In this study, a structural health monitoring methodology using acceleration responses is proposed for damage detection of a three-story prototype building structure during shaking table testing. A damage index is developed using the acceleration data and applied to outlier analysis, one of unsupervised learning based pattern recognition methods. A threshold value for the outlier analysis is determined based on confidence level of the probabilistic distribution of the acceleration data. The probabilistic distribution is selected according to the feature of the collected data.

• 이진형(한국건설기술연구원 연구원, 공학박사) | Lee, Chin-Hyung
• 유영준(한국건설기술연구원 수석연구원, 공학석사) | You, Young-Jun
• 박기태(한국건설기술연구원 연구위원, 공학박사) | Park, Ki-Tae
• 주봉철(한국건설기술연구원 수석연구원, 공학석사) | Joo, Bong-Chul
• 김태헌(한국건설기술연구원 연구원, 공학석사) | Kim, Tae-Heon