PI: Yu Ding Texas Engineering Experiment Station
This project is one component of a 3-way collaborative sensors research program, between University of Connecticut (Grant 0428210), Columbia University (Grant 0427353) and Texas Engineering Experiment Station (Grant 0427878). The research is aimed at developing a wireless piezoelectric sensor network as well as the associated decision making algorithms with enhanced sensor system robustness, reliability, and detection sensitivity for structural health monitoring.
To improve the detection sensitivity, a smart adaptive sensor node is designed to allow multi-resonance passive frequency response based detection and active damage interrogation. To enhance the network robustness, distributed data decoding, distributed interference avoidance, and robust routing strategies are investigated. To reduce false alarms, an adaptive statistical threshold is established and sensor self-diagnosis techniques are developed. A multidisciplinary team has been formed by researchers from Mechanical, Electrical, and Industrial Engineering fields from these three institutions to carry out the work.
This project is expected to create an enabling technology for next-generation large-structure health monitoring and thus have strategic importance to a series of industrial/military systems. The technology could substantially reduce system downtime and service workload. This research will provide multidisciplinary training for all participating students. Research accomplishments will be implemented into undergraduate/graduate curricula and also enhance laboratory developments in all partner universities.
This is a project supported under Sensors Initiative NSF 04-522.
