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Diagnostics and Health Management for Remotely Piloted Aircraft (RPA) Payloads

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-11-M-3138
Agency Tracking Number: F112-001-1078
Amount: $149,991.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: AF112-001
Solicitation Number: 2011.2
Solicitation Year: 2011
Award Year: 2011
Award Start Date (Proposal Award Date): 2011-09-30
Award End Date (Contract End Date): N/A
Small Business Information
1965 Lycoming Creek Road Suite 205
Williamsport, PA -
United States
DUNS: 028856420
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Gregory Bower
 Principal Investigator
 (570) 322-2700
Business Contact
 Cathy Brooke
Title: Chief Financial Officer
Phone: (570) 322-2700
Research Institution

ABSTRACT: In recent years significant effort in the development of sophisticated algorithms to complete prognostics (remaining useful life) RUL of electronic and mechanical systems has been completed. Life prediction of on-board sensor suites of remotely piloted aircraft (RPA) remains behind the development curve of current work in health monitoring. QorTek, in collaboration with Northrop Grumman, proposes to implement a method based on statistics to substantially improve diagnostics and prognostics of the on-board sensor systems of the Global Hawk platform. The Global Hawk program headed by Northrop Grumman is an unmanned surveillance platform that has been deployed to areas such as Iraq and Afghanistan in recent conflicts. The Global Hawk platform is used both by the United States Air Force and Navy. Anticipated results of the program include health monitoring, remaining life prediction, source identification of system degradation, and system reconfiguration for maintaining system readiness. BENEFIT: In military markets, the ability to predict the end of useful system life can save human lives and maintain mission readiness. In terms of commercialization, the ability to predict RUL can be economically beneficial. Many types of commercial systems from traction applications, industrial machinery, to airliner maintenance can benefit from the implementation of a maintenance schedule algorithm. Maintenance can be planned as needed instead of a regularly scheduled maintenance reducing down time. Integration of a health monitoring algorithm into the commercial fleet can be a viable method to reduce maintenance costs and down time.

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

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