Special Session


Structural Health Monitoring in Aerospace Structures | 航空航天结构健康监测


Submission Guideline:

Please submit your manuscript via Online Submission System: http://www.zmeeting.org/submission/meae2024
please choose Special Session: Structural Health Monitoring in Aerospace Structures



Organizers 专题组织者

Dr. Jingjing He, Beihang University, China

Dr. Jingjing He is an associate professor affiliated with the School of Reliability and Systems Engineering at Beihang University, Beijing, China. She received her Ph.D. 2012 in Civil Engineering at Clarkson University, NY, US. Prior to this, she received her MS and BEng from Beihang University. She was a visiting scholar in the department of Civil and Engineering Mechanics at Columbia University from 2015-2017. Her research is focused on structural health monitoring using ultrasonics and applications, smart materials and structures, fatigue and fracture of engineering materials and structures. She serves as an associate editor of ASME Journal of NDE.

Dr. Xun Wang, Beihang University, China

Dr. Xun Wang received his Ph.D. in acoustics in Dec 2014 from the Sorbonne University - University of Technology of Compiègne, France. He was a postdoctoral fellow at the Aix-Marseille University, France, between Mar 2015 and Sept 2016 and a Research Associate at the Hong Kong University of Science and Technology between Oct 2016 and Feb 2020. He joined the Beihang University, China, in Apr 2020 and has been a Full Professor since Feb 2022. Dr. Xun Wang has published around 50 research papers in leading journals in acoustics, signal processing, and hydraulic/oceanic engineering. His research interests include acoustical inverse problems, acoustic imaging, structural health monitoring, and uncertainty quantification.


Introduction 专题介绍

Structural health monitoring (SHM) is widely used in aerospace structures, which allows condition-based maintenance to reduce the repair cost and increase the safety of structure. This special session focuses on enhancing safety, efficiency, availability and effectiveness of systems through monitoring, predicting and managing the health status for aerospace engineering. Academics working on the following topics (not limited to) are very much welcomed:

* Monitoring, Diagnostic and Prognostic Methods.

* Advanced sensing technologies.

* Data-driven Prognostics.

* Industrial Big Data Analytics.

* SHM in Smart Manufacturing System.

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