Center of Structural Monitoring and Control

Harbin Institute of Technology

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Welcome to the Center of SMC

Congratulations!

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Dr. Shunlong Li and Prof. Hui Li as coauthors with Dr. Songye Zhu and Prof. YoulinXu at Hongkong Polytechnic University have gained the 2014 Kobori Prize for the highest-ranked paper, namely “Long-term condition assessment of suspenders under traffic loads based on structural monitoring system: Application to the Tsing Ma Bridge”, Structural Control and Health MonitoringVolume 19, Issue 1, February 2012, Pages: 82–101, Shunlong Li, Songye Zhu, You-Lin Xu, Zhi-Wei Chen and Hui Li.

http://onlinelibrary.wiley.com/doi/10.1002/stc.427/abstract

The 2014 Kobori Prize for the highest-ranked paper was selected from all papers published in the International Journal during 2011 and 2012 by Kobori PrizeCommittee.

Last Updated on Tuesday, 10 June 2014 11:33
 

Lecture Notification

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With Prof. Hui Li and Dr.Shunlong Li's gracious invitation,Mr.Yongchao Yang(杨永超) from Rice University will visit Centre of Structural Monitoring and Control (SMC) at Harbin Institute of Technology and make a presentation on May 16, 2014. We sincerely welcome the interested faculties and students to join in.

Topic:Data-driven structural health monitoring by unsupervised machine learning and sparse representation

The lecture room: 402, School of Civil Engineeering

May16, 9:00am-10:00am

ABSTRACT

Civil infrastructure is subjected to ambient loads, natural hazards, and man-made extreme events, which can cause deterioration, damage, and even catastrophic failure of structures. Dense networks of sensors embedded in structures, which continuously record structural data, make possible real-time health monitoring and assessment of structures. Effectively and efficiently sensing and processing the massive sensor data, potentially from hundreds of channels, is required to identify (update) structural information and detect damage as early as possible to inform immediate decision-making. Different from traditional model based and parametric methods, this presentation will discuss the potential of a novel data-driven framework towards rapid and unsupervised system identification and damage detection of structures, as well as efficient data management in structural health monitoring. Laboratory experiments on bench-scale structures, and real-world structures examples, including a seismically excited building, a large-scale cable-stayed bridge, and a super high-rise TV tower, will be demonstrated.

Biography of Yongchao Yang


Yongchao Yang is a Ph.D. Candidate in the Department of Civil and Environmental Engineering at Rice University. He received his bachelor’s degree in Civil Engineering from Harbin Institute of Technology, China in 2010. His research focuses on novel data sensing and processing for system identification and damage detection of civil structures. His work results in more than ten journal publications in ASCE Journal of Structural Engineering, Earthquake Engineering and Structural Dynamics, Mechanical Systems and Signal Processing, etc.

 

SHM benchmark problem was issued

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SHMC is sharing a benchmark problem based on a real bridge with the SHM community. This benchmark problem has completed recently. The data used in this problem were collected by an in-situ structural health monitoring system implemented into a full-scale cable-stayed bridge before and after the bridge was damaged, which is very rare in structural health monitoring field. 

Please click the menu in the left to find the information about this benchmark problem and download measured data. 

More detailed information about this benchmark problem can be found in following paper: http://onlinelibrary.wiley.com/doi/10.1002/stc.1559/pdf.

Please note that all compressed data files were encrypted. If you are interested in this benchmark problem, please send email to  This e-mail address is being protected from spambots. You need JavaScript enabled to view it to request the password. If you have any questions about the data and structural information, please send email to  This e-mail address is being protected from spambots. You need JavaScript enabled to view it or  This e-mail address is being protected from spambots. You need JavaScript enabled to view it .

 
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