Smartphone app data could help keep bridges from collapsing, study reveals

CAMBRIDGE, Mass. — Data collected by mobile phones could help to assess the structural integrity of bridges, making sure they don’t collapse.

Using the Golden Gate Bridge in San Francisco as an example, researchers from MIT demonstrated that phones are capable of capturing the same kind of information about bridge vibrations which stationary sensors do today. The engineers estimate that, depending on the age of a road bridge, mobile monitoring could increase a bridge’s lifespan by 15 to 30 percent.

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

Engineers typically study the natural vibrations of a bridge by placing sensors, such as accelerometers, on it to measure changes in modal frequencies — or how the rhythm of the vibrations changes over time. These changes may indicate a decay in the bridge’s structural integrity.

Publishing their work in the journal Nature Communications Engineeringthe team at MIT developed an Android-based app that collects data while traveling across a bridge which they compared with traditional bridge-based sensors.

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

How accurate can smartphones be?

In the case of the Golden Gate Bridge, the researchers drove over it 102 times with their devices running and used 72 trips by Uber drivers with activated phones as well. They then compared the resulting data to what 240 sensors detected on the Golden Gate Bridge for three months.

Results showed that data from the phones converged with the information from the bridge sensors. For 10 particular types of low-frequency vibrations the engineers measured, there was a close match. In five cases, there was no discrepancy between the methods at all.

“We were able to show that many of these frequencies correspond very accurately to the prominent modal frequencies of the bridge,” Santi says.

However, because most bridges are not suspension bridges like the famous San Francisco landmark, the researchers decided to test their method on smaller and more common concrete spans. To do so, they studied a bridge in Ciampino, Italy, comparing 280 vehicle trips over the bridge to six sensors placed on the bridge for seven months.

Here, the researchers found up to a 2.3-percent divergence between the methods for certain modal frequencies over all 280 trips, and a 5.5-percent divergence over a smaller sample. These findings suggest a larger volume of trips could produce more useful data.

“Our initial results suggest that only a [modest amount] of trips over the span of a few weeks are sufficient to obtain useful information about bridge modal frequencies,” Santi continues.

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,” adds Professor Markus Buehler.

Teacher. Ratti says there are ways to refine and expand the research, for example by accounting for the effects of the smartphone mount in the vehicle and the influence of the vehicle type on the data.

“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,” Ratti concludes. “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.”

South West News Service writer Danny Halpin contributed to this report.

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