Aircraft Electrical Power System Diagnostics and Health Management

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$69,998.00
Award Year:
2006
Program:
STTR
Phase:
Phase I
Contract:
N00014-06-M-0273
Award Id:
77862
Agency Tracking Number:
N064-007-0103
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
100 Great Meadow Rd., Suite 603, Wethersfield, CT, 06109
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
808837496
Principal Investigator:
SudiptoGhoshal
Manager, Professional Ser
(860) 257-8014
sudipto@teamqsi.com
Business Contact:
ChuckVallurupalli
EVP and COO
(860) 257-8014
chuckv@teamqsi.com
Research Institute:
VANDERBILT UNIV.
Carol L Hachey
Division of Sponsored Research
Nashville, TN, 37203
(615) 322-3979
Nonprofit college or university
Abstract
This proposal is a joint effort between Qualtech Systems, Incorporated (QSI), the Institute for Software Integrated Systems at Vanderbilt University (VU), and Hamilton Sundstrand (HS) in Rockford, IL. QSI and VU have the combined knowledge and experience in successful development of a novel solution to aircraft system and subsystem prognostics and maintenance tools and have developed state-of-the-art technology and mature deployed products in the field. Hamilton Sundstrand is among the largest global suppliers of technologically advanced aerospace products and is the manufacturer of the Integrated Drive Generators (IDG) that are being deployed on the Multi-mission Maritime Aircraft (MMA). For the proposed study, we will focus specifically on the IDG of the MMA as our target system. We propose to develop integrated on-line diagnostic and prognostic technologies for aircraft electrical power systems that feed into the overall vehicle health management system. The primary goal is to improve vehicle readiness and safety while reducing operations and maintenance costs. We propose to adopt a comprehensive model-based solution with fault detection and isolation (FDI) algorithms that work in conjunction with prognostic methods to estimate the health of degrading components and schedule maintenance operations to avoid downtime without compromising safety and mission success.BENEFITS: The technology proposed for development in this Phase I proposal will support 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 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. This effort will result in the development of new commercializable product that can address the needs of industries interested in generator diagnostics and prognostics. These would include the manufacturers of all systems and infrastructure that have power generation and converter units being used in environments where a failure in power generation components has serious consequences.

* information listed above is at the time of submission.

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