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Characterization, identification and life prediction of acoustic emission signals of tensile damage for HSR gearbox housing material
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Ai Yibo, Yuanyuan Zhang, Cui Hao, Weidong Zhang
Railway Sciences | 2023, 2(2) : 225 - 242
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Railway Sciences | 2023, 2(2): 225-242
Research paper
Characterization, identification and life prediction of acoustic emission signals of tensile damage for HSR gearbox housing material
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Ai Yibo, Yuanyuan Zhang, Cui Hao, Weidong Zhang
Affiliations
  • National Center for Materials Service Safety, University of Science and Technology Beijing, Beijing, China
Published: 2023-06-10 doi: 10.1108/RS-01-2023-0007
Outline
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Purpose

This study aims to ensure the operation safety of high speed trains, it is necessary to carry out nondestructive monitoring of the tensile damage of the gearbox housing material in rail time, yet the traditional tests of mechanical property can hardly meet this requirement.

Design/methodology/approach

In this study the acoustic emission (AE) technology is applied in the tensile tests of the gearbox housing material of an high-speed rail (HSR) train, during which the acoustic signatures are acquired for parameter analysis. Afterward, the support vector machine (SVM) classifier is introduced to identify and classify the characteristic parameters extracted, on which basis the SVM is improved and the weighted support vector machine (WSVM) method is applied to effectively reduce the misidentification of the SVM classifier. Through the study of the law of relations between the characteristic values and the tensile life, a degradation model of the gearbox housing material amid tensile is built.

Findings

The results show that the growth rate of the logarithmic hit count of AE signals and that of logarithmic amplitude can well characterize the stage of the material tensile process, and the WSVM method can improve the classification accuracy of the imbalanced data to above 94%. The degradation model built can identify the damage occurred to the HSR gearbox housing material amid the tensile process and predict the service life remains.

Originality/value

The results of this study provide new concepts for the life prediction of tensile samples, and more further tests should be conducted to verify the conclusion of this research.

HSR gearbox housing  /  Damage identification  /  Acoustic emission technology  /  Support vector machine  /  Weighted  /  Life prediction
Ai Yibo, Yuanyuan Zhang, Cui Hao, Weidong Zhang. Characterization, identification and life prediction of acoustic emission signals of tensile damage for HSR gearbox housing material[J]. Railway Sciences, 2023 , 2 (2) : 225 -242 . DOI: 10.1108/RS-01-2023-0007
  • the National Natural Science Foundation of China(U61273205)
Year 2023 volume 2 Issue 2
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Article Info
doi: 10.1108/RS-01-2023-0007
  • Receive Date:2023-01-30
  • Online Date:2026-06-11
  • Published:2023-06-10
Article Data
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History
  • Received:2023-01-30
  • Revised:2023-02-03
  • Accepted:2023-02-03
Funding
the National Natural Science Foundation of China(U61273205)
Affiliations
    National Center for Materials Service Safety, University of Science and Technology Beijing, Beijing, China

Corresponding:

Zhang Weidong 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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