Affiliations: Department of Civil and Environmental Engineering,
University of Waterloo, Waterloo, ON, Canada
Note: [] Corresponding author: A. Sadhu, Department of Civil and
Environmental Engineering, University of Waterloo, Waterloo, ON N2L 3G1,
Canada. E-mail: ayansadhu.civil@gmail.com
Abstract: In this paper, a novel damage detection algorithm is developed based
on blind source separation in conjunction with time-series analysis. Blind
source separation (BSS), is a powerful signal processing tool that is used to
identify the modal responses and mode shapes of a vibrating structure using
only the knowledge of responses. In the proposed method, BSS is first employed
to estimate the modal response using the vibration measurements. Time-series
analysis is then performed to characterize the mono-component modal responses
and successively the resulting time-series models are utilized for one-step
ahead prediction of the modal response. With the occurrence of newer
measurements containing the signature of damaged system, a variance-based
damage index is used to identify the damage instant. Once the damage instant is
identified, the damaged and undamaged modal parameters of the system are
estimated in an adaptive fashion. The proposed method solves classical damage
detection issues including the identification of damage instant, location as
well as the severity of damage. The proposed damage detection algorithm is
verified using extensive numerical simulations followed by the full scale study
of UCLA Factor building using the measured responses under Parkfield
earthquake.
Keywords: Blind source separation, time series analysis, damage detection, ambient modal identification, damage index
