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Smart Structures and Systems
  Volume 14, Number 4, October 2014 , pages 679-697
DOI: https://doi.org/10.12989/sss.2014.14.14.679
 


Multiscale features and information extraction of online strain for long-span bridges
Baijian Wu, Zhaoxia Li, Tommy H.T. Chan and Ying Wang

 
Abstract
    The strain data acquired from structural health monitoring (SHM) systems play an important role in the state monitoring and damage identification of bridges. Due to the environmental complexity of civil structures, a better understanding of the actual strain data will help filling the gap between theoretical/laboratorial results and practical application. In the study, the multi-scale features of strain response are first revealed after abundant investigations on the actual data from two typical long-span bridges. Results show that, strain types at the three typical temporal scales of 105, 102 and 100 sec are caused by temperature change, trains and heavy trucks, and have their respective cut-off frequency in the order of 10-2, 10-1 and 100 Hz. Multi-resolution analysis and wavelet shrinkage are applied for separating and extracting these strain types. During the above process, two methods for determining thresholds are introduced. The excellent ability of wavelet transform on simultaneously time-frequency analysis leads to an effective information extraction. After extraction, the strain data will be compressed at an attractive ratio. This research may contribute to a further understanding of actual strain data of long-span bridges; also, the proposed extracting methodology is applicable on actual SHM systems.
 
Key Words
    health monitoring; bridges; strain; information extraction; multi-scale; wavelet
 
Address
Baijian Wu, Zhaoxia Li and Ying Wang: Department of Engineering Mechanics, Southeast University, Nanjing 210096, China
Tommy H.T. Chan: School of Civil Engineering and Built Environment, Science and Engineering Faculty,
Queensland University of Technology, Queensland, Australia
 

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