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Prof. Krishnamachari Co-PI on multi-million dollar NSF-ITR Grant

March 12, 2004 —
Prof. Krishnamachari Co-PI on multi-million dollar NSF-ITR Grant

Professor Bhaskar Krishnamachari is Co-PI on a recent Information Technology Research Grant Number 0325875 awarded by the National Science Foundation. The project is titled "Structural Health Monitoring Using Local Excitation and Large-Scale Networked Sensing." The Principal Investigator on this interdisciplinary project is Prof. Ramesh Govindan from Computer Science. The other collaborating faculty are Prof. Gaurav Sukhatme (Computer Science), Prof. Erik Johnson (Civil Engineering) and Prof. Sami Masri (Civil Engineering). The project started on September 15, 2003 and is estimated to last till August 2008. The estimated funding for this project is $2.6 million.

Structural Health Monitoring (SHM) is a highly interdisciplinary area of research focused on developing techniques to detect damage in structures such as buildings, bridges, aircraft, ships and spacecraft. Most SHM research to date has focused either on global damage assessment techniques using low-resolution measurements of a structure's response to ambient excitation, or on limited local independent damage detection mechanisms. The proposed project advocates a paradigm shift in SHM, using decentralized local excitation and high-resolution measurements of response to these excitations, detected and collaboratively analyzed through a spatially dense wireless network of devices. This shift promises simpler and more accurate techniques to identify and even localize damage
within the structure.

The goal of the proposed research is the design of a networked computer system, with distributed actuation and sensing, for SHM. The term "networked SHM" denotes the class of monitoring systems that will be enabled by this research. By combining local excitation with high-resolution sensing, networked SHM is quite distinct from other sensor network applications being examined today. Networked SHM promises a future where, for example, buildings are constructed using concrete mixed with several tens of thousands of embedded sensor devices as well as low-power local exciters. The network of sensors will be able to continuously monitor the structure, trigger alarms that identify the onset of damage, precisely pinpoint the location of damage and also provide a long-term history of ambient stresses imposed on the building.