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Research on the rapid diagnosis method for hunting of high-speed trains
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Wanru Xie, Yixin Zhao, Gang Zhao, Fei Yang, Zilong Wei, Jinzhao Liu
Railway Sciences | 2025, 4(1) : 1 - 21
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Railway Sciences | 2025, 4(1): 1-21
Research paper
Research on the rapid diagnosis method for hunting of high-speed trains
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Wanru Xie, Yixin Zhao, Gang Zhao, Fei Yang, Zilong Wei, Jinzhao Liu
Affiliations
  • Infrastructure Inspection Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China
  • Infrastructure Inspection Center, China Railway Corp, Beijing, China
  • Infrastructure Inspection Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China
  • Infrastructure Inspection Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China
Published: 2025-02-10 doi: 10.1108/RS-10-2024-0042
Outline
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Purpose

High-speed turnouts are more complex in structure and thus may cause abnormal vibration of high-speed train car body, affecting driving safety and passenger riding experience. Therefore, it is necessary to analyze the data characteristics of continuous hunting of high-speed trains passing through turnouts and propose a diagnostic method for engineering applications.

Design/methodology/approach

First, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is performed to determine the first characteristic component of the car body's lateral acceleration. Then, the Short-Time Fourier Transform (STFT) is performed to calculate the marginal spectra. Finally, the presence of a continuous hunting problem is determined based on the results of the comparison calculations and diagnostic thresholds. To improve computational efficiency, permutation entropy (PE) is used as a fast indicator to identify turnouts with potential problems.

Findings

Under continuous hunting conditions, the PE is less than 0.90; the ratio of the maximum peak value of the signal component to the original signal peak value exceeded 0.7, and there is an energy band in the STFT time-frequency map, which corresponds to a frequency distribution range of 1-2 Hz.

Originality/value

The research results have revealed the lateral vibration characteristics of the high-speed train's car body during continuous hunting when passing through turnouts. On this basis, an effective diagnostic method has been proposed. With a focus on practical engineering applications, a rapid screening index for identifying potential issues has been proposed, significantly enhancing the efficiency of diagnostic processes.

High-speed railway  /  Periodic hunting  /  Rapid diagnosis  /  CEEMDAN  /  STFT  /  Permutation entropy
Wanru Xie, Yixin Zhao, Gang Zhao, Fei Yang, Zilong Wei, Jinzhao Liu. Research on the rapid diagnosis method for hunting of high-speed trains[J]. Railway Sciences, 2025 , 4 (1) : 1 -21 . DOI: 10.1108/RS-10-2024-0042
  • the funds of National Natural Science Foundation of China(52308473)
  • China Academy of Railway Science Corporation Limited(2022YJ192)
Year 2025 volume 4 Issue 1
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Article Info
doi: 10.1108/RS-10-2024-0042
  • Receive Date:2024-10-18
  • Online Date:2026-06-11
  • Published:2025-02-10
Article Data
Affiliations
History
  • Received:2024-10-18
  • Revised:2024-12-04
  • Accepted:2024-12-18
Funding
the funds of National Natural Science Foundation of China(52308473)
China Academy of Railway Science Corporation Limited(2022YJ192)
Affiliations
    Infrastructure Inspection Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China
    Infrastructure Inspection Center, China Railway Corp, Beijing, China
    Infrastructure Inspection Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China
    Infrastructure Inspection Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China

Corresponding:

Jinzhao Liu can be contacted at:
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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