Detail publikace

ITERATIVE NEAR FIELD ACOUSTICAL HOLOGRAPHY ALGORITHM

Originální název

ITERATIVE NEAR FIELD ACOUSTICAL HOLOGRAPHY ALGORITHM

Anglický název

ITERATIVE NEAR FIELD ACOUSTICAL HOLOGRAPHY ALGORITHM

Jazyk

en

Originální abstrakt

This paper deals with the description, optimization and simulation of the Iterative Near Field Acoustical Holography (NAH) algorithm. Using NAH technique it is possible to calculate the 3D sound field from in plane measured sound pressure field. Even more it is possible to calculate other quantities in 3D space like particle velocity, sound intensity and radiated sound power. Conventional NAH algorithm uses back propagating of the sound field spatial spectra toward the sound source using inverse Green´s function and K-space filter technique. A disadvantage of this technique is that also unwanted measurement noise with high spatial frequencies is strongly amplified and decreases a precision of the sound field estimation. Iterative NAH algorithm uses the forward propagating technique and eliminates the unwanted measurement noise amplification. Sound field is propagated to the hologram plane, compared with the measured data and the difference is multiplied with feedback operator (Wiener filter) and subtracted from the initial guess. Two critical parameters (initial guess and number of iterations) are discussed in this paper and results are compared with the conventional NAH algorithm. The obtained parameters and the accuracy of the Iterative NAH algorithm show better results than results obtained by conventional NAH algorithm with K-space filter.

Anglický abstrakt

This paper deals with the description, optimization and simulation of the Iterative Near Field Acoustical Holography (NAH) algorithm. Using NAH technique it is possible to calculate the 3D sound field from in plane measured sound pressure field. Even more it is possible to calculate other quantities in 3D space like particle velocity, sound intensity and radiated sound power. Conventional NAH algorithm uses back propagating of the sound field spatial spectra toward the sound source using inverse Green´s function and K-space filter technique. A disadvantage of this technique is that also unwanted measurement noise with high spatial frequencies is strongly amplified and decreases a precision of the sound field estimation. Iterative NAH algorithm uses the forward propagating technique and eliminates the unwanted measurement noise amplification. Sound field is propagated to the hologram plane, compared with the measured data and the difference is multiplied with feedback operator (Wiener filter) and subtracted from the initial guess. Two critical parameters (initial guess and number of iterations) are discussed in this paper and results are compared with the conventional NAH algorithm. The obtained parameters and the accuracy of the Iterative NAH algorithm show better results than results obtained by conventional NAH algorithm with K-space filter.

BibTex


@inproceedings{BUT7721,
  author="Petr {Grätz}",
  title="ITERATIVE NEAR FIELD ACOUSTICAL HOLOGRAPHY ALGORITHM",
  annote="This paper deals with the description, optimization and simulation of the Iterative Near Field Acoustical Holography (NAH) algorithm. 
Using NAH technique it is possible to calculate the 3D sound field from in plane measured sound pressure field. Even more it is possible to calculate other quantities in 3D space like particle velocity, sound intensity and radiated sound power. 
Conventional NAH algorithm uses back propagating of the sound field spatial spectra toward the sound source using inverse Green´s function and K-space filter technique. A disadvantage of this technique is that also unwanted measurement noise with high spatial frequencies is strongly amplified and decreases a precision of the sound field estimation.
Iterative NAH algorithm uses the forward propagating technique and eliminates the unwanted measurement noise amplification. Sound field is propagated to the hologram plane, compared with the measured data and the difference is multiplied with feedback operator (Wiener filter) and subtracted from the initial guess. Two critical parameters (initial guess and number of iterations) are discussed in this paper and results are compared with the conventional NAH algorithm.
The obtained parameters and the accuracy of the Iterative NAH algorithm show better results than results obtained by conventional NAH algorithm with K-space filter.
",
  address="TU Kosice",
  booktitle="The 4th International Carphatian Control Conference ICCC 2003",
  chapter="7721",
  institution="TU Kosice",
  year="2003",
  month="may",
  pages="10",
  publisher="TU Kosice",
  type="conference paper"
}