Fatigue Properties and Life Prediction of Ultrasonic Rolling EA4T Axle Steel

ZHANG Jiwang; ZHANG Haonan; YANG Bing; SU Kaixin; LI Hang

doi:10.3969/j.issn.0258-2724.20220257

Volume 59 Issue 6

Dec. 2024

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Journal of Southwest Jiaotong University > 2024 > 59(6): 1305-1313.

ZHANG Jiwang, ZHANG Haonan, YANG Bing, SU Kaixin, LI Hang. Fatigue Properties and Life Prediction of Ultrasonic Rolling EA4T Axle Steel[J]. Journal of Southwest Jiaotong University, 2024, 59(6): 1305-1313. doi: 10.3969/j.issn.0258-2724.20220257

Citation:

ZHANG Jiwang, ZHANG Haonan, YANG Bing, SU Kaixin, LI Hang. Fatigue Properties and Life Prediction of Ultrasonic Rolling EA4T Axle Steel[J]. Journal of Southwest Jiaotong University, 2024, 59(6): 1305-1313. doi: 10.3969/j.issn.0258-2724.20220257

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Fatigue Properties and Life Prediction of Ultrasonic Rolling EA4T Axle Steel

doi: 10.3969/j.issn.0258-2724.20220257

1.
State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610036, China
2.
Aerospace Science and Industry Inertial Technology, Beijing 100070, China

Received Date: 10 Apr 2022
Rev Recd Date: 18 May 2022

Available Online: 09 Nov 2023

Publish Date: 25 May 2022

Abstract

Abstract

In order to study the influence of surface ultrasonic rolling processing (SURP) on the fatigue properties of EA4T axle steel, the EA4T axle steel specimens were firstly treated by SURP technology, and the surface properties of the treated specimens were analyzed. The 3D surface morphologies, roughness, hardness, residual stress, full width at half maximum (FWHM), and crystal size were investigated. Then, the fatigue tests were carried out on the EA4T axle steel specimens using a rotary bending fatigue testing machine. The stress–fatigue life (S-N) curves and crack propagation behaviors were obtained, and the effect of SURP on fatigue properties and crack propagation behaviors of EA4T axle steels was analyzed. Finally, a back propagation (BP) neural network was used to establish the fatigue life prediction model of SURP EA4T axle steel, which took load stress amplitude, surface roughness, surface FWHM, surface hardness, hardened layer depth, surface residual stress, and depth of residual stress layer as input. In addition, the life of SURP EA4T axle steel specimens was predicted. The results show that SURP can reduce the surface roughness of the specimens to 0.17 μm and remove the groove morphology. Meanwhile, the surface hardness of the specimens is improved to 420 HV, and a surface residual stress of about −500 MPa and a residual stress layer with a depth of about 550 μm are introduced. There are conventional fatigue limits for grinding specimens, grinding with polishing specimens, as well as SURP specimens. The fatigue properties of grinding specimens and grinding with polishing specimens are basically the same, with a fatigue limit of 355 MPa. The fatigue property of SURP specimens is improved significantly, with a fatigue limit of 455 MPa, an increase of 28% compared with the grinding specimens. Fatigue fracture observations show that the fatigue cracks of all specimens initiate from the surface, and SURP cannot change the fatigue damage mechanism of the specimen. SURP can increase the threshold value of crack propagation of the specimen from 6.29 MPa·m^1/2 to 11.21 MPa·m^1/2, and it can slow down the crack initiation and propagation of short cracks, thus significantly improving the fatigue property of EA4T axle steel. The fatigue life prediction model of SURP EA4T axle steel has a prediction accuracy of 88.5%.
- EA4T axle steel,
- ultrasonic rolling,
- fatigue property,
- threshold value of crack propagation,
- BP neural network

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References(23)

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Fatigue Properties and Life Prediction of Ultrasonic Rolling EA4T Axle Steel

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