Volume 126, Issue 3, September 2009
Index of content:
- ACOUSTIC SIGNAL PROCESSING 
126(2009); http://dx.doi.org/10.1121/1.3180132View Description Hide Description
This paper deals with a measurement technique for planar nearfield acoustic holography (NAH) applications. The idea is to use a light tensionless membrane as a normal acoustic velocitysensor, whose response is measured by using a laser vibrometer. The main technical difficulty is that the used membrane must be optically reflective but acoustically transparent. The latter condition cannot be fully satisfied because of the membrane mass, which has to be minimized to reduce acoustic reflections. A mass correction operator is proposed in this work, based on a two-dimensional discrete Fourier transform of the membrane velocity field. An academic planar NAH experiment is finally reported, illustrating qualitatively and quantitatively the feasibility of the method and the pertinence of the mass correction operator.
126(2009); http://dx.doi.org/10.1121/1.3183594View Description Hide Description
Due to excessive reverberation or to the presence of secondary noise sources, characterization of sound sources in enclosed space is rather difficult to perform. In this paper a process layer is used to recover the pressure field that the studied source would have radiated in free space. This technique requires the knowledge of both acoustic pressure and velocity fields on a closed surface surrounding the source. The calculation makes use of boundary element method and is performed in two steps. First, the outgoing pressure field is extracted from the measured data using a separation technique. Second, the incoming field then scattered by the tested source body is subtracted from the outgoing field to recover free field conditions. The studied source is a rectangular parallelepiped with seven mid-range loudspeakers mounted on it. It stands at from the rigid ground of a semi-anechoic chamber which strongly modifies the radiated pressure field, especially on the underside. After the measured data have been processed, the loudspeaker positions are recovered with a fairly good accuracy. The acoustic inverse problem is also solved to calculate the velocity field on the source surface.
Near field acoustic holography based on the equivalent source method and pressure-velocity transducers126(2009); http://dx.doi.org/10.1121/1.3179665View Description Hide Description
The advantage of using the normal component of the particle velocity rather than the sound pressure in the hologram plane as the input of conventional spatial Fourier transform based near field acoustic holography (NAH) and also as the input of the statistically optimized variant of NAH has recently been demonstrated. This paper examines whether there might be a similar advantage in using the particle velocity as the input of NAH based on the equivalent source method (ESM). Error sensitivity considerations indicate that ESM-based NAH is less sensitive to measurement errors when it is based on particle velocity input data than when it is based on measurements of sound pressure data, and this is confirmed by a simulation study and by experimental results. A method that combines pressure- and particle velocity-based reconstructions in order to distinguish between contributions to the sound field generated by sources on the two sides of the hologram plane is also examined.
126(2009); http://dx.doi.org/10.1121/1.3192349View Description Hide Description
The patch holography method allows one to make measurements on an extended structure using a small microphone array. Increased attention has been paid to the two techniques, which are quite different at first glance. One is to extrapolate the pressure field measured on the hologram plane while the other is to use statistically optimized processing. A singular value decomposition formulation of the latter is proposed in this paper. The similarity of the two techniques is shown here. Both use a convolution of the measuredpressure patch to obtain a better estimate of the wavenumber spectrum backward propagated on the structure. By using the Morozov discrepancy principle to compute the regularization parameter, the two methods lead to very close results.
126(2009); http://dx.doi.org/10.1121/1.3158934View Description Hide Description
Room-acoustic energy decay analysis of acoustically coupled-spaces within the Bayesian framework has proven valuable for architectural acoustics applications. This paper describes an efficient algorithm termed slice sampling Monte Carlo (SSMC) for room-acoustic decay parameter estimation within the Bayesian framework. This work combines the SSMC algorithm and a fast search algorithm in order to efficiently determine decay parameters, their uncertainties, and inter-relationships with a minimum amount of required user tuning and interaction. The large variations in the posterior probability density functions over multidimensional parameter spaces imply that an adaptive exploration algorithm such as SSMC can have advantages over the exiting importance sampling Monte Carlo and Metropolis–Hastings Markov Chain Monte Carlo algorithms. This paper discusses implementation of the SSMC algorithm, its initialization, and convergence using experimental data measured from acoustically coupled-spaces.