Extraction of contact-point response in indirect bridge health monitoring using an input estimation approach

Identification of bridge dynamic properties from moving vehicle responses presents several practical benefits. However, a problem that arises when working with vehicle responses for indirect bridge health monitoring is that the bridge dynamics may get low-pass filtered by the vehicle suspension dynamics, rendering the identification of higher bridge modes difficult. Instead, the contact-point (CP) response-response at the contact point of the vehicle with the bridge surface-is a superior alternative to the vehicle response for identifying the bridge modal features. In the CP response, the vehicle dynamics is suppressed and the higher bridge modes are significantly enhanced, thus making it better suited for modal identification. Extracting the CP response from vehicle response is, however, not straightforward for a multiple degrees of freedom (MDoF) vehicle model. In this study, a novel methodology is proposed to extract CP acceleration from the measured vehicle acceleration using the knowledge of the MDoF vehicle dynamics. The CP acceleration is shown to act as a base-excited input to the test vehicle and is extracted via a joint input-state estimation procedure employing a Gaussian process latent force model (GPLFM). Numerical case studies are considered to assess the quality of the CP acceleration estimated with the proposed approach. It is found that the proposed method performs well and the extracted CP acceleration response is able to reduce the effect of vehicle dynamics and improve the prominence of higher bridge modes.