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A Comprehensive On-board Generator Health Management System

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-05-C-0122
Agency Tracking Number: N032-0283
Amount: $746,501.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: N03-179
Solicitation Number: 2003.2
Timeline
Solicitation Year: 2003
Award Year: 2005
Award Start Date (Proposal Award Date): 2005-01-25
Award End Date (Contract End Date): 2007-01-25
Small Business Information
2851 Commerce Street
Blacksburg, VA 24060
United States
DUNS: 627132913
HUBZone Owned: Yes
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Roger Duncan
 Principal Investigator
 (540) 552-5128
 woodruffc@lunainnovations.com
Business Contact
 Wendy Vogt
Title: Director of Contracts
Phone: (540) 552-5128
Email: vogtw@lunainnovations.com
Research Institution
N/A
Abstract

Generators play a key role in a wide range of military and commercial applications. Especially for aerospace applications, increased power generation with reduced size and weight is a continuous design objective that taxes life limiting components such as bearings, windings, diode assembles, and rectifiers in already harsh operating environments. Both time and money are lost as generator failures can lead to mission aborts and expensive, time-consuming maintenance procedures that affect overall fleet performance. To address this need, new technologies are required that permit continuous real-time monitoring of these generators to provide long-range forecasting of problems, preserve valuable hardware, improve safety of flight, extend time between maintenance, and increase vehicle autonomy. Luna Innovations proposes to develop an on-board generator health-management system that integrates data from fiber-optic sensors and supplemental data with a prognostic software architecture. This system will consist of two primary elements: a fiber-optic sensing system developed to measure critical indicators of failure in generators and health management software to fuse sensory information into a complete prognostic architecture that will ensure early damage detection, thereby learning of a problem when it is least costly to repair and before it becomes a threat to either crew safety or mission success.

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

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