The Internet of Everything Makes Smart Bridges Even Smarter
Using IoE technology, researchers experiment with ways to monitor, detect and repair bridge defects.
April 30 , 2014
The two-mile six-lane Charilaos Trikoupis Bridge in Greece links the town of Rio on the Peloponnese peninsula to the mainland, spanning the Gulf of Corinth. Its 300 or so sensors monitor its condition, alerting operators when, say, high winds call for shutting the bridge to traffic. Soon after going live about ten years ago, for example, the technology detected unusual vibrations in the bridge's cables and, in response, engineers added more weights.
Such "smart bridges" using sensors to monitor for such potentially hazardous problems as cracks or weak joints are sprinkled throughout the world. But now it looks like they're going to get a lot more capable. Using Internet of Everything (IoE) technology, researchers at a variety of universities are engaged in projects aimed at everything from boosting the monitoring, detection and repair capabilities of bridges to finding methods for powering the technology more efficiently and sustainably. Here's a look at three such research projects, all funded by the National Institute of Standards and Technology in the U.S.#77: Smart Bridges Get Smarter by The Network Podcast
Making Data More Useful
One problem with many smart bridge systems to date has been the sheer amount of raw data they collect. "It requires very skilled engineers to process all of this information," says Jerome Lynch, professor of civil and environmental engineering at the University of Michigan. His team led a five-year research project to create a way to convert massive amounts of raw data transmitted wirelessly from sensors into a form that can more easily be analyzed and used for effective decision-making about bridge repair.
Part of that research involved creating what Lynch calls a "framework" for giving more context to data collected and transmitted by sensors. That involved collecting related meta data, including everything from a bridge's name to the year it was built, history of repairs and the location of the beams.
Then the team built a set of analysis tools to use in making sense of the data. One example: Sensors on bridges communicated data wirelessly to three bay stations, which aggregated the information and passed it on to a server via a cell phone connection, to be stored in a data base. Most important, the server was able to store different types of data in different ways. Meta data was stored in a relational data base, while historical data was housed in another system. Then various algorithms looked for specific categories of information—say, signs of structural damage—and processed the data in an easy to assess form so engineers could determine whether action needed to be taken immediately.
The process doesn't eliminate the need for visual inspections which, by law, must be done every six months to two years, depending on the bridge, but "By combining the qualitative and quantitative data, you can be more accurate in assessing the real health of the structure," says Lynch.
Overall vs. Localized Assessment
Wireless systems using sensors placed on certain areas of a bridge generally provide information about only those specific, girders or arches. Part of Nenad Gucunski's research over the past five years has focused, in part, on creating a more global structural assessment system that evaluates how a bridge as a whole reacts to traffic. "We're looking at the overall structural vulnerability of the bridge," says Gucunski, professor of civil and environmental engineering at Rutgers, the State University of New Jersey.
He did that by dropping 30,000 to 40,000 pound weights, the impact of which, of course, would create vibrations on the bridge. Then a series of sensors placed on the structure measured the frequency of movement and how the bridge reacted during those oscillations, sending that information wirelessly to computers, where engineers, ultimately, determined the acceptable level of impact.
Gucunski studied localized systems, aimed at making targeted repairs, as well. That included two components. Usually, bridge detection systems use accelerometers, which measure motion and acceleration. But Gucunski instead employed an air-coupled ultrasonic system--basically microphones--which picked up sound waves much faster. Then if a defect were detected, a GPS-controlled robotic arm could drill into the crack and inject a glue-like material to seal it up. "The result is much faster repair and less traffic interruption," he says.
Speeding Up Processing
Sharon Woods, a professor of engineering at the University of Texas at Austin's Cockrell School of Engineering, recently led a team trying to speed up processing of sensor data and, as a result, preserve the life of batteries powering the equipment.
Central to the effort was new hardware developed by National Instruments, according to Woods. The system included a wireless network with multiple nodes containing sensors, which was able to scan, process and synthesize data about potential damage caused by too much use –or strain, as it's called--and then send that data to be collected by a gateway computer. Without that hardware, raw data would have been streamed straight to the gateway for processing. "That really drains the battery because wireless communications require a lot of power," says Woods. "So we were able to cut down on wireless communication and preserve battery life."
The research focused on a steel bridge—Woods won't reveal which one--where a crack from over-use had developed, potentially causing a collapse. Over three years, she monitored the bridge before, during and after the defect was repaired. "We extended the life of the bridge," she says.
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