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.
Highlights
Blind Source Separation (BSS) methods have recently emerged as a powerful class of signal processing methods capable of monitoring the health of a large class of civil structures
A linear damage situation is defined as the case when a initially linear-elastic structure remains linear-elastic after damage. Such elastic changes in modal properties primarily occur due to changes in the geometry and/or the material properties of the structure, the structural response can still be modeled using a linear equation of motion [9]. This is the basis of the proposed method where the second-order blind identification (SOBI)-based BSS is used for the modal identification, and the estimated sources in conjunction with the time-series analysis are used for the prediction of future measurements to identify the damage
Blind source separation-based damage detection method in conjuction with time-series analysis is proposed for civil structures
Summary
Blind Source Separation (BSS) methods have recently emerged as a powerful class of signal processing methods capable of monitoring the health of a large class of civil structures. Modal properties primarily occur due to changes in the geometry and/or the material properties of the structure, the structural response can still be modeled using a linear equation of motion [9] This is the basis of the proposed method where the SOBI-based BSS is used for the modal identification, and the estimated sources in conjunction with the time-series analysis are used for the prediction of future measurements to identify the damage. The identification results of the UCLA building are presented, followed by the main conclusions of this study
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
