric studies comparing the influence of position error from the GPS sensor, vehicle damping, and vehicle natural frequency on th identification accuracy achieved, using a data-driven methodology and four differen damage features: (i) temporal-frequency, (ii) spatial-frequency (iii) spatial amplitude, and (iv) signal-energy (spatial squared amplitude).…”

Section: Rail Condition-based Assessmentmentioning

confidence: 99%

“…This finding reaffirms the need to have reliable position systems fo the success of data-driven approaches. Yang et al [58] demonstrated that the squared amplitude computed from the signal's envelope derived from the Hilbert transform is also a very powerful feature for rail damage identification. Figure 8.…”

Section: Rail Condition-based Assessmentmentioning

confidence: 99%

“…The authors also investigated the influence of other factors besides those evaluated by Yang et al [61] and were able to conclude that the damping of the vehicle suspension is unfavorable to the accuracy of the method, while the mass is beneficial. This same feature was also used by Yang et al [58] in a more challenging situation involving a track section over a viaduct. Even for this case, the IAS was shown to be sensitive to damage at the tracks interlayer.…”

Section: Rail Supporting Components' Condition-based Assessmentmentioning

confidence: 99%

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Drive-by Methodologies Applied to Railway Infrastructure Subsystems: A Literature Review—Part II: Track and Vehicle

et al. 2023

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Railways are one of the most important means of transportation, allowing people and goods to move quickly, environmentally beneficially, and efficiently over long distances. To ensure safe and reliable operations, regular condition-based assessments of trains and track are of paramount importance. Drive-by methodologies, which utilize data collected by onboard monitoring systems as the vehicle travels over the track, have gained popularity as an economically viable strategy for monitoring extensive track networks as well as vehicles traveling on them. This paper presents a critical review of these methodologies applied to railway tracks and vehicles. It assesses research on track irregularities, rail conditions, and the condition of rail supporting elements, highlighting important early developments and recent papers that provide insights into future practical applications. Additionally, the paper explores works related to global vehicle condition evaluation, focusing on the identification of suspension and wheelset element damage and also discussing challenges towards commercial application. The findings suggest that drive-by methodologies have several promising future applications. These include track maintenance optimization, proactive fault detection, predictive maintenance, track performance evaluation, vehicle health monitoring, and data-driven decision-making. By leveraging drive-by assessments, railway operators can optimize maintenance efforts, detect faults early, predict remaining component life, evaluate track performance, monitor vehicle health, and make informed decisions based on data analysis. Finally, a comprehensive conclusion summarizes the achievements thus far and provides perspectives for forthcoming developments. The future practical applications of drive-by methodologies discussed in this review have the potential to revolutionize railway track and vehicle assessments, leading to safer and more efficient railway operations in the days to come.

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Section: Rail Condition-based Assessmentmentioning

confidence: 99%

Section: Rail Condition-based Assessmentmentioning

confidence: 99%