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Open AccessArticle

Extraction of Bridge Fundamental Frequencies Utilizing a Smartphone MEMS Accelerometer

1
Department of Civil, Construction, and Environmental Engineering, The University of Alabama at Birmingham, 1075 13th St S, Birmingham, AL 35205, USA
2
School of Civil Engineering, University College Dublin, Newstead Block B, Belfield, Dublin D04V1W8, Ireland
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(14), 3143; https://doi.org/10.3390/s19143143
Received: 25 June 2019 / Revised: 10 July 2019 / Accepted: 15 July 2019 / Published: 17 July 2019
(This article belongs to the Special Issue Bridge Damage Detection with Sensing Technology)
Smartphone MEMS (Micro Electrical Mechanical System) accelerometers have relatively low sensitivity and high output noise density. Therefore, it cannot be directly used to track feeble vibrations such as structural vibrations. This article proposes an effective increase in the sensitivity of the smartphone accelerometer utilizing the stochastic resonance (SR) phenomenon. SR is an approach where, counter-intuitively, feeble signals are amplified rather than overwhelmed by the addition of noise. This study introduces the 2D-frequency independent underdamped pinning stochastic resonance (2D-FI-UPSR) technique, which is a customized SR filter that enables identifying the frequencies of weak signals. To validate the feasibility of the proposed SR filter, an iPhone device is used to collect bridge acceleration data during normal traffic operation and the proposed 2D-FI-UPSR filter is used to process these data. The first four fundamental bridge frequencies are successfully identified from the iPhone data. In parallel to the iPhone, a highly sensitive wireless sensing network consists of 15 accelerometers (Silicon Designs accelerometers SDI-2012) is installed to validate the accuracy of the extracted frequencies. The measurement fidelity of the iPhone device is shown to be consistent with the wireless sensing network data with approximately 1% error in the first three bridge frequencies and 3% error in the fourth frequency. View Full-Text
Keywords: stochastic resonance; bridge inspection; structural health monitoring, SHM; bridge health monitoring; frequency independent stochastic resonance; SHM using smartphones stochastic resonance; bridge inspection; structural health monitoring, SHM; bridge health monitoring; frequency independent stochastic resonance; SHM using smartphones
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Elhattab, A.; Uddin, N.; OBrien, E. Extraction of Bridge Fundamental Frequencies Utilizing a Smartphone MEMS Accelerometer. Sensors 2019, 19, 3143.

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