Nonlinear measurements for feature extraction in structural health monitoring

Document Type: Review Article

Authors

1 ENAP, Faculty of Engineering, Departments of Electromechanical and Biomedical Engineering. Autonomous University of Queretaro, Campus San Juan del Rio, Moctezuma 249, Col. San Cayetano, 76807, San Juan del Rio, Queretaro, Mexico

2 The Ohio State University, Columbus, OH 43210, U.S.A

10.24200/sci.2019.21669

Abstract

In the past twenty-five years, structural health monitoring (SHM) has become an increasingly significant topic of investigation in the civil and structural engineering research community. An SHM schema involves three main steps: (a) measurement and acquisition of signals related to the structural response, (b) signal processing consisting of pre-processing and feature extraction employing nonlinear measurements, and (c) interpretation using machine learning. This article presents a review of recent journal articles on nonlinear measurements used for feature extraction in SHM of building and bridge structures. It also reviews three recently-developed nonlinear indexes with potential applications in SHM.

Keywords