Instrumentation & Measurement Magazine 25-8 - 9

The Attraction of New Members
As a newborn technical committee, TC-3 welcomes and wishes
to attract more members into the family, including industry
professionals, university teachers, researchers, and graduate
students. Young scholars, including Ph.D. students, researchers,
and lecturers, who join the TC-3 through research projects,
will be rising stars to push forward the sustainable development
of TC-3 and the IMS.
International Communication
TC-3 aims at establishing a communication platform for both
domestic and international experts. As described above, TC-3
will organize conferences, seminars, and workshops expertizing
in condition monitoring and fault diagnosis. Meanwhile,
TC-3 will continue to pay attention to COVID-19 prevention
during these activities, to ensure all the participants are
in good health. In the future, TC-3 will keep extending the
academic network through active communication with international
research groups and participation in international
academic activities.
Conclusions
In the past few years, TC-3 has done a great job in communicating
and exchanging information between industry and
academia. IMS and I&M Magazine have always provided
strong support for TC-3 to carry out joint research projects and
organize academic activities. In the future, with the consistent
support of the Society and the Magazine, TC-3 will play a
more active role in the field of condition monitoring and fault
diagnosis.
Acknowledgment
The authors would like to thank the IMS for the continuous
support of TC-3's work. Besides, the authors would also like to
thank all of the TC-3 members for their remarkable contributions
to the activities and research projects of TC-3, including
Prof. Zhaoyan Fan, Prof. Peng Wang, Prof. Xingwu Zhang,
Prof. Qingbo He, Prof. Datong Liu, Prof. Zhibo Yang, and Prof.
Ruqiang Yan.
References
[1] W. Li, R. Huang, J. Li, Y. Liao, Z. Chen, et al., " A perspective
survey on deep transfer learning for fault diagnosis in industrial
scenarios: theories, applications and challenges, " Mechanical
Systems and Signal Processing, vol. 167, p. 108487, 2022.
[2] I. Garcia, J. Beloki and J. Zubia, " An optical fiber bundle sensor
for tip clearance and tip timing measurements in a turbine rig, "
Sensors, vol. 13, pp. 7385-7398, 2013.
[3] Y. Li, Z. Zhou, C. Sun, R. Yan and X. Chen, " Domain adaptive
sparse transformer for aeroengine bevel gear fault diagnosis, " in
Proc. 2021 Int. Conf. Sensing, Meas. Data Analytics in era of Artificial
Intell. (ICSMD), pp. 1-6, 2021.
[4] J. Xia, R. Huang, Y. Liao, Z. Chen and W. Li, " Dynamic modeling
of gearbox based on virtual-physical interaction, " in Proc. 2021
Int. Conf. Sensing, Meas. Data Analytics in era of Artificial Intell.
(ICSMD), pp. 1-5, 2021.
[5] J. Chen, J. Li, R. Huang, K. Yue, Z. Chen and W. Li, " Federated
learning for bearing fault diagnosis with dynamic weighted
averaging, " in Proc. 2021 Int. Conf. Sensing, Meas. Data Analytics in
era of Artificial Intell. (ICSMD), pp. 1-6, 2021.
[6] Z. Zhou, T. Li, Z. Zhao, C. Sun, R. Yan, and X. Chen,
" Differentiable architecture search for aeroengine bevel gear fault
diagnosis, " in Proc. 2020 Int. Conf. Sensing, Meas. Data Analytics in
era of Artificial Intell. (ICSMD), pp. 270-274, 2020.
[7] J. Wu, Z. Zhao, H. Shang, C. Sun, R. Yan and X. Chen, " Machine
anomaly detection under changing working condition with
syncretic self-regression auto-encoder, " in Proc. 2021 IEEE Int.
Instrum. Meas. Technol. Conf. (I2MTC), pp. 1-5, 2021.
[8] B. An, S. Wang, R. Yan, W. Li, and X. Chen, " Generalized gaussian
noise distribution enabled sparse representation model for
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Technol. Conf. (I2MTC), pp. 1-5, 2020.
Weihua Li (M'12-SM'19, whlee@scut.edu.cn) is a Professor
and the Deputy Dean of the Shien-Ming Wu School of
Intelligent Engineering at the South China University of Technology
in Guangzhou, China. He received the Ph.D. degree
in mechanical engineering from the Huazhong University
of Science and Technology, China in 2003. His research interests
include industrial Big Data, intelligent maintenance and
health management, digital twins, and intelligent connected
vehicles.
Xuefeng Chen (chenxf@mail.xjtu.edu.cn) is a Full Professor
and Dean of the School of Mechanical Engineering at Xi'an Jiaotong
University in Shaanxi, China, where he received his
Ph.D. degree in 2004. His main research fields are mechanical
structure design and dynamic analysis, finite element method
and digital manufacturing, mechanical fault diagnosis and life
prediction.
November 2022
IEEE Instrumentation & Measurement Magazine
9
Instrumentation & Measurement Magazine 25-8

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