The aim of structural health monitoring (SHM) is to achieve structural reliability and sustainability through integrated health management and prognosis. Research areas include:

1. Fundamental aspects of autonomous, active material-based sensors design

2. Sensory information processing techniques

3. Novel damage detection techniques

4. Optimal sensor placement algorithms

Efficient and cost-effective approaches for maintaining aging structures require an integrated diagnostic and prognostic framework. This, in turn, involves a critical assessment of the current state of the system so that preventative measures and prognostic steps can be taken. Researchers use a multidisciplinary approach that combines modeling, data interrogation techniques and experimental validation tools to develop an early warning system applicable to a range of engineering fields.

Current research focus includes developing modeling active wave-based techniques to detect cracks in thick, complex metallic structures. This technique is used to complement data mining approaches as well as to optimize the placement of sensors on structural ‘hot spots.’ This method is also used to study the interaction of the waves with the plastic zone ahead of a crack, a difficult task to perform experimentally. Once the signals are simulated, a pre-stack reverse time migration technique is used to localize the damage.