Data Driven Prognostics

Award Information
Agency:
Department of Defense
Branch
Missile Defense Agency
Amount:
$69,729.00
Award Year:
2003
Program:
STTR
Phase:
Phase I
Contract:
DASG6003P0332
Award Id:
64422
Agency Tracking Number:
03-0025T
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
10001 Derekwood Lane, Suite 204, Lanham, MD, 20706
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
061997029
Principal Investigator:
Carole Teolis
Director, Systems Engineering
(301) 577-6000
carole@technosci.com
Business Contact:
Amy Hizoune
Vice President, Finance
(301) 577-6000
hizounea@technosci.com
Research Institution:
ASOK RAY, PH.D., P.E.
Jackie Kline
Mechanical Engineering Dept, Pennsylvania State University
University Park, PA, 16802
(814) 865-6377
Nonprofit college or university
Abstract
In this SBIR Project we will develop and demonstrate novel general algorithms for anomaly detection in complex systems. Component wear in electrical and mechanical system components causes degradation that occurs on a slow time scale with respect to theobserved system behavior and is evident in very small magnitude changes to system behavior long before a component's eventual failure. An objective of the proposed research is to detect the precursors to slowly approaching failures in order that theremaining life of critical components can be accurately predicted at an early stage. We propose a novel approach for anomaly detection in complex systems using the tools of computational dynamics and pattern discovery. The predictive algorithms will betested on a subsystem of the Airborne Laser. New advances in sensor technology, failure analysis techniques, system predictive modeling, data fusion and automated reasoning algorithms are beginning to make it possible for these predictive technologies tobe developed into a complete Prognostic Health Monitoring system. These same core technologies could be harnessed for almost any type of equipment. As a result of the development of predictive maintenance technologies, we could witness an incrediblerevolution in the way large multi-unit electromechanical systems, such as ships; aircraft or even power plants are maintained.

* information listed above is at the time of submission.

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