한국음향학회지 (The Journal of the Acoustical Society of Korea)

  • 제32권5호
  • /
  • Pages.408-414
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  • 2013
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  • 1225-4428(pISSN)
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  • 2287-3775(eISSN)
한국음향학회 (The Acoustical Society of Korea)
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비정상 잡음환경에서의 지능형 적응 능동소음제어

Intelligent Adaptive Active Noise Control in Non-stationary Noise Environments

  • Mu, Xiangbin (Department of Electrical, Electronics and Communication Engineering, Korea University of Technology and Education) ;
  • Ko, JinSeok (Department of Electrical, Electronics and Communication Engineering, Korea University of Technology and Education) ;
  • Rheem, JaeYeol (Department of Electrical, Electronics and Communication Engineering, Korea University of Technology and Education)
  • 투고 : 2012.10.19
  • 심사 : 2013.04.04
  • 발행 : 2013.09.30
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⟨ 이전 논문 다음 논문 ⟩

초록

능동소음제어에서 널리 사용되는 FxLMS 알고리즘은 비정상 잡음환경에서 불안정하게 동작하는 경우가 있다. 이와 같은 문제를 해결하기 위하여, Sun과 Akhtar는 FxLMS 알고리즘의 갱신 과정에서 기준신호를 수정하는 방법을 제안하였다. 그러나 이들의 방법은 임펄스 노이즈가 발생할 경우 만족스러운 안정성을 보여주지 못하였다. 본 논문에서 제안된 알고리즘은 확률추정과 영교차율을 이용하여 능동소음제어의 안정성과 성능을 개선하였다. 또한 최적의 파라미터 선정을 위하여 퍼지 추론을 사용하였다. 제안된 방법의 실험결과 비정상 잡음환경에서 기존의 방법에 비하여 우수한 안정성과 빠른 수렴속도를 보여줬다.

The famous filtered-x least mean square (FxLMS) algorithm for active noise control (ANC) systems may become unstable in non-stationary noise environment. To solve this problem, Sun's algorithm and Akhtar's algorithm are developed based on modifying the reference signal in update of FxLMS algorithm, but these two algorithms have dissatisfactory stability in dealing with sustaining impulsive noise. In proposed algorithm, probability estimation and zero-crossing rate (ZCR) control are used to improve the stability and performance, at the same time, an optimal parameter selection based on fuzzy system is utilized. Computer simulation results prove the proposed algorithm has faster convergence and better stability in non-stationary noise environment.

키워드

참고문헌

  1. S. J. Elliot, Signal Processing for Active Control (Academic Press, London, 2001), pp. 2-45.
  2. S. M. Kuo and D. R. Morgan, Active Noise Control Systems: Algorithms and DSP Implementations (Wiley, New York, 1996), pp. 62-77.
  3. P. Lueg, Process of Silencing Sound Oscillations, U.S. Patent 2043416 (1936)
  4. X. Sun, S. M. Kuo, and G. Meng, "Adaptive algorithm for active control of impulsive noise," J. Sound Vib. 291, 516-522 (2006). https://doi.org/10.1016/j.jsv.2005.06.011
  5. M. T. Akhtar and Mitsuhashi, "Improving performance of FxLMS algorithm for active noise control of impulsive noise," J. Sound Vib. 327, 647-656 (2009). https://doi.org/10.1016/j.jsv.2009.07.023
  6. R. Leahy, Z. Zhou and Y. C. Hsu, "Adaptive filter of stable processes for active attenuation of impulsive noise," in Proc. of IEEE Int. Conference on Acoustic, Speech and Signal Processing, 5, 2983-2986, (1995).
  7. X. Mu, J. Ko and J. Rheem, "Stability improvement of active noise control in non-stationary noise environments," in Proc. of IEEK Fall Conference, pp.413-414, (2010).
  8. H. J. Zimmermann, Fuzzy Set Theory and Its Applications (Kluwer-Nijhoff Publishing, 2001), pp. 226-232.