Basic Information

 

王宇 博士、副教授、博士生导师、硕士生导师

 

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2015   上银优秀博士论文佳作奖Hiwin Doctoral Dissertation Award

2013   香港城市大学杰出学术奖Outstanding Academic Perfor-mance Award

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1.  IEEE Access期刊 副主编

(中科院二区, IF 3.367

2.  IEEE 高级会员 (遴选10%    

3.  国家自然科学基金评审专家,

国家科技专家库专家

4. 中国振动工程学会故障诊断

专业委员会理事

6.担任2021年神经计算与

先进应用国际会议程序委员会主席

7.担任2020年神经计算与

先进应用国际会议组委会主席

8.担任2019年IEEE SDPC

会议分会主席

9. 国际著名期刊审稿专家, 包括

IEEE Transactions on Industrial Informatics (IF:10.215),

IEEE Transactions on Industrial Electronics (IF: 8.236),

MechanicalSystem and Signal Processing (MSSP, IF: 6.471),

Reliability Engineering& System Safety (RESS, IF:5.040),

Tribology InternationalIF4.872

Quality and Reliability Engineering International IF2.885

Contact Information

  Email:ywang95@xjtu.edu.cn

  TEL: 82663689

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Main Responsibility

 王宇    博士、副教授、硕士生导师、博士生导师 20142月获得香港城市大学(QS全球排名45位)系统工程及工程管理学系博士学位。2013年到2014年在香港城市大学电子工程系担任副研究员Research Associate)工作。IEEE高级会员,中国振动工程学会故障诊断分会理事。主持和参加国家自然科学基金重点项目、青年项目,博士后基金面上项目、特别资助项目,国家重点实验室项目,企业横向合作课题等近20项。在IEEE Transactions on Industrial Informatics, IEEE Transactions on Magnetics, IEEE Transactions on Instrument and MeasurementJournal of Sound and Vibration等国际著名学术刊物上发表研究论文40篇,其中SCI收录30篇,EI收录10篇,其中数篇论文ESI高被引,已发表论文至今已被引用1000余次。申请国家发明专利10项,已授权7项。

 

Work Experience

  1. 装备运行可靠性分析与寿命预测
  2. 系统故障预测与健康管理(PHM)
  3. 基于大数据分析的智能制造与维护
  4. 基于深度学习理论的设备故障诊断与剩余寿命预测技术(对抗学习、迁移学习、贝叶斯深度学习、深度强化学习)

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  • J. Li, Y. Wang*, Y. Zi and Z. Zhang, "Whitening-Net: A Generalized Network to Diagnose the Faults Among Different Machines and Conditions," IEEE Transactions on Neural Networks and Learning Systems, Apr. 2021,(SCI, EI, 中科院一区, IF: 10.451,计算机和神经网络计算的顶级期刊).
  • Y. Wang, Y. Peng and T. W. S. Chow, “Adaptive Particle Filter-Based Approach for RUL Prediction Under Uncertain Varying Stresses With Application to HDD,” IEEE Transactions on Industrial Informatics, Sept 2021, (SCI, EI, 中科院一区, IF: 10.215,智能诊断与控制的顶级期刊).
  • Y. Wang, L. He, S. Jiang and T. W. S. Chow, "Failure Prediction of Hard Disk Drives Based on Adaptive Rao–Blackwellized Particle Filter Error Tracking Method," IEEE Transactions on Industrial Informatics, vol. 17, no. 2, pp. 913-921, Feb. 2021,(SCI, EI, 中科院一区, IF: 10.215,智能诊断与控制的顶级期刊).
  • Y. Peng, Y. Wang*, and Y. Zi, "Switching state-space degradation model with recursive filter/smoother for prognostics of remaining useful life," IEEE Transactions on Industrial Informatics, Vol. 15, no. 2, pp. 822 - 832, Feb. 2019(SCI, EI,中科院一区, IF: 10.215,智能诊断与控制的顶级期刊).
  • Y. Wang, Y. Peng, Y. Zi, X. Jin and K. Tsui, "A Two-Stage Data-Driven-Based Prognostic Approach for Bearing Degradation Problem," IEEE Transactions on Industrial Informatics, vol. 12, no. 3, pp. 924-932, June 2016, (SCI, EI, 中科院一区, IF: 10.215,智能诊断与控制的顶级期刊).

  • Y. Wang, E. W. M. Ma, T. W. S. Chow and K. Tsui, "A Two-Step Parametric Method for Failure Prediction in Hard Disk Drives," IEEE Transactions on Industrial Informatics, vol. 10, no. 1, pp. 419-430, Feb. 2014, (SCI, EI, 中科院一区, IF: 10.215,智能诊断与控制的顶级期刊).

  • Y. Peng, Y. Wang*, G. Wang and K. L. Tsui, "Doubly Stochastic Cumulative Damage Model for RUL Prediction of HDDs in Uncertain Operating Environments," IEEE Transactions on Industrial Electronics, Aug. 2020, (SCI, EI, 中科院一区, IF: 8.236,智能诊断与控制的顶级期刊).
  • Y. Peng, Y. Wang*, J. S. Xie, Y. Zi, “Adaptive stochastic-filter-based failure prediction model for complex repairable systems under uncertainty conditions,” Reliability Engineering & System Safety, vol. 204, Dec. 2020, (SCI, EI, 中科院一区, IF: 5.04,可靠性的顶级期刊).
  • G. Wang, Y. Wang* and X. Sun, "Multi-Instance Deep Learning Based on Attention Mechanism for Failure Prediction of Unlabeled Hard Disk Drives," IEEE Transactions on Instrumentation and Measurement, vol. 70, pp. 1-9, Apr 2021, (SCI, EI, IF: 4.016).

  • J. Li, Y. Wang*, Y. Zi, X. Sun and Y. Yang, “A Current Signal-Based Adaptive Semisupervised Framework for Bearing Faults Diagnosis in Drivetrains,” IEEE Transactions on Instrumentation and Measurement, vol. 70, pp. 1-12, Jan. 2021, (SCI, EI, IF: 4.016).

  • Y. Wang, X. Sun, J. Li and Y. Yang, “Intelligent Fault Diagnosis With Deep Adversarial Domain Adaptation,” IEEE Transactions on Instrumentation and Measurement, vol. 70, pp. 1-9, Jan. 2021, (SCI, EI, IF: 4.016).

  • A. Yang, Y. Wang*, Y. Zi and T. W. S. Chow, "An Enhanced Trace Ratio Linear Discriminant Analysis for Fault Diagnosis: An Illustrated Example Using HDD Data," IEEE Transactions on Instrumentation and Measurement, vol. 68, no. 12, pp. 4629-4639, Dec. 2019, (SCI, EI, IF: 4.016).