Predicting Thermal Response for Structural Health Monitoring using Blind Source Separation Method
Abstract »Research in Structural Health Monitoring (SHM) has been rapidly expanding over the last decades. However, data interpretation is still a big challenge for damage detection in SHM applications for civil infrastructure, especially due to the presence of environmental variations. This is the motivation for developing a methodology to separate the prediction of thermal responses from other sources of a structural response. This paper presents a Blind Source Separation (BSS) method for predicting structural thermal responses without any prior knowledge of the structure in-service circumstances. This BSS-based method involves combination and optimization of Ensemble Empirical Mode Decomposition (EEMD), Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Numerical simulation of a truss bridge, inspired from New Joban Line Arakawa Railway Bridge, is used to validate applicability of the method. Results demonstrate that the method can predict temperature effects from the mixed structural responses recorded by a single sensor with sufficient accuracy.
Biography: Yanjie ZHU was born in 1994 and graduated from School of Transportation at Southeast
University (SEU), Nanjing, China, with BEng Degree in Highway & Bridge
Engineering. In October 2014, she started her PhD study under
Dr. Irwanda Laory’s supervision in School of Engineering at University of
Warwick. Her research area is Structural Health Monitoring (SHM), focusing on damage detection of civil infrastructure.
Affiliation: The University of Warwick School of Engineering CV4 7AL Coventry United Kingdom