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Dynamic response diagnosis method for poor condition of high-speed railway fasteners
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Liangqi ZHOU1, Jinzhao LIU2, Xiaodi XU2, Zhongyan LI1
Journal of Vibration Engineering | 2025, 38(8) : 1739 - 1746
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Journal of Vibration Engineering | 2025, 38(8): 1739-1746
Dynamic response diagnosis method for poor condition of high-speed railway fasteners
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Liangqi ZHOU1, Jinzhao LIU2, Xiaodi XU2, Zhongyan LI1
Affiliations
  • 1.School of Mathematics and Physics,North China Electric Power University,Beijing 102206,China
  • 2.Infrastructure Inspection Research Institute,China Academy of Railway Sciences Corporation Limited,Beijing 100081,China
Published: 2025-08-10 doi: 10.16385/j.cnki.issn.1004-4523.202305008
Outline
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In order to improve the intelligence of fastener disease diagnosis,a fastener condition diagnosis method is proposed based on vehicle dynamic response data and generalized demodulation time-frequency analysis combined with sparrow search algorithm-support vector machine (SSA-SVM) model. The acceleration signals of the normal and abnormal sections of the fastener are collected,and the short-time Fourier transform and the maximum overlapping discrete wavelet packet transform are used to preprocess the signal data. The generalized demodulation time-frequency analysis method is used to decompose the signal,and the effective value,energy contribution rate and wavelength of the main information components are calculated as the characteristic index. The characteristic index is trained by the joint SSA-SVM model to construct the classification model. The results show that the accuracy of the method is 97.50%,and several evaluation indicators are used to verify that its effectiveness and accuracy can meet the actual needs.

fastener status diagnostics  /  vehicle dynamic response  /  generalized demodulation time-frequency analysis method  /  SSA-SVM model
Liangqi ZHOU, Jinzhao LIU, Xiaodi XU, Zhongyan LI. Dynamic response diagnosis method for poor condition of high-speed railway fasteners[J]. Journal of Vibration Engineering, 2025 , 38 (8) : 1739 -1746 . DOI: 10.16385/j.cnki.issn.1004-4523.202305008
Year 2025 volume 38 Issue 8
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Article Info
doi: 10.16385/j.cnki.issn.1004-4523.202305008
  • Receive Date:2023-05-04
  • Online Date:2026-02-09
  • Published:2025-08-10
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History
  • Received:2023-05-04
  • Revised:2023-07-12
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Affiliations
    1.School of Mathematics and Physics,North China Electric Power University,Beijing 102206,China
    2.Infrastructure Inspection Research Institute,China Academy of Railway Sciences Corporation Limited,Beijing 100081,China
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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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