Limited sensor-based bridge condition assessment using vehicle-induced nonstationary measurements

Abstract

Retrofitting and maintenance of bridges using vehicle-induced measurements have attracted increasing attention in the field of vibration-based bridge health monitoring. In this paper, a novel condition assessment method is proposed that uses a fewer number of sensors for monitoring bridges when subjected to moving vehicles. As a vehicle travels over a bridge, the bridge responses are measured at different locations, and the traffic-induced vibrations are analyzed to identify modal parameters of the bridge using a limited number of sensors. This study investigates a viable solution to various practical challenges associated with bridge inspection using vehicle-induced measurements, such as sensor location, vehicle speeds and vehicle parameters, and severity of the damage. Unlike ambient vibration measurements, moving vehicle-induced bridge vibration is nonstationary in nature. In this paper, a novel hybrid method is proposed by integrating Time-Varying Filtering-based Empirical Mode Decomposition (TVF-EMD) with Synchro-extracting Transform (SET) to track the nonstationary modal parameters of the bridge. The proposed approach is validated using numerical and full-scale studies comprising of a steel bridge subjected to passing vehicles.