The American Society of Civil Engineers (ASCE) estimates that, in the US alone, $3.6 trillion dollars are needed by 2020 to repair and update infrastructure in order to ensure public safety and economic growth.
As infrastructure assets age, design assumptions made during the original planning stages become increasingly obsolete and outdated. These structures are often subjected to more usage, larger loads, and more environmental stresses than originally expected.
Given the vast inventory of such aging infrastructure assets in the US and other developed countries, informed decisions must be made before spending limited budgets to upgrade and replace such assets. Owners and stakeholders need information that will aid in condition-based maintenance decision-making in order to safeguard public safety but still work within limited replacement budgets.
Andrew Swartz is developing automated and embedded sensing and data interrogation of the condition of civil structures to supplement limited inspection
budgets. His goal: to provide real-time alerts when distress conditions occur.
“Continuous monitoring of structures for damage is known as structural health monitoring (SHM),” Swartz explains. “SHM systems can warn owners and users when significant changes in structural performance are detected. These changes are often associated with dangerous damage conditions.”
Deployment of SHM systems as long-term, low-cost, automated wireless sensor nodes is a major goal of Swartz’s research group. Focused on both bridge and wind turbine structures, their research involves wireless data collection, autonomous extraction of damage-sensitive features from the data,
modeling of structural behavior to correlate damage and behavior, and statistical decision making for alerts and risk assessment.
Early detection of damage in structures due to excessive loads or fatigue, as well as deterioration due to aging and environmental attack, are major challenges for bridge, building, wind turbine, and other structures, but automated monitoring and response to dangerous conditions is possible using structural control technologies,” says Swartz. “Fusion of SHM and advances in semi-active control strategies make possible adaptive sensing and control networks that can work to actively redistribute loads in order to minimize stresses induced into damaged components during extreme loading events such as earthquakes,” he adds.
“Such a sensor network must first be able to collect data and autonomously identify the existence, type, location, and severity of damage. A semi-active control network is composed of sensors and actuators, mechanical devices that tune the dynamic vibrational properties of a structure in real time in order to minimize unwanted or damaging vibrations. These systems are typically designed to minimize danger to a healthy structure and rely on fixed control algorithms that have been optimized assuming an undamaged state,” he explains. “With the addition of damage information, a combined SHM/control network will be able to adapt itself to the presence of damage by reprogramming its own control algorithm such that vibrational modes that induce stresses into identified damaged components may be minimized. In this way, SHM information can be leveraged immediately to protect structures and their occupants.”