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Front. Built Environ. | doi: 10.3389/fbuil.2019.00016

Rapid and Automated Damage Detection in Buildings Through ARMAX Analysis of Wind Induced Vibrations

  • 1University of Alberta, Canada

After a seismic event, it is imperative that critical structural members that are damaged within a building are identified and analyzed as soon as possible to ensure proper remedial measures can be taken. Failure to detect damage or correctly analyze the severity of damage within the building could have catastrophic consequences. When a reinforced concrete building is subjected to a damaging event, the current standard method for identifying and analyzing structural damage involves extensive surface-level visual inspections which often result in inconclusive and inconsistent damage analysis. Structural Health Monitoring (SHM) is a rapidly developing field which is vastly improving the way damage is assessed within buildings and other major infrastructure. In this paper, an automated SHM Damage Detection Model (DDM) specifically tailored for buildings is developed that uses time series analysis along with sensor clustering techniques to detect damage in a building from its vibration response due to ambient wind loading. The specific time series analysis methodology used throughout this paper is an Auto-Regressive Moving Average model with eXogenous inputs (ARMAX). To validate the ARMAX DDM, a detailed wind simulation model that applies forces based on actual wind behaviour is created along with a numerical damage model applicable to reinforced concrete buildings. To evaluate the effectiveness of the proposed DDM in locating and quantifying damage at storey level precision, two buildings are modelled in SAP2000. The results from the numerical modelling proved the effectiveness of the ARMAX DDM at accurately locating and quantifying the degree damage from wind induced floor vibrations at a storey level precision. The limitations of the DDM in its current state and recommendations for future work are discussed to conclude the paper.

Keywords: ARMAX model, Wind induced vibration, damage detection, time series analysis, Shear type building

Received: 23 Aug 2018; Accepted: 05 Feb 2019.

Edited by:

Eleni N. Chatzi, ETH Zürich, Switzerland

Reviewed by:

Harsh Nandan, SC Solutions (United States), United States
Luis David Avendaño Valencia, ETH Zürich, Switzerland
Suparno Mukhopadhyay, Indian Institute of Technology Kanpur, India  

Copyright: © 2019 Gislason, Mei and Gul. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Mustafa Gul, University of Alberta, Edmonton, T6G 2R3, Alberta, Canada,