Validation Tools and Data for PHM Technologies

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$69,989.00
Award Year:
2004
Program:
SBIR
Phase:
Phase I
Contract:
N68335-04-C-0188
Award Id:
69970
Agency Tracking Number:
N041-028-0072
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
850 Energy Drive, Suite 307, Idaho Falls, ID, 83401
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
089822014
Principal Investigator:
SeanMarble
President
(208) 522-8560
smarble@sentientscience.com
Business Contact:
SeanMarble
President
(208) 522-8560
smarble@sentientscience.com
Research Institute:
n/a
Abstract
Emerging prognostics and health management (PHM) technologies will reduce maintenance costs for military aircraft while improving safety and availability. On the Joint Strike Fighter, software modules supplied by multiple vendors will be assembled into PHM area reasoners. System integrators will need tools and data for evaluation, selection, and testing of these modules. Sentient Corporation, in cooperation with Pratt & Whitney and Purdue University, will develop a PHM V&V toolset for efficient and effective testing using proven methodologies for diagnostic validation along with innovative metrics for assessing the accuracy and uncertainty of predictive prognostics. Ground truth data is also essential to any V&V capability. To maximize access to and utility of existing data, the new toolset will include powerful functions for secure distributed access to archival data. Finally, a Virtual Bearing Simulator will be created that combines general bearing dynamics and fault progression models with application specific finite element transfer function analyses to generate realistic fault vibration signatures and failure progressions. These signatures will allow PHM development to begin at the design stage for new platforms, and will augment operational validation data for deployed platforms. This project will leverage an existing program to develop fault-to-failure progression models that includes a large experimental study of bearing fault signatures and failure trajectories.

* information listed above is at the time of submission.

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