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Smart Structures and Systems   Volume 14, Number 5, November 2014, pages 917-942
An integrated approach for structural health monitoring using an in-house built fiber optic system and non-parametric data analysis
Masoud Malekzadeh, Mustafa Gul, Il-Bum Kwon and Necati Catbas

Abstract     [Buy Article]
    Multivariate statistics based damage detection algorithms employed in conjunction with novel sensing technologies are attracting more attention for long term Structural Health Monitoring of civil infrastructure. In this study, two practical data driven methods are investigated utilizing strain data captured from a 4-span bridge model by Fiber Bragg Grating (FBG) sensors as part of a bridge health monitoring study. The most common and critical bridge damage scenarios were simulated on the representative bridge model equipped with FBG sensors. A high speed FBG interrogator system is developed by the authors to collect the strain responses under moving vehicle loads using FBG sensors. Two data driven methods, Moving Principal Component Analysis (MPCA) and Moving Cross Correlation Analysis (MCCA), are coded and implemented to handle and process the large amount of data. The efficiency of the SHM system with FBG sensors, MPCA and MCCA methods for detecting and localizing damage is explored with several experiments. Based on the findings presented in this paper, the MPCA and MCCA coupled with FBG sensors can be deemed to deliver promising results to detect both local and global damage implemented on the bridge structure.
Key Words
    structural health monitoring; fiber optic sensor; non-parametric damage detection algorithm; principal component analysis; cross correlation analysis
Masoud Malekzadeh and Necati Catbas: Department of Civil, Environmental, and Construction Engineering, University of Central Florida, 4000 Central Florida Blvd, Orlando, Florida, United States
Mustafa Gul: Department of Civil and Environmental Engineering, University of Alberta, 9105 116th St, Edmonton, Alberta, Canada
Il-Bum Kwon : Center for Safety Measurements, Korea Research Institute of Standards and Science, 1 Doryonga-dong, Yuseong-gu, Daejeon, 305-340, South Korea

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