An Approach to Health Management and Sustainability for Critical Aircraft Systems

Award Information
Agency:
National Aeronautics and Space Administration
Branch
n/a
Amount:
$99,703.00
Award Year:
2010
Program:
STTR
Phase:
Phase I
Contract:
NNX10RA81P
Award Id:
95660
Agency Tracking Number:
090049
Solicitation Year:
n/a
Solicitation Topic Code:
T1
Solicitation Number:
n/a
Small Business Information
200 Canal View Blvd., Rochester, NY, 14623
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
073955507
Principal Investigator:
George Vachtsevanos
Principal Investigator
() -
george.vachtsevanos@impact-tek.com
Business Contact:
Carol Marquardt
Business Official
(585) 627-1923
Research Institute:
Georgia Insitute of Technology

505 Tenth Street, NW
Atlanta, AK, 30332
(404) 894-6929
Nonprofit college or university
Abstract
Impact Technologies, in collaboration with the Georgia Institute of Technology and its industrial partners, proposes to develop and demonstrate innovative technologies to integrate anomaly detection and failure prognosis algorithms into automated fault mitigation strategies for advanced aircraft controls. Traditional reactive fault tolerant control approaches fail to provide optimal fault mitigation over a long period of time to guarantee the integrity of the platform for the mission duration. We will create a generic simulation environment to demonstrate fault detection and progression at the component level, using electromechanical actuators as a testbench. The proposed Anomaly Detection/Mitigation system accepts sensor inputs, extracts features from raw data and employs an anomaly detection module to determine the presence of an anomaly with performance guarantees; a prognostic routine, built on Bayesian estimation (particle filtering) techniques to estimate the remaining useful life of the component; finally, a mitigation strategy trades off between performance and control authority to extend the life of the failing component until the mission is completed. This innovative prognostics-enhanced approach to fault mitigation uses Model Predictive Control techniques running in real time. Core algorithms will be implemented on embedded systems and used in hardware-in-the-loop demonstrations.

* information listed above is at the time of submission.

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