A narrowband active noise control system with a frequency estimator based on Bayesian inference

Rong Han, Ming Wu, Feng Liu, Hongling Sun, Jun Yang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

Narrowband active noise control (NANC) achieves good performance in controlling low-frequency periodic noise. Such control is necessary to obtain the frequency information of the primary periodic noise, including the number of frequency components and the individual frequency values, to generate reference signals. The performance of the NANC system mainly depends on the accuracy of frequency estimation of the primary periodic noise. In this article, a frequency estimator based on Bayesian inference that can obtain accurate frequencies as well as the number of frequency components is applied to a NANC system. Numerous computer simulations are conducted. Simulation results show that the proposed system outperforms a conventional NANC system with the adaptive notch filter (ANF) algorithm at low signal-to-noise-ratio (SNR) primary periodic noise.

Original languageEnglish
Pages (from-to)299-311
Number of pages13
JournalJournal of Sound and Vibration
Volume455
DOIs
Publication statusPublished - Sept 1 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019 Elsevier Ltd

ASJC Scopus Subject Areas

  • Condensed Matter Physics
  • Mechanics of Materials
  • Acoustics and Ultrasonics
  • Mechanical Engineering

Keywords

  • Adaptive notch filter
  • Bayesian inference
  • Frequency estimation
  • Narrowband active noise control

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