Want to know if the Golden Gate Bridge is holding up? There might be an app for that.
A new study involving MIT researchers shows that cell phones placed in vehicles, equipped with special software, can collect useful data on structural integrity when crossing bridges. In doing so, they could become a cheaper alternative to sets of sensors attached to the bridges themselves.
“The main finding is that information about the structural health of bridges can be extracted from accelerometer data collected by smartphone,” says Carlo Ratti, director of MIT Sensable City Laboratory and co-author of a new paper summarizing the results of the study.
The research was conducted, in part, on the Golden Gate Bridge itself. The study showed that mobile devices can capture the same type of bridge vibration information that stationary sensors compile. The researchers also estimate that, depending on the age of a highway bridge, mobile device monitoring could add an additional 15 to 30 percent years to the life of the structure.
“These results suggest that massive, low-cost datasets collected by smartphones could play an important role in monitoring the health of existing transportation infrastructure,” the authors write in their new paper.
The study, “Crowdsourcing Bridge Vital Signs with Smartphone Vehicle Trips,” is published in Communications Engineering.
The authors are Thomas J. Matarazzo, assistant professor of civil and mechanical engineering at the United States Military Academy at West Point; Daniel Kondor, postdoctoral fellow at the Complexity Science Hub in Vienna; Sebastiano Milardo, researcher at Senseable City Lab; Soheil S. Eshkevari, principal investigator at DiDi Labs and former member of Senseable City Lab; Paolo Santi, Senior Researcher at Senseable City Lab and Research Director at the Italian National Research Council; Shamim N. Pakzad, professor and chair of the Department of Civil and Environmental Engineering at Lehigh University; Markus J. Buehler, Jerry McAfee Professor of Engineering and Professor of Civil and Environmental Engineering and Mechanical Engineering at MIT; and Ratti, who is also a professor of practice in MIT’s Department of Urban Studies and Planning.
Bridges naturally vibrate, and to study the essential “modal frequencies” of these vibrations in many directions, engineers typically place sensors, such as accelerometers, on the bridges themselves. Changes in modal frequencies over time can indicate changes in the structural integrity of a bridge.
To conduct the study, the 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 that data matched the data recorded by the sensors on the bridges themselves, to see if the cellphone method worked.
“In our work, we devised a methodology to extract modal vibration frequencies from noisy data collected from smartphones,” Santi explains. “While data from multiple journeys on a bridge is recorded, noise generated by engine, suspension and traffic vibrations, [and] the asphalt, tend to cancel each other out, while the underlying dominant frequencies emerge.
In the case of the Golden Gate Bridge, the researchers crossed the bridge 102 times with their devices turned on, and the team also used 72 Uber driver rides with activated phones. The team then compared the resulting data to that of a group of 240 sensors that had been placed on the Golden Gate Bridge for three months.
The result was that the data from the phones converged with that from the sensors on the bridge; for 10 particular types of low-frequency vibration measured by engineers on the bridge, there was a close match, and in five cases there was no difference between the methods.
“We were able to show that many of these frequencies correspond very precisely to the prominent modal frequencies of the bridge,” says Santi.
However, only 1% of all bridges in the United States are suspension bridges. About 41 percent are much smaller concrete span bridges. So the researchers also considered how well their method would work in this context.
To do this, they studied a bridge in Ciampino, Italy, comparing 280 vehicle trips across the bridge to six sensors placed on the bridge for seven months. Here the researchers were also encouraged by the results, although they found up to 2.3% discrepancy between the methods for some modal frequencies across the 280 trips, and a 5.5% discrepancy in one sample. smaller. This suggests that a greater volume of travel could produce more useful data.
“Our initial results suggest that only one [modest amount] trips over a period of a few weeks are enough to get useful information about the modal frequencies of bridges,” says Santi.
Looking at the method as a whole, Buehler observes, “Vibrational signatures emerge as a powerful tool for assessing properties of large and complex systems, ranging from the viral properties of pathogens to the structural integrity of bridges, as shown in this study. . It is a universal signal widespread in the natural and built environment that we are only just beginning to explore as a diagnostic and generation tool in engineering.
As Ratti acknowledges, there are ways to refine and expand the search, including considering the effects of in-vehicle smartphone support, the influence of vehicle type on data, and more.
“We still have work to do, but we think our approach could be easily scaled up – down to the level of an entire country,” says Ratti. “It may not achieve the accuracy that can be achieved 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 other analyses.
The researchers received support from Anas SpA, Allianz, Brose, Cisco, Dover Corporation, Ford, the Amsterdam Institute for Advanced Metropolitan Solutions, the Fraunhofer Institute, the former Kuwait-MIT Center for Natural Resources and the Environment, Lab Campus, RATP, Singapore – MIT Alliance for Research and Technology (SMART), SNCF Gares & Connections, UBER and the US Department of Defense High Performance Computing Modernization Program.