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王俊

轨道交通学院教授

学位:博士

办公地址:阳澄湖校区交通大楼261室

毕业院校:中国科学技术大学

电子邮箱:junking@suda.edu.cn

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个人简介

      王俊,苏州大学轨道交通学院教授,博士生导师。苏州大学“优秀青年学者”,江苏省“高层次创新创业人才引进计划”“双创博士”,江苏省科协青年科技人才托举工程资助培养对象,年度科学影响力排行榜全球前2%学者(斯坦福大学与Elsevier联合发布)。主持国家级项目2项、省部级项目4项、市厅级项目2项。已累计发表学术论文70余篇,入选ESI高被引论文4篇、热点论文1篇,获授权中国发明专利20余件,美国国家发明专利3件,中国实用新型专利7件,软件著作权7。是中国振动工程学会故障诊断专业委员会、转子动力学专业委员会和动态信号分析专业委员会理事。主要研究方向为载运工具关键部件安全监控与故障诊断。


教育经历:

  • 博士, 2010.09-2015.06, 精密仪器及机械, 中国科学技术大学, 工学博士学位

  • 本科, 2006.09-2010.06, 测控技术与仪器, 武汉理工大学, 工学学士学位

  • 本科, 2006.09-2010.06, 工商管理, 武汉理工大学, 管理学学士学位


工作经历:

  • 2017.07-今, 苏州大学轨道交通学院, 副教授,教授

  • 2015.07-2017.06, 美国内布拉斯加大学林肯分校, 高级研究助理


代表性论文:

[1]             Jun Wang, He Ren, Changqing Shen, Weiguo Huang, Zhongkui Zhu*Multi-scale style generative and adversarial contrastive networks for single domain generalization fault diagnosis, Reliability Engineering & System Safety, Mar. 2024, 243: 109879. DOI: 10.1016/j.ress.2023.109879.

[2]             He Ren, Jun Wang*, Weiguo Huang, Xingxing Jiang, Zhongkui Zhu, Domain-invariant feature fusion networks for semi-supervised generalization fault diagnosis, Engineering Applications of Artificial Intelligence, Nov. 2023, 126, Part D: 107117. DOI: 10.1016/j.engappai.2023.107117.

[3]             He Ren, Jun Wang*, Changqing Shen, Weiguo Huang, Zhongkui Zhu, Dual classifier-discriminator adversarial networks for open set fault diagnosis of train bearings, IEEE Sensors Journal, 2023, 23(18): 22040-22050. DOI: 10.1109/JSEN.2023.3301593.

[4]             Jun Dai, Jun Wang*,Linquan Yao, Weiguo Huang, Zhongkui Zhu, Categorical feature GAN for imbalanced intelligent fault diagnosis of rotating machinery, IEEE Transactions on Instrumentation and Measurement, 2023, 72: 3525212. DOI:10.1109/TIM.2023.3298425.

[5]             He Ren, Jun Wang*, Zhongkui Zhu, Juanjuan Shi, Weiguo Huang, Domain fuzzy generalization networks for semi-supervised intelligent fault diagnosis under unseen working conditions, Mechanical Systems and Signal Processing, 2023, 200: 110579. DOI: 10.1016/j.ymssp.2023.110579.

[6]             Linghui Lu, Jun Wang*, Weiguo Huang, Changqing Shen, Juanjuan Shi, Zhongkui Zhu, Dual contrastive learning for semi-supervised fault diagnosis under extremely low label rate, IEEE Transactions on Instrumentation and Measurement, 2023, 72: 3520512. DOI: 10.1109/TIM.2023.3284954.

[7]             王俊, 王玉琦, 轩建平, 刘金朝, 黄伟国*, 朱忠奎. 车辆传动系统变参小波流形融合故障诊断方法. 交通运输工程学报, 2023, 23(1): 170–183. DOI: 10.19818/j.cnki.1671-1637.2023.01.013.

[8]             He Ren, Jun Wang*, Jun Dai, Zhongkui Zhu, Jinzhao Liu, Dynamic balanced domain adversarial networks for cross domain fault diagnosis of train bearings, IEEE Transactions on Instrumentation and Measurement, 2022, 71: 3514612. DOI: 10.1109/TIM.2022.3179468.

[9]             Guifu Du, Tao Jiang, Jun Wang*, Xingxing Jiang, Zhongkui Zhu, Improved multi-bandwidth mode manifold for enhanced bearing fault diagnosis, Chinese Journal of Mechanical Engineering, 2022, 35(1): 14. DOI: 10.1186/s10033-022-00677-5.

