ABSTRACT
Data fusion of different types of measurements has shown a strong potential to improve the SHM performance (Chatzi & Smyth 2009; Kim et al. 2011; Park et al. 2013; Park et al. 2014). Contrary to most damage identification methods that have used a single measurement, combining multiple measurement can extract hidden damage information. Law et al. (2005) used acceleration and strain measurements in their wavelet-based damage detection, which was further developed and implemented on a decentralized wireless smart sensor network by Kijewski-Correa et al. (2006). Sim et al. (2011) proposed a flexibility-based damage detection using acceleration and strain responses. While these previous research outcomes have proved the enhanced performance in damage detection, the algorithms based on the modal properties have not been verified with the environmental change.
