Smartphone-based bridge frequency identification using vehicle contact-point response

Bridge frequency (BF) identification using the vehicle scanning method has attracted considerable attention during the last two decades. However, most previous studies have adopted unrealistic vehicle models, thus finding limited practical applications. This study proposes a smartphone-based BF identification method that uses the contact-point acceleration response of a four degree-of-freedom vehicle model. The said response can be inferred from the vehicle body response measured by a smartphone. For realizing practical applications, this method is incorporated into a self-developed smartphone app to obtain data smoothly and identify BFs in a timely manner. Numerical and experimental investigations are performed to verify the effectiveness of the proposed method. In particular, the robustness of this method is investigated numerically against various factors, including the vehicle speed, bridge span, road roughness, and bridge type. Furthermore, laboratory calibration tests are performed to investigate the accuracy of the smartphone gyroscope in measuring the angular velocity, where anomalous data are detected and eliminated. Laboratory experiment results for a simply supported bridge indicate that the proposed method can be used to identify the first two BFs with acceptable accuracy.