- A new study suggests mobile data collected while traveling over bridges could help evaluate their integrity.
- The researchers developed an Android-based mobile phone application to collect accelerometer data when the devices were placed in vehicles passing over the bridge.
- The application was tested on the Golden Gate Bridge and a bridge in Ciampino, Italy.
Next time you drive over the Golden Gate Bridge, you could help collect data on its structural integrity.
Bridges naturally vibrate, and to study the essential “modal frequencies” of those vibrations in many directions, engineers typically place sensors, such as accelerometers, on bridges themselves. Changes in the modal frequencies over time may indicate changes in a bridge’s structural integrity.
But, MIT researchers developed an Android-based mobile phone application to collect accelerometer data when the devices were placed in vehicles passing over the bridge. They could then see how well those data matched up with data record by sensors on bridges themselves, to see if the mobile-phone method worked.
In the case of the Golden Gate Bridge, the researchers drove over the bridge 102 times with their devices running, and the team used 72 trips by Uber drivers with activated phones as well. The team then compared the resulting data to that from a group of 240 sensors that had been placed on the Golden Gate Bridge for three months.
The outcome was that the data from the phones converged with that from the bridge’s sensors—for 10 particular types of low-frequency vibrations engineers measure on the bridge, there was a close match, and in five cases, there was no discrepancy between the methods at all.
However, only 1 percent of all bridges in the US are suspension bridges. About 41 percent are much smaller concrete span bridges. So, the researchers also examined how well their method would fare in that setting.
To do so, they studied a bridge in Ciampino, Italy, comparing 280 vehicle trips over the bridge to six sensors that had been placed on the bridge for seven months. Here, the researchers were also found encouraged by the findings, though they up to a 2.3% divergence between methods for certain modal frequencies, and a 5.5% divergence over a smaller sample. That suggests a larger volume of trips could yield more useful 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,” said Carlo Ratti, director of the MIT Sensable City Laboratory. “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.”
Information provided by MIT.