Application of draw-wire displacement sensors on structural health monitoring of Jiangyin Bridge

2006 ◽  
Author(s):  
Zhendong Qian ◽  
Yehua Fan ◽  
Zhenbo Lu
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Health ◽  
Displacement Sensors

New Directions of Health Monitoring for Building Structures

2016 ◽  
Vol 101 ◽  
pp. 15-19
Author(s):  
Akira Nishitani ◽  
Ping Xiang ◽  
Shohei Marutani ◽  
Tomohiko Hatada ◽  
Ryuta Katamura
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Building Structures ◽  
Structural Health ◽  
Displacement Sensors ◽  
New Directions ◽  
Story Drift ◽  
Direct Sensing ◽  
Structural Engineers

The concept of structural health monitoring (SHM) has appealed the attentions of structural engineers. However, most of the proposed schemes for SHM do not seem “friendly” to the practicing engineers in terms of the used data or employed methods. In this regard, the direct sensing of inter-story drift displacements could open the door to the construction of “practicing engineers friendly” SHM schemes. The authors‘ group developed non-contact types of inter-story drift displacement sensors. Several schemes based on the drift displacement sensing are discussed, which do not involve heavy researchers-oriented processes.

scholarly journals Integration of High-Resolution Laser Displacement Sensors and 3D Printing for Structural Health Monitoring

Sensors ◽  
2017 ◽  
Vol 18 (2) ◽  
pp. 19 ◽  
Author(s):  
Shu-Wei Chang ◽  
Tzu-Kang Lin ◽  
Shih-Yu Kuo ◽  
Ting-Hsuan Huang
Keyword(s):  
High Resolution ◽  
Structural Health Monitoring ◽  
3D Printing ◽  
Health Monitoring ◽  
Structural Health ◽  
Displacement Sensors

scholarly journals Marker-free monitoring of the grandstand structures and modal identification using computer vision methods

2018 ◽  
Vol 18 (5-6) ◽  
pp. 1491-1509 ◽  
Author(s):  
Chuan-Zhi Dong ◽  
Ozan Celik ◽  
F Necati Catbas
Keyword(s):  
Structural Health Monitoring ◽  
Sensor Network ◽  
Health Monitoring ◽  
Single Point ◽  
Modal Identification ◽  
Dynamic Monitoring ◽  
Structural Dynamic ◽  
Multiple Camera ◽  
Structural Health ◽  
Displacement Sensors

In this study, a vision-based multi-point structural dynamic monitoring framework is proposed. This framework aims to solve issues in current vision-based structural health monitoring. Limitations are due to manual markers, single-point monitoring, and synchronization between a multiple-camera setup and a sensor network. The proposed method addresses the first issue using virtual markers—features extracted from an image—instead of physical manual markers. The virtual markers can be selected according to each scenario, which makes them versatile. The framework also overcomes the issue of single-point monitoring by utilizing an advanced visual tracking algorithm based on optical flow, allowing multi-point displacement measurements. Besides, a synchronization mechanism between a multiple-camera setup and a sensor network is built. The proposed method is first tested on a grandstand simulator located in the laboratory. The experiment is to verify the performance of displacement measurement of the proposed method and conduct structural identification of the grandstand through multi-point displacement records. The results from the proposed method are then compared to the data gathered by traditional displacement sensors and accelerometers. A second experiment is conducted at a stadium during a football game to validate the feasibility of field application and the operational modal identification of the stadium under human crowd jumping through the measured displacement records. From these experiments, it is concluded that the proposed method can be employed to identify modal parameters for structural health monitoring.

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