According to a recent report from the White House Administration, one in four bridges in the United States is in dire need of significant repair or cannot handle automobile traffic. Typically, when bridges are inspected for defects, such as cracks, engineers must use hanging scaffold systems or view them from elevated platforms. It’s a slow, dangerous, expensive process and even the most experienced engineers can overlook cracks in the structure or other critical deficiencies. However, Tuft University engineers are employing wireless sensors and drones that may soon be able to examine the condition of bridges in a quicker, more efficient manner.
Led by assistant professors Babak Moaveni and Usman Khan, the Tufts University team is developing a detection system using smart sensors that are permanently attached to bridge beams and joins. Each sensor can continuously record vibrations and process the recorded signals; furthermore, any changes in the vibration response can signify damage, Moaveni explained. A wireless system would then use unmanned aerial vehicles (UAVs) to hover near the sensors and collect data while taking visual images of bridge conditions. These quadcopters would transmit data to a central collection point for analysis. According to Tufts, Khan was recently awarded $400,000 award from the National Science Foundation to explore this technology, which requires addressing significant navigational and communications challenges before it could be a reliable inspection tool.
Five years ago, Moaveni installed a series of 10 wired sensors on a 145-foot-long footbridge on the Tufts Medford/Somerville campus. These sensors measured vibrations that passed through the bridge, caused by people walking across it. In 2011, Moaveni added nearly 5,000 pounds of concrete weights on the bridge deck to simulate the effects of damage on the bridge — a load well within the bridge’s limits. Connected by cables, the sensors recorded readings on vibration levels as pedestrians walked across the span before and after installation of the concrete blocks. Tufts notes that from the changes in vibration measurements, Moaveni and his research team could successfully identify the simulated damage on the bridge, validating his vibration-based monitoring framework.
The scientists are currently working on a way of scaling the system, in hopes that it could be applied to larger, car-carrying bridges. A major goal of his research, Moaveni says, is to develop computer algorithms that can automatically detect damage in a bridge from the changes in its vibration measurements. According to Moaveni, the system should already be capable of detecting severe damage, but still needs some tweaking before it can pick up on more subtle defects. “Right now, if a bridge has severe damage, we’re pretty confident we can detect that accurately. The challenge is building the system so it picks up small, less obvious anomalies.”
This isn’t the first time a drone has been used to examine the condition of fatigued bridges. Back in 2011, a team of architects used a remote-controlled aircraft to survey the 500-year-old Stirling Bridge in Scotland and assess what repair work needed to be done. From agriculture to real estate, there are countless ways these flying apparatuses will soon, if not already, revolutionize the world around us.