[10]          Xingxing Jiang, Jun Wang*, Changqing Shen, Juanjuan Shi, Weiguo Huang, Zhongkui Zhu, Qian Wang, An adaptive and efficient VMD and its application for bearing fault diagnosis, Structural Health Monitoring, Sep. 2021, 20(5): 2708-2725. DOI: 10.1177/1475921720970856.

[11]          Jun Wang, Guifu Du, Zhongkui Zhu, Changqing Shen, Qingbo He*, Fault diagnosis of rotating machines based on the EMD manifold, Mechanical Systems and Signal Processing, 2020, 135: 106443. DOI: 10.1016/j.ymssp.2019.106443.

[12]          Jun Dai, Jun Wang*, Weiguo Huang, Juanjuan Shi, Zhongkui Zhu, Machinery health monitoring based on unsupervised feature learning via generative adversarial networks, IEEE/ASME Transactions on Mechatronics, Oct. 2020, 25(5): 2252–2263. DOI: 10.1109/TMECH.2020.3012179.

[13]          Guifu Du, Jun Wang*, Xingxing Jiang, Dongliang Zhang, Longyue Yang, Yihua Hu, Evaluation of rail potential and stray current with dynamic traction networks in multitrain subway systems, IEEE Transactions on Transportation Electrification, Jun. 2020, 6(2): 784–796. DOI: 10.1109/TTE.2020.2980745.

[14]          Guifu Du, Jun Wang*, Zhongkui Zhu, Yihua Hu, Dongliang Zhang, Effect of crossing power restraint on reflux safety parameters in multitrain subway systems, IEEE Transactions on Transportation Electrification, 2019, 5(2): 490–501. DOI: 10.1109/TTE.2019.2899207.

[15]          Jun Wang, Wei Qiao*, Liyan Qu, Wind turbine bearing fault diagnosis based on sparse representation of condition monitoring signals, IEEE Transactions on Industry Applications, 2019, 55(2): 1844–1852. DOI: 10.1109/TIA.2018.2873576.

[16]          戴俊, 王俊*, 朱忠奎, 沈长青, 黄伟国. 基于生成对抗网络和自动编码器的机械系统异常检测. 仪器仪表学报, 2019, 40(9): 16–26. DOI: 10.19650/j.cnki.cjsi.J1905083.

[17]          Jun Wang, Fangzhou Cheng, Wei Qiao*, Liyan Qu, Multiscale filtering reconstruction for wind turbine gearbox fault diagnosis under varying-speed and noisy conditions, IEEE Transactions on Industrial Electronics, 2018, 65(5): 4268–4278.DOI: 10.1109/TIE.2017.2767520.

[18]          Jun Wang, Yayu Peng, Wei Qiao*, Jerry L. Hudgins, Bearing fault diagnosis of direct-drive wind turbines using multiscale filtering spectrum, IEEE Transactions on Industry Applications, 2017, 53(3): 3029–3038. DOI: 10.1109/TIA.2017.2650142.

[19]          Jun Wang, Qingbo He*, Wavelet packet envelope manifold for fault diagnosis of rolling element bearings, IEEE Transactions on Instrumentation and Measurement, 2016, 65(11): 2515–2526. DOI: 10.1109/TIM.2016.2566838.

[20]          Jun Wang, Yayu Peng, Wei Qiao*, Current-aided order tracking of vibration signals for bearing fault diagnosis of direct-drive wind turbines, IEEE Transactions on Industrial Electronics, 2016, 63(10): 6336–6346. DOI: 10.1109/TIE.2016.2571258.

[21]          Jun Wang, Qingbo He*, Fanrang Kong, Multiscale envelope manifold for enhanced fault diagnosis of rotating machines, Mechanical Systems and Signal Processing, 2015, 52-53: 376–392. DOI: 10.1016/j.ymssp.2014.07.021.

[22]          Jun Wang, Qingbo He*, Fanrang Kong, Adaptive multiscale noise tuning stochastic resonance for health diagnosis of rolling element bearings, IEEE Transactions on Instrumentation and Measurement, 2015, 64(2): 564–577. DOI: 10.1109/TIM.2014.2347217.

