Nonlinear aeroacoustic characterization of Helmholtz resonators with a local-linear neuro-fuzzy network model

K. Förner, W. Polifke

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

The nonlinear acoustic behavior of Helmholtz resonators is characterized by a data-based reduced-order model, which is obtained by a combination of high-resolution CFD simulation and system identification. It is shown that even in the nonlinear regime, a linear model is capable of describing the reflection behavior at a particular amplitude with quantitative accuracy. This observation motivates to choose a local-linear model structure for this study, which consists of a network of parallel linear submodels. A so-called fuzzy-neuron layer distributes the input signal over the linear submodels, depending on the root mean square of the particle velocity at the resonator surface. The resulting model structure is referred to as an local-linear neuro-fuzzy network. System identification techniques are used to estimate the free parameters of this model from training data. The training data are generated by CFD simulations of the resonator, with persistent acoustic excitation over a wide range of frequencies and sound pressure levels. The estimated nonlinear, reduced-order models show good agreement with CFD and experimental data over a wide range of amplitudes for several test cases.

Original languageEnglish
Pages (from-to)170-190
Number of pages21
JournalJournal of Sound and Vibration
Volume407
DOIs
StatePublished - 27 Oct 2017

Keywords

  • Acoustic liner
  • CFD/SI
  • Helmholtz resonator
  • Impedance
  • Nonlinear acoustics
  • Nonlinear system identification

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