Bridge damage detection using reconstructed mode shape by improved vehicle scanning method

In this study, the improved vehicle scanning method (VSM) is adopted for structural health monitoring to identify healthy and damaged states of bridges. The improved VSM uses a designed elliptic filter (instead of the conventional Butterworth filter) to obtain the narrowband signals from the contact point response. These highquality narrowband signals are able to furnish accurate vibration modes that reveal kinks that indicate the damage locations in the bridges. This improved VSM works best with a series of vehicles that are modeled as moving sprung masses passing over the bridge. The exciting vehicles modeled by heavier masses excite the bridge, and they are followed by a testing vehicle modeled by lighter masses to capture the acceleration response at the contact point. Some example problems involving bridges with different damage locations and severities were studied. It is shown herein that the improved VSM extracted mode shapes have very visible kinks to mark the damage positions of the bridges when compared to mode shapes extracted from existing VSMs. So, the improved VSM is able to directly pinpoint the damage locations from the extracted mode shapes with minimal postprocessing effort, whereas existing VSMs generally require additional effort, e.g., constructed damage indices, for damage identification. To better identify the damage locations, a few higher modes should be used so as to avoid missing the damage locations at nodes of a particular vibration mode.

Automated summary

This study adopts the improved vehicle scanning method (VSM) to monitor the structural health of bridges and identify their healthy and damaged states. The improved VSM uses an elliptic filter to obtain high-quality narrowband signals, which accurately reveal the vibration modes and damage locations in the bridges. It is shown that this improved VSM outperforms existing methods by directly pinpointing the damage locations with minimal postprocessing effort.