This project will develop a new structural health monitoring technique and its application through system integration by direct implementation of the software advances in data processing and interpretation algorithms together with hardware advances in smart wireless sensing. In particular, a novel nonlinear pattern classification algorithm will be developed and then embedded into a Field-Programmable Gate Array (an FPGA) and microprocessor-based processor core to enable and optimize the functionality of on-board data processing of nonlinear and nonstationary data sets recorded in smart wireless sensing.
The project research is expected to impact infrastructure health assessment and monitoring, earthquake hazard mitigation and homeland security. The proposal develops close ties with industrial partners Weidlinger Associates and Xilinx through summer internships. Training materials on the new capabilities of FPGA-based smart wireless sensing will be disseminated widely. The participating institutions (University of Oklahoma and Washington University in St. Louis) will work together to engage graduate and undergraduate students, especially those from under-represented groups.
