Type of Document	Master's Thesis
Author	Cabell, Randolph H.
URN	etd-11212012-040018
Title	The automatic identification of aerospace acoustic sources
Degree	Master of Science
Department	Mechanical Engineering
Advisory Committee	Advisor Name Title Fuller, Christopher R. Committee Chair O'Brien, Walter F. Jr. Committee Member Wicks, Alfred L. Committee Member
Keywords	Airplanes
Date of Defense	1989-02-15
Availability	restricted
Abstract This work describes the design of an intelligent recognition system used to distinguish noise signatures of five different acoustic sources. The system uses pattern recognition techniques to identify the information obtained from a single microphone. A training phase is used in which the system learns to distinguish the sources and automatically selects features for optimal performance. Results were obtained by training the system to distinguish jet planes, propeller planes, a helicopter, train, and wind turbine from one another, then presenting similar sources to the system and recording the number of errors. These results indicate the system can successfully identify the trained sources based on acoustic information. Classification errors highlight the impact of the training sources on the system’s ability to recognize different sources.
Files	Filename       Size       Approximate Download Time (Hours:Minutes:Seconds)     28.8 Modem   56K Modem   ISDN (64 Kb)   ISDN (128 Kb)   Higher-speed Access  LD5655.V855_1989.C323.pdf 8.03 Mb 00:37:11 00:19:07 00:16:44 00:08:22 00:00:42 next to an author's name indicates that all files or directories associated with their ETD are accessible from the Virginia Tech campus network only.

If you have questions or technical problems, please Contact DLA.