The Transactions of the Korean Institute of Electrical Engineers P (전기학회논문지P)

The Korean Institute of Electrical Engineers (대한전기학회)
권호 표지

A Neural Multiple LMS Based ANC System for Reducing Acoustic Noise of High-Speed Trains

신경회로망 다중 LMS 기법을 이용한 고속철도의 실내소음저감을 위한 ANC 시스템

  • 조현철 (울산과학대학 전기전자학부) ;
  • 이권순 (동아대학교 전기공학과) ;
  • 남현도 (단국대학교 전자전기공학부)
  • Published : 2009.12.01
Download PDF
⟨ Previous Next ⟩

Abstract

This paper presents a novel active noise control (ANC) system using least mean square (LMS) algorithm and neural network approach for decreasing acoustic noise signals inside high-speed trains. We construct a LMS framework as a nominal ANC system and additionally design an artificial single-layered perceptron model as an auxiliary ANC which is aimed to reduce real-time residuary noise due to its nonstationary and uncertain nature. Parameter vector of the hybrid ANC is determined through online estimation to realize an adaptive ANC configuration by means of the steepest descent algorithm. We achieve simulation experiment to demonstrate the proposed ANC system employing realistic acoustic noise signals measured in Korea Train eXpress (KTX).

Keywords

References

  1. 김재철, "해외철도기술동향: 차륜/레일 접촉에 의한 소음과 저감기술," 한국철도학회지, vol. 11, no. 3, pp. 23-28, 2008
  2. T. Tanaka, C. Jindaiji-higashicho, K. Li, "Development of an active muffler for medium-duty diesel vehicles considering thermal influence and control trackability," Noise Control Engineering Journal, vol. 51, no. 2, pp. 90-96, 2003 https://doi.org/10.3397/1.2839702
  3. Y. Song, Y. Gong, M. Sen, "A robust hybrid feedback active noise cancellation headset," IEEE Trans. on Speech & Audio Processing, vol. 13, no. 4, pp. 607-617, 2005 https://doi.org/10.1109/TSA.2005.848878
  4. J. Diaz, J. Vinolas, J. M. Egana, "Method of adjusting active noise control system parameters for application in railway sleeping cars," Noise Control Engineering Journal, vol. 54, no. 4, pp. 263-270, 2006 https://doi.org/10.3397/1.2219897
  5. 백광현, "능동 소음/진동 제어의 해외 연구동향," 전기의 세계, vol. 56, no. 11, pp. 24-27, 2007
  6. S. M. Kuo, D. R. Morgan, "Active noise control: a tutorial review," Proc. of the IEEE, vol. 87, no. 6, pp. 943-973, 1999 https://doi.org/10.1109/5.763310
  7. K. K. Das, J. K. Satapathy, "Frequency-domain block filtered-x NLMS algorithm for multichannel ANC," Int. Conf. on Emerging Trends in Engineering & Technology, pp. 1293-1297, 2008
  8. X. Yegui, A. Ikuta, M. Liying, K. Khorasani, "Stochastic analysis of the FXLMS-Based narrowband active noise control system," IEEE Trans. on Audio, Speech, & Language Processing, vol. 16, no. 5, pp. 1000-1014, 2008 https://doi.org/10.1109/TASL.2008.921756
  9. H.-S. Kim, Y. Park, "Delayed-X LMS algorithm: An efficient ANC algorithm utilizing robustness of cancellation path model," J. of Sound & Vibration, vol. 212, no. 5, pp. 875-887, 1998 https://doi.org/10.1006/jsvi.1997.1484
  10. A. Rubaai, R. Kotaru, "Online identification and control of a dc motor using learning adaptation of neural networks," IEEE Trans. on Industry Applications, vol. 36, no. 3, pp. 935-942, 2000 https://doi.org/10.1109/28.845075