Title page for ETD etd-11212012-040018


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.

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