Title page for ETD etd-07292010-183849


Type of Document Master's Thesis
Author Spalt, Taylor B
URN etd-07292010-183849
Title Background Noise Reduction in Wind Tunnels using Adaptive Noise Cancellation and Cepstral Echo Removal Techniques for Microphone Array Applications
Degree Master of Science
Department Mechanical Engineering
Advisory Committee
Advisor Name Title
Fuller, Christopher R. Committee Chair
Brooks, Thomas F. Committee Member
Wicks, Alfred L. Committee Member
Keywords
  • Wind Tunnel
  • Cepstrum
  • Adaptive Noise Cancellation
  • Conventional Beamforming
  • Linear Array
  • Background Noise Reduction
  • Noise Sources
Date of Defense 2010-06-29
Availability unrestricted
Abstract
Two experiments were conducted to investigate Adaptive Noise Cancelling and Cepstrum echo removal post-processing techniques on acoustic data from a linear microphone array in an anechoic chamber. A point source speaker driven with white noise was used as the primary signal. The first experiment included a background speaker to provide interference noise at three different Signal-to-Noise Ratios to simulate noise propagating down a wind tunnel circuit. The second experiment contained only the primary source and the wedges were removed from the floor to simulate reflections found in a wind tunnel environment.

The techniques were applicable to both signal microphone and array analysis. The Adaptive Noise Cancellation proved successful in its task of removing the background noise from the microphone signals at SNRs as low as -20 dB. The recovered signals were then used for array processing. A simulation reflection case was analyzed with the Cepstral technique. Accurate removal of the reflection effects was achieved in recovering both magnitude and phase of the direct signal. Experimental data resulted in Cepstral features that caused errors in phase accuracy. A simple phase correction procedure was proposed for this data, but in general it appears that the Cepstral technique is and would be not well suited for all experimental data.

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