ABSTRACT
Informed decisions on timely intervention for effective bridge maintenance activities rely on good quality, accurate and reliable asset condition data. The principal difficulty with adding several traditional monitoring systems is that they produce vast quantities of inconsistent data and are labor intensive. Gathering information requires structural health monitoring (SHM) and inspection and, for it to be useful, it must be accurate, inexpensive and easy to interpret, and must avoid interfering with traffic flows whether rail or highways. Digital image correlation (DIC) is a noncontact photogrammetry technique that can be used for monitoring by imaging a bridge component periodically and computing movement and deformation from images without traffic disruption. This paper describes the use of DIC for the monitoring of the Great Belt Bridge wind‐induced hanger vibrations and traffic-induced bridge deck displacements. Both deck and hanger movements were captured using the same DIC system, limiting costs of the equivalent monitoring system. The paper also presents how vision‐based monitoring helped to better understand the structural behavior of key suspension bridge components without any traffic disruption. To the authors knowledge, these are one of the first such long-term SHM campaigns carried out on a major suspension bridge.
