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Fault Diagnostics, Prognostics, and Self-Healing Control of Navy Electric Machinery

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-06-M-0263
Agency Tracking Number: N064-033-0105
Amount: $99,974.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N06-T033
Solicitation Number: N/A
Timeline
Solicitation Year: 2006
Award Year: 2006
Award Start Date (Proposal Award Date): 2006-08-01
Award End Date (Contract End Date): 2007-05-31
Small Business Information
100 Great Meadow Rd., Suite 603
Wethersfield, CT 06109
United States
DUNS: 808837496
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Sudipto Ghoshal
 Manager, Professional Ser
 (860) 257-8014
 sudipto@teamqsi.com
Business Contact
 Chuck Vallurupalli
Title: EVP and COO
Phone: (860) 257-8014
Email: chuckv@teamqsi.com
Research Institution
N/A
Abstract

The objective of this project is to develop an integrated condition monitoring, fault diagnostics and prognostics scheme for power electronic converters and electromechanical devices, e.g., advanced induction motors, specifically targeting the DD(X) platform and subsequently expanding the scope for addressing the needs of other defense-related and commercial applications. An additional goal of this project is to explore "self healing" strategies for critical electrical systems to improve system reliability, availability, and "limp-home" capability. Increased use of electric power to run communication, navigation, and even the prime movers is an ongoing trend in military and commercial engineering systems. Safe and reliable operation of these systems largely depends on the uninterrupted functioning of the underlying power generators, converters and electromechanical systems. Intelligent fault diagnostic and prognostic schemes with low false alarm rates and smart reconfiguration schemes play a key role in ensuring outage-free operation of these systems.BENEFITS: The technology proposed for development in this Phase I proposal will support model-based and data-driven fault diagnosis and physical model-based prognosis through a best-of-breed information fusion approach. This technology is expected to be implemented as a new module of QSI's TEAMS product suite. TEAMS Test Designer will host the feature extraction and testing techniques developed for this project. Sensor allocation and reconfiguration algorithms will be augmented into the existing optimization techniques suite of TEAMS. TEAMS is currently used for early design decisions related to testability and maintainability, as well as for developing solutions for diagnostics, fault isolation and guided maintenance of fielded systems. The industries interested in integrated diagnostics and material-based prognostics would include the manufacturers and end users of such supplies that are used in environments where a failure has serious consequences. DD(X) program primes are the initial target, while luxury cruise ship and fast ocean liner builders, their customers and similar industry segments are also of interest and, if appropriately marketed, will provide possible venues for commercial applications. In addition, similar prognostics and diagnostics technology developed through this effort will also have significant commercial potential in the aviation industry as well.

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

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