Intelligent identification for vertical track irregularity based on multi-level evidential reasoning rule model

Zhang, Zhenjie; Xu, Xiaobin; Zhang, Xuelin; Xu, Xiaojian; Ye, Zifa; Wang, Guodong; Dustdar, Schahram

doi:10.1007/s10489-021-03114-7

Cited by 2 publications

(1 citation statement)

References 23 publications

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“…Czop et al (2011) evaluated the track irregularity by the acceleration of the train based on the inverse linear change solution method. Zhang et al (2022) developed a multi-level evidence reasoning multi-level evidential reasoning rule model to establish the nonlinear causal relationship between vibration signals and track vertical irregularities. Niu et al (2020) combined ARX model and state space model to study the transfer relationship between track irregularity and vehicle acceleration.…”

Section: Introductionmentioning

confidence: 99%

A combined method to identify the rail irregularity at welded region

Lou

Chen

Zheng

2023

Journal of Vibration and Control

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The track irregularities affect the safety and comfort of running vehicle and increase the dynamic responses of vehicle and track. There is the rail irregularity at the welded region, and the irregularity can be regarded as the superposition of two cosine waves with the long wavelength about 1 m and the short wavelength of 0.1–0.2 m. The welded location has both short-wavelength irregularity and long-wavelength irregularity. A combined method is presented to identify the rail irregularity at the welded region using the acceleration time history curve of wheelset. Firstly, the accelerations of wheelset are transformed into the different frequencies domain signals by wavelet transformation, and the rail irregularity with the short wavelength and high-frequency is determined. Secondly, the rail irregularity with the long wavelength and low-frequency is identified by the Wigner–Ville distribution or the short-time energy method. Finally, the rail irregularity at the welded region is determined by both of the above two steps met. The correctness of the proposed method is validated by numerical example. The proposed method can accurately and efficiently identify the high-frequency and low-frequency characteristics of the rail irregularity at the welded region.

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Section: Introductionmentioning

confidence: 99%