Improved Methodology for the Prediction of the Empennage Maneuver In-Flight Loads of a General Aviation Aircraft Using Neural Networks

Kim, David; Pechaud, Laure

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Improved Methodology for the Prediction of the Empennage Maneuver In-Flight Loads of a General Aviation Aircraft Using Neural Networks

2001-12-01
By Kim, David ; Pechaud, Laure

File Language:

English

Details

Creators:

Kim, David ; Pechaud, Laure
Corporate Creators:

Embry-Riddle Aeronautical University
Corporate Contributors:

United States. Department of Transportation. Federal Aviation Administration. Office of Aviation Research
Subject/TRT Terms:
Publication/ Report Number:

DOT/FAA/AR-01/80
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final Report
Corporate Publisher:

United States. Department of Transportation. Federal Aviation Administration. William J. Hughes Technical Center
Description:

This research presents and documents an improved methodology for the prediction of empennage maneuver loads of a general aviation aircraft. Previous research using Neural Networks and angular accelerometers achieved predictions of strains to within ±50με of the measured strains in 100% of the cases for the vertical tail and 93% for the horizontal tail. The improved methodology is based on maneuver recognition using Neural Networks with the focus on both cost saving and improving the horizontal tail predictions. The recorded data are first classified by data clusters corresponding to known maneuvers then analyzed using Neural Networks trained for those maneuvers. This weighted sum approach successfully predicted strains to within ±50με of the measured strains in 100% of the cases for the horizontal tail. Angular accelerometer signals were replaced by numerically differentiated rate-gyro signals for the Neural Networks, and the predictions were found to be comparable resulting in considerable cost savings for the required minimum instrumentation.
Format:

PDF
Funding:

98-G-025
Download URL:

https://rosap.ntl.bts.gov/view/dot/94152/dot_94152_DS1.pdf
File Type:

[PDF - 6.95 MB]
Collection(s):

FAA William J. Hughes Technical Center for Advanced Aerospace
Main Document Checksum:

urn:sha-512:3f3dc943a473dc72eb6833359b24220c582c8dc0555f11c836e2796f4c69baca5df078d1553ffc6ccdf4de72b7bddf58cafdc61ed0c6e095d43c4ff1aa664ba4

File Language:

English

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