Hybrid Model Fusion for Gas Turbine Engine Diagnostics and Prognostics

Award Information
Agency:
National Aeronautics and Space Administration
Branch
n/a
Amount:
$69,991.00
Award Year:
2002
Program:
SBIR
Phase:
Phase I
Contract:
NAS4-02038
Award Id:
56484
Agency Tracking Number:
012685
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
13029 Danielson Street, Suite 200, Poway, CA, 92064
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Tom Brotherton
Vice President, CTO
(858) 679-4140
tom.brotherton@iac-online.com
Business Contact:
Laura Goodrich
Vice President, Contracts
(858) 679-4140
laura.goodrich@iac-online.com
Research Institution:
n/a
Abstract
In Phase I IAC, teamed with Pratt & Whitney and Luppold & Associates, developed and demonstrated a hybrid modeling approach to enhance diagnostics and prognostics performance on F-117 engines. The hybrid model fuses a physics-based model developed by Pratt & Whitney called STORM with an empirical model that uses neural networks to monitor and quantify unmodeled and/or mismodeled engine phenomena that corrupt STORM?s diagnostic outputs. The resulting hybrid model is called the enhanced STORM or eSTORM. In Phase I eSTORM was demonstrated to work extremely well for limited conditions when processing simulated engine data. In Phase II IAC proposes to develop a standalone system for real time implementation of a full F-117 engine eSTORM. The system will cover the full C-17 flight envelope. The system will include interfaces to accept data from the C-17 aircraft bus and will be capable of on-wing operation. The system will be demonstrated using real F-117 inputs running in a test bench environment. Though developed explicitly for an F-117 application, the hybrid modeling concept developed on this Phase II is generic and can be used for eSTORM development on all Pratt & Whitney military and commercial engines.

* information listed above is at the time of submission.

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