Bin Yang received the B.S. and M.S. degrees in Mechatronics Engineering from Chang’an University, Xi’an, P.R. China, in 2014 and 2017, respectively, and then received the Ph.D. degree in Mechanical Engineering from Xi’an Jiaotong University, Xi’an, P.R. China, in 2022. He is currently an Assistant Professor with School of Mechanical Engineering, Xi’an Jiaotong University. He was also a Visiting Ph.D. Student of the Centre of Maintenance Optimization and Reliability Engineering (C-MORE) at the University of Toronto, Canada. He is also a Member of IEEE, ASME and IET, a senior member of CMES, and a reviewer of MSSP, IEEE TIE, TII, TNNLS, etc.

His research interests include the methodology and technology of transfer learning in machinery condition monitoring and fault diagnosis. He has published serials of articles in the authorized Top journals, such as Mechanical Systems and Signal Processing, IEEE Transactions on Industrial Electronics, etc. With the achievements, he has developed intelligent fault diagnosis system for bearing manufacturing defects, which performs well at SKF’s largest manufacturing base of roller element bearings around world. In 2022, he has been elected into the Program for Supporting Young and Excellent Talents at Xi’an Jiaotong University.

  Career                                                                                                                                                                                                      

• 2022.10 - Present      Assistant Professor, School of Mechanical Engineering, Xi'an Jiaotong University, P.R. China

• 2022.09 - Present      Postdoctoral Fellow, School of Mechanical Engineering, Xi'an Jiaotong University, P.R. China

  Education                                                                                                                                                                                                

• 2017.09 - 2022.07      Ph.D., Mechanical Engineering, Xi'an Jiaotong University, P.R. China

• 2019.11 - 2020.11      Visiting Ph.D. Student, Mechanical and Industrial Engineering, University of Toronto, Canada

• 2014.09 - 2017.06      M.S., Mechatronics Engineering, Chang'an University, P.R. China

• 2010.09 - 2014.06      B.S., Mechatronics Engineering, Chang'an University, P.R. China

  Research Interests                                                                                                                                                                                

• Methodology and technology of transfer learning in machinery fault diagnosis

• Big-data-driven intelligent maintenance of machines

• Industrial applications of intelligent fault diagnosis with big-data era

  Selected Publications                                                                                                                                                                           

• Bin Yang, Yaguo Lei, Xiang Li, Naipeng Li. Targeted transfer learning through distribution barycenter medium for intelligent fault diagnosis of machines with data decentralization[J]. Expert Systems With Applications, 2024, 244: 122997.

• Bin Yang, Yaguo Lei*, Xiang Li, Naipeng Li, Asoke K. Nandi. Label recovery and trajectory designable network for transfer fault diagnosis of machines with incorrect annotation[J]. IEEE/CAA Journal of Automatica Sinica, 2024, 11(4): 932-945.

• Bin Yang, Yaguo Lei*, Xiang Li, Clive Roberts. Deep targeted transfer learning along designable adaptation trajectory for fault diagnosis across different machines[J]. IEEE Transactions on Industrial Electronics, 2023, 70(9): 9463-9473.

• Bin Yang, Yaguo Lei*, Songci Xu, Chi-Guhn Lee. An optimal transport-embedded similarity measure for diagnostic knowledge transferability analytics across machines[J]. IEEE Transactions on Industrial Electronics, 2022, 69(7): 7372-7382.

• Bin Yang, Songci Xu, Yaguo Lei*, Chi-Guhn Lee, Edward Stewart, Clive Roberts. Multi-source transfer learning network to complement knowledge for intelligent diagnosis of machines with unseen faults[J]. Mechanical Systems and Signal Processing, 2022, 162: 108095.

• Bin Yang, Chi-Guhn Lee, Yaguo Lei*, Naipeng Li, Na Lu. Deep partial transfer learning network: A method to selectively transfer diagnostic knowledge across related machines[J]. Mechanical Systems and Signal Processing, 2021, 156: 108095.

• Bin Yang, Yaguo Lei*, Feng Jia, Naipeng Li, Zhaojun Du. A polynomial kernel induced distance metric to improve deep transfer learning for fault diagnosis of machines[J]. IEEE Transactions on Industrial Electronics, 2020, 67(11): 9747-9757.

• Bin Yang, Yaguo Lei*, Feng Jia, Saibo Xing. An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings[J]. Mechanical Systems and Signal Processing, 2019, 122: 692-706.

• Yaguo Lei*, Bin Yang, Xinwei Jiang, Feng Jia, Naipeng Li, Asoke K. Nandi. Applications of machine learning to machine fault diagnosis: A review and roadmap[J]. Mechanical Systems and Signal Processing, 2020, 138: 106587.