Entropy-Based Local Irregularity Detection for High-Speed Railway Catenaries With Frequent Inspections

Journal Article (2019)
Author(s)

H. Wang (TU Delft - Railway Engineering)

Zhigang Liu (Southwest Jiaotong University)

AA Núñez (TU Delft - Railway Engineering)

Rolf P.B.J. Dollevoet (TU Delft - Railway Engineering)

Research Group
Railway Engineering
Copyright
© 2019 H. Wang, Zhigang Liu, Alfredo Nunez, R.P.B.J. Dollevoet
DOI related publication
https://doi.org/10.1109/TIM.2018.2881529
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 H. Wang, Zhigang Liu, Alfredo Nunez, R.P.B.J. Dollevoet
Research Group
Railway Engineering
Issue number
10
Volume number
68
Pages (from-to)
3536-3547
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Abstract

The condition-based maintenance of high-speed railway catenary is an important task to ensure the continuous availability of train power supply. To improve the condition monitoring of catenary, this paper presents a novel scheme to detect catenary local irregularities using pantograph head acceleration measurements. First, a series of experimental inspections is carried out in a section of the Beijing-Guangzhou high-speed line in China. The time intervals between the inspections are shortened from the traditional six months to about 40 days, which enables monitoring the short-term degradation of local irregularities. Then, based on the wavelet packet entropy, an approach is proposed to detect local irregularities with different scales in length. Criteria for identifying and verifying the local irregularities are established based on the gradient and repeatability of entropy from multiple measurements. Results from the experimental inspections show that different scales of local irregularities can be detected by the proposed scheme. By using frequent inspections, local irregularities can be effectively verified after about seven inspections. The spatial distribution of local irregularities is found to be closely related to the catenary structure. These findings provide valuable information to deploy the scheme for a railway network.

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