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Active noise control in a pure tone diffuse sound field using virtual sensing

J. Acoust. Soc. Am. Volume 125, Issue 6, pp. 3742-3755 (2009); (14 pages)

D. J. Moreau, J. Ghan, B. S. Cazzolato, and A. C. Zander

School of Mechanical Engineering, The University of Adelaide, Adelaide, South Australia 5005, Australia

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Local active noise control systems generate a zone of quiet at the physical error sensor using one or more secondary sources to cancel acoustic pressure and its spatial derivatives at the sensor location. The resulting zone of quiet is generally limited in size and as such, placement of the error sensor at the location of desired attenuation is required, which is often inconvenient. Virtual acoustic sensors overcome this by projecting the zone of quiet away from the physical sensor to a remote location. The work described here investigates the effectiveness of using virtual sensors in a pure tone diffuse sound field. Stochastically optimal virtual microphones and virtual energy density sensors are developed for use in diffuse sound fields. Analytical expressions for the controlled sound field generated with a number of control strategies are presented. These expressions allow the optimal control performance to be predicted. Results of numerical simulations and experimental measurements made in a reverberation chamber are also presented and compared.

© 2009 Acoustical Society of America

ACKNOWLEDGMENTS

The authors gratefully acknowledge the financial support for this work provided by the Australian Research Council.

Article Outline

  1. INTRODUCTION
  2. THEORETICAL BACKGROUND
    1. Control strategy 1: Canceling the pressure at a point with one control source
    2. Control strategy 6: Canceling the pressure at a virtual location with one control source using the pressure and pressure gradient at a point
    3. Control strategy 8: Canceling the pressure and pressure gradient at a virtual location with two control sources using the pressures and pressure gradients at two points
  3. DIFFUSE FIELD SIMULATIONS
  4. DIFFUSE FIELD EXPERIMENTS
  5. RESULTS
    1. Numerically simulated results
    2. Experimental results
      1. Improving conditioning
  6. CONCLUSIONS

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ARTICLE DATA

History
Received 19 Jun 2008
Accepted 27 Mar 2009
Revised 22 Mar 2009

PUBLICATION DATA

ISSN

0001-4966 (print)  

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