Active control of outgoing noise fields in rooms

Ma, Fei; Zhang, Wen; Abhayapala, Thushara D.

doi:10.1121/1.5055217

Cited by 8 publications

(2 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The effectiveness of the frequency-domain SFS method based on the spherical wave expansion has been validated by both simulations and experiments. 3,4,21 The outgoing field separated by the frequency-domain method reveals the characteristics of the target source. However, the frequency-domain method is based on the Short Time Fourier Transform to transfer the time-domain acoustic quantities into the time-frequency domain.…”

Section: A Problem Formulationmentioning

confidence: 99%

Real-time separation of non-stationary sound fields on spheres

Zhang

Abhayapala

2019

The Journal of the Acoustical Society of America

Self Cite

View full text Add to dashboard Cite

1 Sound field separation The sound field separation methods can separate the target field from the interfering noises, facilitating the study of the acoustic characteristics of the target source, which is placed in a noisy environment. However, most of the existing sound field separation methods are derived in the frequency-domain, thus are best suited for separating stationary sound fields. In this paper, a time-domain sound field separation method is developed that can separate the non-stationary sound field generated by the target source over a sphere in real-time. A spherical array sets up a boundary between the target source and the interfering sources, such that the outgoing field on the array is only generated by the target source. The proposed method decomposes the pressure and the radial particle velocity measured by the array into spherical harmonics coefficients, and recoveries the target outgoing field based on the time-domain relationship between the decomposition coefficients and the theoretically derived spatial filter responses. Simulations show the proposed method can separate non-stationary sound fields both in free field and room environments, and over a longer duration with small errors. The proposed method could serve as a foundation for developing future time-domain spatial sound field manipulation algorithms.

show abstract

Section: A Problem Formulationmentioning

confidence: 99%

Real-time separation of non-stationary sound fields on spheres

Zhang

Abhayapala

2019

The Journal of the Acoustical Society of America

Self Cite

View full text Add to dashboard Cite

show abstract

“…The SH decomposition of a sound field (the angular dependent SHs, the radial dependent spherical Bessel functions, and the frequency dependent sound field coefficients) greatly facilitates its analysis and manipulation [1][2][3]. Thus, spherical modal decomposition has become popular in many diverse spatial acoustic applications, such as spatial active noise control [4][5][6], beamforming [3,7,8], and direction of arrival estimation [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Circumvent spherical Bessel function nulls for open sphere microphone arrays with physics informed neural network

Ma,

Abhayapala,

Samarasinghe

2022

Proceedings of the 10th Convention of the European Acoustics Association Forum Acusticum 2023

View full text Add to dashboard Cite

Open sphere microphone arrays (OSMAs) are simple to design and do not introduce scattering fields, and thus can be advantageous than other arrays for implementing spatial acoustic algorithms under spherical model decomposition. However, an OSMA suffers from spherical Bessel function nulls which make it hard to obtain some sound field coefficients at certain frequencies. This paper proposes to assist an OSMA for sound field analysis with physics informed neural network (PINN). A PINN models the measurement of an OSMA and predicts the sound field on another sphere whose radius is different from that of the OSMA. Thanks to the fact that spherical Bessel function nulls vary with radius, the sound field coefficients which are hard to obtain based on the OSMA measurement directly can be obtained based on the prediction. Simulations confirm the effectiveness of this approach and compare it with the rigid sphere approach.

show abstract