Tracking the normal modes of an overpass highway bridge using Distributed Acoustic Sensing

TL;DR

This study demonstrates that Distributed Acoustic Sensing (DAS) can effectively identify the normal modes of a highway bridge using ambient vibrations, revealing detailed modal shapes and seasonal effects with high spatial resolution.

Contribution

The paper introduces the novel application of DAS for modal identification of a bridge, achieving unprecedented spatial resolution and observing seasonal variations in modal properties.

Findings

Successful identification of bridge's normal modes using DAS data.

High spatial resolution reveals detailed modal shapes.

Seasonal effects influence modal frequencies and shapes.

Abstract

Distributed Acoustic Sensing (DAS) of ambient vibrations is a promising technique in the context of structural health monitoring of civil engineering structures. The methodology uses Rayleigh backscattered light from small deformations at different locations of the sensed fiber-optic cable, turning it into a large array of equally distributed strain sensors. In this paper, we demonstrate the feasibility of using DAS technology to record dynamic strain used for modal identification through the Operational Modal Analysis (OMA) of a strut-frame bridge overpassing the A8 highway in southeastern France. Modal identification using DAS data is successful despite its predominantly axial sensitivity (along fiber), though the help of three-component seismometers is useful for discriminating the main motion direction of each identified mode. The identification of 1 bridge's normal modes with unprecedented spatial resolution is obtained from the lowest (transverse and longitudinal) modes to high-order modes that present significant vertical motion. In addition, strong seasonal effects are observed in both the absolute frequency values and the modal shapes of the first transverse and longitudinal modes of the bridge, comparing ambient vibration testing and DAS surveys carried out in the summer and winter periods.