광섬유 FBG 센서를 이용한 국부손상탐색에 관한 실험 연구

Abstract

In this study, the fiber Bragg grating (FBG)-sensor based local damage detection method is proposed under circumstances with temperature and external loading variations. To compensate the environmental effects, principal component analysis (PCA) is utilized and also the performance of PCA is compared with that of the conventional linear adaptive filter (LF) model. Laboratory tests with a 1/20 scale model of a jacket-type offshore structure with six jacket-legs and a heavy super structure have been carried out for investigating the performance of the proposed damage detection method. From the experimental tests, it is observed that the local damage feature is mostly hidden and difficult to identify due to the environmental effects. By utilizing the conventional LF and PCA models, the effects of the undesirable environmental effects can be efficiently eliminated, and it is also found that the performances of the LF and PCA models are very similar and competitive to each other. However PCA model does not require the information on the temperature and external load variations, hence it can be concluded that the PCA-based local damage detection can be more efficiently applied for FBG-based local damage detection under temperature and external loading variations.(PCA) is utilized and also the performance of PCA is compared with that of the conventional linear adaptive filter (LF) model. Laboratory tests with a 1/20 scale model of a jacket-type offshore structure with six jacket-legs and a heavy super structure have been carried out for investigating the performance of the proposed damage detection method. From the experimental tests, it is observed that the local damage feature is mostly hidden and difficult to identify due to the environmental effects. By utilizing the conventional LF and PCA models, the effects of the undesirable environmental effects can be efficiently eliminated, and it is also found that the performances of the LF and PCA models are very similar and competitive to each other. However PCA model does not require the information on the temperature and external load variations, hence it can be concluded that the PCA-based local damage detection can be more efficiently applied for FBG-based local damage detection under temperature and external loading variations.