STRUCTURAL FAULT DETECTION OF BRIDGES BASED ON LINEAR SYSTEM PARAMETER AND MTS METHOD

Abstract

This study investigated the feasibility of bridge health monitoring (BHM) using a linear system parameter of a time series model identified from traffic-induced vibration data of bridges, which data were obtained through a moving-vehicle experiment on scaled model bridges. In order to detect possible anomalies in bridges, this study adopted a parameter from autoregressive (AR) coefficients. Consideration was given to diagnosis of the bridge condition from pattern changes of identified system parameters due to damage. The Mahalanobis-Taguchi system (MTS) was successfully applied to make decisions on the bridge health condition. Observations demonstrate the feasibility of structural diagnoses of bridges from the identified system parameter.