Bridge monitoring utilizing handheld devices

Natural Frequencies of structures is an elegant intrinsic property that is essential for many Civil Structural applications, as Structural Health Monitoring and Simulation Modeling. The physically tangible relation between the frequency of the structures and its dynamic characteristics was the impetus for using different time/frequency based methods to quantify this fundamental property. Unfortunately, the disruption effect of noise requires incorporating advanced sensors, that provide signals with a low noise-intensity, to accurately identify the fundamental frequencies of the structure. This article solves this bottleneck via exploiting the Stochastic Resonance (SR) phenomena to extract the fundamental frequencies of a bridge using an acceleration recorded by a conventional portable sensor as the sensor implemented in small portable accelerometer. The portable accelerometer device has an M9 motion coprocessor designed mainly for tracking human activities. Human activities have an exaggerated amplitude when it is compared to the structural responses. Therefore, if an iPhone device is used to record the response of the structure (for example a bridge) the structure response will be swamped by severe surrounding noise because of its small amplitude. Therefore, in this vein, the SR phenomena has been employed to use rather than suppress the noise to magnify the feeble bridge response in the recorded acceleration and hence identify the corresponding frequency. The fidelity of the proposed approach has been verified using the data of a field experiment. The bridge frequencies are identified first using conventional vibration analysis, thereafter, the portable accelerometer has been attached to the bridge rail to record the bridge vibration under the passing traffic. The recorded data has been processed using a new Developed Underdamped Pinning Stochastic Resonance (DUPSR) technique to quantify the bridge frequency.