Innovative Method for Aircraft Gross Weight and Center of Gravity Estimation

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-11-C-0489
Agency Tracking Number: N112-114-0126
Amount: $79,992.00
Phase: Phase I
Program: SBIR
Awards Year: 2011
Solicitation Year: 2011
Solicitation Topic Code: N112-114
Solicitation Number: 2011.2
Small Business Information
3190 Fairview Park Drive, Suite 650, Falls Church, VA, -
DUNS: 010983174
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Nicoleta Apetre
 Senior Engineer
 (703) 226-4076
Business Contact
 Scott Bradfield
Title: President
Phone: (703) 226-4061
Research Institution
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. *

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