[23]          Jun Wang, Qingbo He*, Fanrang Kong, An improved multiscale noise tuning of stochastic resonance for identifying multiple transient faults in rolling element bearings, Journal of Sound and Vibration, 2014, 333(26): 7401–7421. DOI: 10.1016/j.jsv.2014.08.041.

[24]          Jun Wang, Qingbo He*, Exchanged ridge demodulation of time-scale manifold for enhanced fault diagnosis of rotating machinery, Journal of Sound and Vibration, 2014, 333(11): 2450–2464. DOI: 10.1016/j.jsv.2014.01.006.

[25]          Jun Wang, Qingbo He*, Fanrang Kong, A new synthetic detection technique for trackside acoustic identification of railroad roller bearing defects, Applied Acoustics, 2014, 85: 69–81. DOI: 10.1016/j.apacoust.2014.04.005.

[26]          Jun Wang, Qingbo He*, Fanrang Kong, Automatic fault diagnosis of rotating machines by time-scale manifold ridge analysis, Mechanical Systems and Signal Processing, 2013, 40(1): 237–256. DOI: 10.1016/j.ymssp.2013.03.007.

[27]          Qingbo He*, Jun Wang, Fei Hu, Fanrang Kong, Wayside acoustic diagnosis of defective train bearings based on signal resampling and information enhancement, Journal of Sound and Vibration, 2013, 332(21): 5635–5649. DOI: 10.1016/j.jsv.2013.05.026.

[28]          Qingbo He*, Jun Wang, Effects of multiscale noise tuning on stochastic resonance for weak signal detection, Digital Signal Processing, 2012, 22(4): 614–621. DOI: 10.1016/j.dsp.2012.02.008.

[29]          Qingbo He*, Jun Wang, Yongbin Liu, Daoyi Dai, Fanrang Kong, Multiscale noise tuning of stochastic resonance for enhanced fault diagnosis in rotating machines, Mechanical Systems and Signal Processing, 2012, 28: 443–457. DOI: 10.1016/j.ymssp.2011.11.021.

研究领域

载运工具关键部件安全监控与故障诊断

1、轨道交通供电回流安全监控:广域回流安全参数分布特性建模与仿真、时空演化机理及交互影响规律分析、在线监测与柔性接地协同控制。

2、车辆关键部件振动信号处理:时频分析、模态分解、稀疏表示、流形学习等先进信号处理方法在微弱故障特征提取与增强中的新理论和新方法。

3、车辆关键部件故障智能诊断:机器学习、深度学习、可解释神经网络等人工智能算法在故障模式识别、剩余使用寿命预测、健康管理等中的新理论和新框架。


开授课程

  • 1、载运工具智能运维, 研究生
  • 2、机械故障诊断, 研究生
  • 3、电路分析, 本科生
  • 4、数字电子与逻辑设计, 本科生
  • 5、测试技术, 本科生
  • 6、自动控制理论, 本科生

科研项目

  • 1、2019.01-2021.12,国家自然科学基金青年科学基金项目,51805342,主持
  • 2、2018.07-2021.06,江苏省自然科学基金青年基金项目,BK20180842,主持
  • 3、2019.01-2020.12,中国博士后基金面上项目,2018M640514,主持
  • 4、2018.06-2019.12,江苏省博士后科研资助计划,2018K006B,主持
  • 5、2019.07-2021.06,江苏省科协青年科技人才托举工程,苏科协发【2019】134号,主持
  • 6、2023.01-2026.12,国家自然科学基金面上项目,52275121,主持
  • 7、2021.06-2023.10,中国博士后基金面上项目,2021M692354,主持

论文

  • 1、已累计发表高水平学术论文70余篇。
  • 2、代表性论文见个人简介。

科技成果

软件著作
  • 1、取得软件著作权7件。
专利
  • 1、获授权中国发明专利20余件。
  • 2、获授权美国国家发明专利3件。
  • 3、获授权中国实用新型专利7件。

荣誉及奖励

  • 1、江苏省“双创博士”,2018.09
  • 2、苏州大学“优秀青年学者”,2017.07
  • 3、中科院院长优秀奖,2014.10
  • 4、博士研究生国家奖学金,2012.12
  • 5、江苏省科协青年科技人才托举工程,2019.09

招生信息

博士研究生:

智能交通系统科学与技术


硕士研究生:

交通运输工程-->交通信息工程及控制

交通运输工程-->载运工具运用工程

式识别与智能系统

车辆工程


交通运输-->交通信息工程及控制

交通运输-->载运工具运用工程