Drive-by interlayer damage detection methodology for heavy-haul Railway Bridge using axle box acceleration

Abstract As critical component of heavy-haul railway (HHR) bridge, the interlayer is designed to transfer vehicle load and dissipate residual oscillation. The increasing transport volumes and axle loads can degrade interlayer condition, thereby threatening the operation safety of HHR bridge. This paper proposes an innovative drive-by inspection methodology combining vertical axle box acceleration with a hybrid filtering approach for rapid interlayer damage detection in multi-span HHR bridges. The developed framework introduces a Hilbert-transform-based indicator, instantaneous amplitude quartic index (IAQI), to enhance damage localization accuracy. The hybrid filtering methodology integrates two components: (1) bandpass filtering targeting sleeper-passing frequency components to suppress track irregularity effects and enhance the interlayer damage detection efficiency; (2) a statistical diagnostic tool to diagnose whether the abnormal signal from the sleeper-related driving component of axle box acceleration is interlayer damage in multi-span HHR bridges. The feasibility of the proposed method is validated by numerical analyses and a field test of an 18-span HHR bridge. The analyses results indicate that the proposed method has good effectiveness and efficiency in detecting interlayer damage, even combined with beam damage, irregularity and noise. This research offers a new strategy to enhance the inspection efficiency and ensure the operation safety of HHR bridges.

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Publication Details

Journal
Railway Engineering Science
Published
2026-01-14
DOI
https://doi.org/10.1007/s40534-025-00404-5
Primary Topic
Railway Engineering and Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Drive-by interlayer damage detection methodology for heavy-haul Railway Bridge using axle box acceleration

Jiawang Zhan, N Zhang, Zhen Hua Ni, Chenyu Wang et al.
Railway Engineering Science
Railway Engineering and Dynamics
article

Drive-by interlayer damage detection methodology for heavy-haul Railway Bridge using axle box acceleration

Jiawang Zhan, N Zhang, Zhen Hua Ni, Chenyu Wang, Zhihang Wang, Xinxiang Xu, Yujie Wang
article en

Abstract

Abstract As critical component of heavy-haul railway (HHR) bridge, the interlayer is designed to transfer vehicle load and dissipate residual oscillation. The increasing transport volumes and axle loads can degrade interlayer condition, thereby threatening the operation safety of HHR bridge. This paper proposes an innovative drive-by inspection methodology combining vertical axle box acceleration with a hybrid filtering approach for rapid interlayer damage detection in multi-span HHR bridges. The developed framework introduces a Hilbert-transform-based indicator, instantaneous amplitude quartic index (IAQI), to enhance damage localization accuracy. The hybrid filtering methodology integrates two components: (1) bandpass filtering targeting sleeper-passing frequency components to suppress track irregularity effects and enhance the interlayer damage detection efficiency; (2) a statistical diagnostic tool to diagnose whether the abnormal signal from the sleeper-related driving component of axle box acceleration is interlayer damage in multi-span HHR bridges. The feasibility of the proposed method is validated by numerical analyses and a field test of an 18-span HHR bridge. The analyses results indicate that the proposed method has good effectiveness and efficiency in detecting interlayer damage, even combined with beam damage, irregularity and noise. This research offers a new strategy to enhance the inspection efficiency and ensure the operation safety of HHR bridges.

Railway Engineering Science
Beijing Jiaotong University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 88%
Railway Engineering and Dynamics
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Drive-by interlayer damage detection methodology for heavy-haul Railway Bridge using axle box acceleration — Jiawang Zhan, N Zhang, et al. · Railway Engineering Science (2026) | TGRS Research Map | TGRS