叶运广

硕士生导师

个人信息Personal Information


学历:博士研究生毕业

学位:工学博士学位

办公地点:牵引红楼313

性别:

所在单位:轨道交通运载系统全国重点实验室

报考该导师研究生的方式

欢迎你报考叶运广老师的研究生,报考有以下方式:

1、参加西南交通大学暑期夏令营活动,提交导师意向时,选择叶运广老师,你的所有申请信息将发送给叶运广老师,老师看到后将和你取得联系,点击此处参加夏令营活动

2、如果你能获得所在学校的推免生资格,欢迎通过推免方式申请叶运广老师研究生,可以通过系统的推免生预报名系统提交申请,并选择意向导师为叶运广老师,老师看到信息后将和你取得联系,点击此处推免生预报名

3、参加全国硕士研究生统一招生考试报考叶运广老师招收的专业和方向,进入复试后提交导师意向时选择叶运广老师。

4、如果你有兴趣攻读叶运广老师博士研究生,可以通过申请考核或者统一招考等方式报考该导师博士研究生。

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  • 一、轨道车辆服役安全监测

    [1] Ye Y*, Li H, Wang Q, Li F, Yi C, Peng X, Huang C, Zeng J. Fault diagnosis of railway wheelsets: A review[J]. Measurement, 2025, 116169.

    [2] Li H, Wang Y, Zeng J, Li F, Yang Z, Mei G, Gao H, Ye Y*. Fusing binocular vision and deep learning to detect dynamic wheel-rail displacement of high-speed trains[J]. Mechanical Systems and Signal Processing, 2025, 223: 111832.

    [3] Ye Y*, Li H, Li F, Gao H, Mei G, Dai H, Wu P, Zeng J. Online assessment of train hunting stability by monitoring dynamic wheel-rail displacement: why and how?[J]. Nonlinear Dynamics, 2024, 112: 11993-12017.

    [4] Li H, Wang Y, Zeng J, Li F, Yang Z, Mei G, Ye Y*. Virtual point tracking method for online detection of relative wheel-rail displacement of railway vehicles[J]. Reliability Engineering & System Safety, 2024, 246: 110087.

    [5] Ye Y*, Huang C, Zeng J, Zhou Y, Li F. Shock detection of rotating machinery based on activated time-domain images and deep learning: An application to railway wheel flat detection[J]. Mechanical Systems and Signal Processing, 2023, 186: 109856.


    二、轮轨动力学

    [1] Ye Y, Qu S, Wei L, Li D, Huang C, Wang J, Tao Z, Gan F, Gao H, Zhu B, Wu P, Zeng J, Dai H*. Localized rail third-order bending mode causes high-order polygonization of high-speed train wheels[J]. Mechanical Systems and Signal Processing, 2025, 223: 111816.

    [2] Ye Y*, Huang C, Zeng J, Wang S, Liu C, Li F. Predicting railway wheel wear by calibrating existing wear models: Principle and application[J]. Reliability Engineering & System Safety, 2023, 238: 109462.

    [3] Ye Y, Huang P*, Sun Y, Shi D. MBSNet: A deep learning model for multibody dynamics simulation and its application to a vehicle-track system[J]. Mechanical Systems and Signal Processing, 2021, 157: 107716.

    [4] Ye Y*, Sun Y*, Shi D, Peng B, Hecht M. A wheel wear prediction model of non-Hertzian wheel-rail contact considering wheelset yaw: Comparison between simulated and field test results[J]. Wear, 2021, 474-475: 203715.

    [5] Ye Y*, Shi D, Krause P, Tian Q, Hecht M. Wheel flat can cause or exacerbate wheel polygonization[J]. Vehicle System Dynamics, 2019, 58(10): 1575–1604.