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:男
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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- Song C, Tao Z, Li D, Qu S, Wei L, Huang C, Dai H, Ye Y*. Formation mechanism of high-order wheel polygonization of high-speed trains in China: a decade-long debate[J]. Wear, 2025, 578-579: 206209.
- Li D, Ye Y, Li F, Wang Q, Tao Z, Wei L, Shi H, Qu S, Dai H*. A model-based method for wheel out-of-roundness detection considering rail flexibility and multi-wheel interaction[J]. Mechanical Systems and Signal Processing, 2025, 233: 112745.
- Tao Z, Li D, Wei L, Ma C, Qu S, Huang C, Gao H, Zhu B, Dai H, Ye Y*. Influence of high-frequency vibration-absorbing fasteners on suppressing localized rail bending modal vibration[J]. Railway Engineering Science, 2025.
- Huang C*, Ye Y, Zeng J, Song C. Stability assessment of railway vehicles considering undefined nonlinearity in static force–velocity characteristics of hydraulic yaw dampers[J]. Vehicle System Dynamics, 2024.
- Zhu T, Ren Y, Shi H, Ye Y, Feng P, Su Z, Yao C, Ma G*. Wheel-rail force inversion via transfer learning-based residual LSTM neural network with temporal pattern attention mechanism[J]. Mechanical Systems and Signal Processing, 2025, 224: 112135.
- 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, 242: 116169.
- 叶运广*, 高旭, 邬平波, 戴焕云, 曾京. 欧盟列车动力学性能评价标准的解读、仿真及试验应用[C]. 中国铁道学会牵引动力委员会 2024 年机车车辆动力学及强度技术研讨会论文集, 2024: 40-53.
- Zhu T, Ren Y, Shi H, Ye Y, Feng P, Su Z, Yao C, Ma G*. Wheel-rail force inversion via transfer learning-based residual LSTM neural network with temporal pattern attention mechanism[J]. Mechanical Systems and Signal Processing, 2025, 224: 112135.
- Gao H*, Pfaff R, Babilon K, Ye Y. A comprehensive wheel–rail contact model incorporating sand fragments and its application in vehicle braking simulation[J]. Vehicle System Dynamics, 2024.
- 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.