In this paper, we use a scale model to experimentally validate an indirect approach to bridge structural health
monitoring (SHM). In contrast to a traditional direct monitoring approach with sensors placed on a bridge, the
indirect approach uses instrumented vehicles to collect data about the bridge. Indirect monitoring could offer
a mobile, sustainable, and economical complementary solution to the traditional direct bridge SHM approach.
Acceleration signals were collected from a vehicle and bridge system in a laboratory-scale experiment for
four different bridge scenarios and five speeds. These signals were classified using a simple short-time Fourier
transform technique meant to detect shifts in the fundamental frequency of the bridge due to changes in the
bridge condition. Results show near-perfect detection of changes when this technique is applied to signals collected
from the bridge (direct monitoring), and promising levels of detection when one uses signals from sensors
on the vehicle (indirect monitoring) instead of those recorded on the bridge itself.