Modal Identification Framework for Bridges Using Traffic Smartphone Data

Regular monitoring and maintenance of bridge infrastructure requires sophisticated sensors, expensive equipment, high installation, and labor costs. Specialized equipment required to continuously monitor a large inventory of bridges can result in an alarmingly overspending budget. The concept of indirect bridge health monitoring (iBHM) has been explored by researchers worldwide for efficient monitoring of bridges. iBHM utilizes the traffic passing over the bridge as an actuator and a data-collecting device. The advancement of sensing and communication technologies over the years can be leveraged to enhance the idea of iBHM. The majority of passing vehicles traveling over a bridge is equipped with a smartphone that contains sophisticated sensors such as gyroscope, accelerometer, etc. This study is aimed at using smartphone sensors from passing vehicles to detect the bridge dynamic parameters. A smartphone application is developed in this study capable of gathering and analyzing vibration data through the passing vehicle. The analyzed data is readily available for the user in terms of bridge modal frequencies. The application is capable of simultaneously collecting and visually representing the data throughout the test duration. Furthermore, the smartphone application is linked to a server through the internet for further time–frequency analysis. The performance of this framework was tested using a comparison of direct and indirect data collected using the smartphone application. This study combined smartphone sensing technology with cloud computing to provide a robust monitoring framework for smart infrastructure.