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Active Noise Reduction Algorithm Based on NOTCH Filter and Genetic Algorithm

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Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Application of active noise reduction (ANR) systems in hearing protectors requires the use of control algorithms to ensure stability of the ANR system and at the same time highly effective active noise reduction. A control algorithm based on NOTCH filters is an example of solutions that meet these criteria. Their disadvantage is operation over a narrow frequency band and a need for prior determination of frequencies to be reduced. This paper presents a solution of the ANR system for hearing protectors which is controlled with the use of modified NOTCH filters with parameters determined by a genetic algorithm. Application of a genetic algorithm allows to change the NOTCH filter reference signal frequency, and thus, adapt the filter to the reduced signal frequency.
Słowa kluczowe
Rocznik
Strony
185--190
Opis fizyczny
Bibliogr. 16 poz., wykr.
Twórcy
autor
  • Central Institute for Labour Protection – National Research Institute Czerniakowska 16, 00-701 Warszawa, Poland
  • Central Institute for Labour Protection – National Research Institute Czerniakowska 16, 00-701 Warszawa, Poland
Bibliografia
  • 1. Bismor D. (2012), LMS Algorithm Step Size Adjustment for Fast Convergence, Archives of Acoustics, 37, 1, 31-40.
  • 2. Canetto P. (2009), Hearing Protectors: Topicality and Research Needs, JOSE, 15, 2, 141-153.
  • 3. Engel Z., Koradecka D., Augustyńska D., Kowalski P., Morzyński L., Żera J. (2010), Vibroa- coustic hazards, [in:] Handbook of Occupational Safety and Health, Koradecka D. [Ed.], pp. 153-198, CRC Press, Boca Raton.
  • 4. Goldberg D. (1989), Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, Mass, USA.
  • 5. Gwiazda T.D. (2007), Genetic algorithms reference Volume I and II, Polish Scientific Publishers PWN, Warszawa.
  • 6. Górski P., Morzyński L. (2012), The control algorithm with NOTCH filter and genetic algorithm, 59th Open Seminar on Acoustics, Poznań - Boszkowo, Poland.
  • 7. Kotarbińska E., Kozłowski E. (2009), Measurement of Effective Noise Exposure of Workers Wearing Ear-Muffs, JOSE, 15, 2, 193-200.
  • 8. Krukowicz T. (2010), Active Noise Control Algorithm Based on a Neural Network and Nonlinear InputOutput System Identification Model, Archives of Acoustics, 35, 2, 191-202.
  • 9. Makarewicz G. (2007), Application of genetic algorithm an active noise control system, Archives of Acoustics, 32, 4, 839-849.
  • 10. Mejia J., Dillon H., Fisher M. (2008), Active cancellation of occlusion: An electronic vent for hearing aids and hearing protectors, JASA, 124, 1.
  • 11. Mojiri M., Bakhshai A.R. (2004), An adaptive notch filter for frequency estimation of a periodic signal, IEEE Trans.on Automatic Control, 49, 2, 314-318.
  • 12. Morzynski L. Makarewicz G. (2003), Application of neural networks in Active Noise Reduction Systems, JOSE, 9, 3, 257-270.
  • 13. Oinonen M., Raittinen H., Kivikoski M. (2006), Development of an active noise cancellation hearing protector: how can passive attenuation be retained?, NVI, 20, 3.
  • 14. Pawelczyk M. (2004), Adaptive noise control algorithms for active headrest system, Control Engineering Practice, 12, 9.
  • 15. Pawelczyk M., Latos M. (2010), Earplug actuator selection for a miniature personal active hearing protection system, Archives of Acoustics, 35, 2, 213-222.
  • 16. Prashanth M.K.V. (2010), Design of a headset prototype for speech detection and noise reduction, 17th International Congress on Sound and Vibration (ICSV17), Cairo, Egypt.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2c844111-3707-4eda-8907-96ee2c0193b9
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