Hybrid structure health monitoring technique for enhancing modal parameter identification accuracy

Abstract

SHM relies on the possibility of estimating structural modal parameters, such as mode shapes, natural frequencies, and damping, from the structure’s measured data. Nevertheless, modal parameter estimation still faces accuracy problems. The identification of bridge and/or vehicle system parameters and vibration characteristics have been studied both numerically and experimentally. The knowledge of bridge vibration characteristics and vehicle system parameters is crucial to the maintenance of bridges. The issue is that the techniques used to identify bridge and vehicle system parameters usually work very well with numerical simulation but present accuracy issues with experimental data due to environmental noise. Traditionally, measured data were obtained by instrumenting bridges with connected sensor systems, which had issues such as high cost, maintenance problems, safety concerns, and traffic disruption. More recently, indirect SHM (iSHM) methods, such as drive-by using passing instrumented vehicles, have been researched[1,2]. However, these methods still struggle with the accuracy of modal parameter identification, particularly for higher vibration modes sensitive to localized bridge damage, limiting the widespread adoption of iSHM methodologies[1,3]. A combination of indirect and direct monitoring methods is proposed to address these limitations. This approach aims to improve modal parameter identification, including higher vibration modes, for localized damage detection and structural assessment. The proposed method uses GPS-time synchronized sensors for simultaneous measurement of vehicle and bridge vibration data and is verified through numerical simulation assuming multiple runs over the same bridge. The study highlights the potential of this hybrid SHM technique to significantly improve the accuracy of indirect structural health monitoring, providing more reliable and precise modal parameter estimates, especially for higher vibration modes, allowing for the identification of localized bridge damage.

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