王宇 教授

博士/硕士研究生导师

亚太认知智能学会副秘书长、教育部技术发明一等奖、

中国振动工程学会二等奖、科唯睿安 “全球高被引科学家”

  王宇    博士、教授、硕士生导师、博士生导师。 2014年2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。研究方向聚焦装备多模态感知与信息融合、故障诊断和健康管理，主持国家重点研发计划课题、国家自然科学基金面上项目、青年项目，陕西省重点研发计划、航天一院、航天五院、航天六院、中国兵器集团、中国电子科技集团、中船集团等横向合作课题40余项。 研究成果获教育部技术发明一等奖、中国振动工程学会二等奖、中国发明学会二等奖、被评为科唯睿安 “全球高被引科学家”。在IEEE Transactions on Industrial Informatics, IEEE Transactions on Magnetics, IEEE Transactions on Instrument and Measurement，Journal of Sound and Vibration等国际著名学术刊物上发表研究论文100余篇。担任亚太认知智能学会副秘书长，SCI期刊 IEEE Trans. Consumer Elctronics客座编辑、IEEE ACCESS副编辑、IEEE高级会员，中国振动工程学会故障诊断分会理事。指导学生获得中国研究生数学建模大赛一等奖（E组第一）、二等奖等荣誉。

1. 亚太认知智能学会副秘书长

2.SCI期刊 IEEE Trans. CONSUM ELECTR  客座主编（IF： 10.9）

3.  SCI期刊  IEEE Access 副主编  （IF：3.367）

4.  IEEE 高级会员（遴选10%）       

5.  国家自然科学基金评审专家，国家科技专家库专家  

6. 中国振动工程学会故障诊断专业委员会理事

7.担任2021年神经计算与先进应用国际会议程序委员会主席

8.担任2020年神经计算与先进应用国际会议组委会主席

9.担任2019年IEEE SDPC会议分会主席

10. 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),  

Mechanical  System and Signal Processing (MSSP, IF: 6.471),Reliability Engineering  & System Safety (RESS, IF:5.040), Tribology International（IF：4.872）  

Quality and Reliability Engineering International （IF：2.885）  

  Email：ywang95@xjtu.edu.cn

  TEL: 82663689

 王宇    博士、教授、硕士生导师、博士生导师。 2014年2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。研究方向聚焦在装备多模态感知与信息融合、故障诊断和健康管理，主持国家重点研发计划课题、国家自然科学基金面上项目、青年项目，陕西省重点研发计划、航天一院、航天五院、航天六院、中国兵器集团、中船集团等横向合作课题40余项。 研究成果获教育部技术发明一等奖、中国振动工程学会二等奖、中国发明学会二等奖、被评为科唯睿安 “全球高被引科学家”。在IEEE Transactions on Industrial Informatics, IEEE Transactions on Magnetics, IEEE Transactions on Instrument and Measurement，Journal of Sound and Vibration等国际著名学术刊物上发表研究论文100余篇。指导学生获中国研究生数学建模大赛一等奖（E组第一名）、二等奖等荣誉。担任亚太认知智能学会副秘书长，SCI期刊 IEEE Trans. Consumer Elctronics客座编辑、IEEE ACCESS副编辑、IEEE高级会员，中国振动工程学会故障诊断分会理事。

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）

• Liu Y, Wang Y, Chow T W S, et al. Deep adversarial subdomain adaptation network for intelligent fault diagnosis[J]. IEEE Transactions on Industrial Informatics, vol.18, no.9, pp.6038-6046, Sep. 2022, (SCI, EI, 高被引, 中科院一区, IF: 10.215,智能诊断与控制的顶级期刊).
• 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).