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Mobile phones could detect if bridges are in good shape

A new study led by the Massachusetts Institute of Technology (MIT) has found that mobile phones placed in vehicles and equipped with special software could collect useful structural integrity data while crossing bridges. Thus, they could become a less expensive alternative to sets of sensors attached to bridges themselves.

“The core finding is that information about structural health of bridges can be extracted from smartphone-collected accelerometer data,” said study co-author Carlo Ratti, the director of the MIT Sensable City Laboratory.

The research was conducted at the Golden Gate Bridge in San Francisco, as well as at a smaller bridge in Ciampino, Italy. The scientists developed an Android-based smartphone application to collect accelerometer data when the devices were placed in vehicles passing over the bridge.

“In our work, we designed a methodology for extracting modal vibration frequencies from noisy data collected from smartphones. As data from multiple trips over a bridge are recorded, noise generated by engine, suspension and traffic vibrations, [and] asphalt, tend to cancel out, while the underlying dominant frequencies emerge,” explained study co-author Paolo Santi, a principal research scientist at the Sensable Lab.

In the case of the Golden Gate Bridge, the researchers drove over the bridge 102 times with their devices running, while also collecting data from 72 Uber drivers with activated phones. By comparing the data with that from a group of 240 sensors that had been placed on the bridge for three months, they found that the data from the phones largely converged with that from the sensors. Although the information collected on the smaller bridge in Italy appeared to be slightly more divergent with that from sensors placed on the bridge, the results nonetheless showed that only a modest number of trips over the span of a few weeks could be sufficient to obtain useful data about bridge modal frequencies.

“Vibrational signatures are emerging as a powerful tool to assess properties of large and complex systems, ranging from viral properties of pathogens to structural integrity of bridges as shown in this study. It’s a universal signal found widely in the natural and built environment that we’re just now beginning to explore as a diagnostic and generative tool in engineering,” said study co-author Markus Buehler, a professor of Civil and Environmental Engineering at MIT.

“We still have work to do, but we believe that our approach could be scaled up easily – all the way to the level of an entire country. It might not reach the accuracy that one can get using fixed sensors installed on a bridge, but it could become a very interesting early-warning system. Small anomalies could then suggest when to carry out further analyses,” concluded senior author Carlo Ratti, another professor of Civil and Environmental Engineering at MIT.

The study is published in the journal Nature Communications Engineering.

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By Andrei Ionescu, Staff Writer

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