임피던스를 이용한 조류발전 구조물의 장기 구조물 건전성 모니터링

Abstract

Offshore structures are always exposed to severe environmental conditions such as salt, high speed of current, wave, and wind compared with other onshore structures. In spite of the importance of maintaining the structural integrity for offshore structures, only few cases have been reported to apply structural health monitoring (SHM) system in practice. The impedance-based SHM is a kind of local SHM techniques and to date, numerous techniques and algorithms have been proposed for local SHM of real-scale structures. However, it still requires a significant challenge for practical applications to extract only damage features from impedance signals by compensating unknown environmental effects and reducing signal noises. In this study, the impedance-based SHM was carried out on a 1/20-scaled model of an Uldolmok current power plant structure under changes in temperature and transverse loadings. Through conventional principal component analysis (PCA), principal components sensitive to environmental changes and noises were eliminated from the original signals and the efficiency of damage characterization was finally improved. A series of experiments showed that the proposed PCA-base approach is an effective tool especially for long-term SHM under significant environmental changes.shore structures, only few cases have been reported to apply structural health monitoring (SHM) system in practice. The impedance-based SHM is a kind of local SHM techniques and to date, numerous techniques and algorithms have been proposed for local SHM of real-scale structures. However, it still requires a significant challenge for practical applications to extract only damage features from impedance signals by compensating unknown environmental effects and reducing signal noises. In this study, the impedance-based SHM was carried out on a 1/20-scaled model of an Uldolmok current power plant structure under changes in temperature and transverse loadings. Through conventional principal component analysis (PCA), principal components sensitive to environmental changes and noises were eliminated from the original signals and the efficiency of damage characterization was finally improved. A series of experiments showed that the proposed PCA-base approach is an effective tool especially for long-term SHM under significant environmental changes.