Damage detection of a prototype building structure under shaking table testing using outlier analysis

Ji-Hyun Hwang; Bong-Chul Joo; Young-Jun Yoo; Ki-Tae Park; Chin-Hyung Lee

doi:10.1117/12.2013198

17 April 2013 Damage detection of a prototype building structure under shaking table testing using outlier analysis

Ji-Hyun Hwang, Bong-Chul Joo, Young-Jun Yoo, Ki-Tae Park, Chin-Hyung Lee

Proceedings Volume 8695, Health Monitoring of Structural and Biological Systems 2013; 86953H (2013) https://doi.org/10.1117/12.2013198
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2013, San Diego, California, United States

Abstract

The civil engineering community is becoming increasingly interested in monitoring structural behavior of civil infrastructure and in evaluation of the structural performance. The demand has largely been driven by deficiencies in structural performance due to the aging of the infrastructure, excessive loading, and natural disasters such as an earthquake, a landslide, a typhoon and a tsunami. 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.

Citation Download Citation

Ji-Hyun Hwang, Bong-Chul Joo, Young-Jun Yoo, Ki-Tae Park, and Chin-Hyung Lee "Damage detection of a prototype building structure under shaking table testing using outlier analysis", Proc. SPIE 8695, Health Monitoring of Structural and Biological Systems 2013, 86953H (17 April 2013); https://doi.org/10.1117/12.2013198

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available