Innovative Method for Aircraft Gross Weight and Center of Gravity Estimation

Award Information
Agency:
Department of Defense
Branch
n/a
Amount:
$79,992.00
Award Year:
2011
Program:
SBIR
Phase:
Phase I
Contract:
N68335-11-C-0489
Award Id:
n/a
Agency Tracking Number:
N112-114-0126
Solicitation Year:
2011
Solicitation Topic Code:
N112-114
Solicitation Number:
2011.2
Small Business Information
3190 Fairview Park Drive, Suite 650, Falls Church, VA, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
010983174
Principal Investigator:
Nicoleta Apetre
Senior Engineer
(703) 226-4076
napetre@tda-i.com
Business Contact:
Scott Bradfield
President
(703) 226-4061
sbradfield@tda-i.com
Research Institution:
Stub




Abstract
An accurate, automated assessment of helicopter Gross Weight (GW) and Center of Gravity (CG) is critical for the determination of aircraft fatigue and life estimates since GW/CG affect static and dynamic characteristics of helicopters. Therefore GW and CG of a helicopter are valuable information in calculating reliable loads and remaining fatigue life. These in turn will assist the condition based maintenance systems used to enhance safety and reduce the operating cost of helicopters. An automated system for GW and CG will improve aircraft structural life estimation and performance characteristics, will relieve pilot"s burden of logging data, and will also improve situational awareness. To capture GW and CG changes continuously throughout the flight, advanced methods are required as conventional methods are not sufficient and prone to errors. Technical Data Analysis, Inc. (TDA) envisions a comprehensive solution based on a combination of physics based (deterministic) models and data driven (stochastic) models. TDA"s team believes that combining both methods will overcome each technique limitations and will take advantage of each method"s strengths. Therefore TDA"s team aims to develop a hybrid system that combines the powerful estimation capabilities of the Kalman Filter (KF) scheme with the strong learning capabilities of the Neural Network (NN).

* information listed above is at the time of submission.

Agency Micro-sites


SBA logo

Department of Agriculture logo

Department of Commerce logo

Department of Defense logo

Department of Education logo

Department of Energy logo

Department of Health and Human Services logo

Department of Homeland Security logo

Department of Transportation logo

Enviromental Protection Agency logo

National Aeronautics and Space Administration logo

National Science Foundation logo
US Flag An Official Website of the United States Government