Impedance-based Sensing Optimization & Algorithms for Visualization of Ship Hull Structural Health Monitoring Data

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-10-M-0301
Agency Tracking Number: N10A-042-0344
Amount: $99,998.00
Phase: Phase I
Program: STTR
Awards Year: 2010
Solicitation Year: 2010
Solicitation Topic Code: N10A-T042
Solicitation Number: 2010.A
Small Business Information
10 Canal Park, Suite 601, Cambridge, MA, 02141
DUNS: 111487588
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Seth Kessler
 (617) 661-5616
Business Contact
 Seth Kessler
Title: President
Phone: (617) 661-5616
Research Institution
 U.C. San Diego
 Carlos D Molina J.D.
 9500 Gilman Drive
Mail Code 0934
La Jolla, CA, 92093
 (858) 534-0247
 Nonprofit college or university
The implementation of structural health monitoring (SHM) systems into naval applications has been hindered due to component quantity, including sensors, power/communication cables, and acquisition/computation units, as well as data quality. Particularly for large-area applications such ship hulls, complexity of implied system infrastructure can be impractical, and data can be worthless with attenuation and EMI pickup on long analog cables. The payoff of reliable real-time SHM would be the ability to detect/characterize in-situ damage for condition-based maintenance, thereby greatly reducing overall life-cycle costs. Metis Design Corporation (MDC) has demonstrated point-of-measurement datalogging and digital sensor-busing during prior Phase II SBIR work, which minimizes SHM infrastructure and EMI susceptibility. During the proposed STTR effort, MDC will further exploit this SHM architecture to satisfy Navy mission requirements. Phase I will have 2 main research thrusts: optimization of an impedance-based damage characterization method, and development of diagnostic visualization tools. UCSD will adapt their piezo-impedance method to be compatible with MDC hardware, optimize size/placement, and develop/calibrate diagnostic algorithms. MDC will facilitate the UCSD detection method with their mature SHM infrastructure, and provide a state-of-the-art graphical interface for visualization of diagnostic results in support of blind validation testing. Phase II would extend this tool to include prognostics.

* Information listed above is at the time of submission. *

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