A Testbed for Data Fusion for Gas Turbine Engine Diagnostics and Predictive Diagnostics

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$0.00
Award Year:
2001
Program:
SBIR
Phase:
Phase I
Contract:
F33615-01-C-2129
Award Id:
55277
Agency Tracking Number:
001PR-2320
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
10299 Scripps Trail, PMB 231, San Diego, CA, 92131
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
097858836
Principal Investigator:
Thomas Brotherton
VP, Chief Technical Offic
(858) 679-4140
tom.brotherton@iac-online.com
Business Contact:
Laura Goodrich
Vice President, Finance
(858) 679-4140
laura.goodrich@iac-online.com
Research Institute:
n/a
Abstract
The key to producing more confident, real-time, on-wing diagnoses resides in the processing of multisensor data. Adding expensive new sensors is not the solution, but data fusion is. Fusion saves cost and weight; no new sensors are required. Fusionreduces false alarm rates; faults to be seen across multiple sensors. Diagnostic performance is improved by allowing detection of unique fault patterns seen on sets of sensors instead of a single sensor. Fusion enables predictive diagnostics; low-levelinformation is integrated across sensors so potential faults can be detected earlier. In Phase IIAC developed a PC-based gas turbine engine health monitoring system that uses a combination of signal and information processing algorithms to perform data fusion for engine fault diagnostics and predictive diagnostics. The system is built around anIntelligent Mechanical Diagnostics System (i-mds) Matlab toolbox that aids in systems development of future and in the integration of new sensors and new information. In Phase II that fusion technology and i-mds will be further developed and included intoan integrated system to support individual aircraft field maintenance, fleet maintenance, as well as research engineers in performing diagnostics and predictive diagnostics on real data. That development includes significant amounts of real data.

* information listed above is at the time of submission.

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