Applying the remote microphone method in the filtered error least mean squares algorithm
Applying the remote microphone method in the filtered error least mean squares algorithm
An active noise control (ANC) system generates an anti-noise wave to reduce the noise level at a control point, where the error microphone is conventionally placed. Virtual sensing techniques are developed for situations when the error microphone cannot be permanently placed at the control point. The remote microphone (RM) method is one of the most straightforward virtual sensing methods. Previous studies have demonstrated that the performance of the RM method is influenced by the causality between the physical and virtual error microphones, which can be resolved by introducing a delayed version of the virtual error signal. So far, the RM method has mainly been examined with the filtered reference least mean squares (FxLMS) algorithm. This paper applies the RM method in the filtered error least mean squares (FeLMS) algorithm. The FeLMS algorithm introduces an adjoint filter to reduce the computational complexity of the ANC system. The delay incurred by the adjoint filter is just right to implement the delayed virtual error signal of the RM method.
Institute of Noise Control Engineering of the USA
Fu, Yujie
a2f9277a-2ff3-44b0-9541-754cbbd7a7c9
Liu, Chunyu
097fd8ad-2b0a-4659-a3db-ede482189a8b
Shi, Chuang
c46f72bd-54c7-45ee-ac5d-285691fccf81
1 February 2023
Fu, Yujie
a2f9277a-2ff3-44b0-9541-754cbbd7a7c9
Liu, Chunyu
097fd8ad-2b0a-4659-a3db-ede482189a8b
Shi, Chuang
c46f72bd-54c7-45ee-ac5d-285691fccf81
Fu, Yujie, Liu, Chunyu and Shi, Chuang
(2023)
Applying the remote microphone method in the filtered error least mean squares algorithm.
In INTER-NOISE and NOISE-CON Congress and Conference Proceedings.
Institute of Noise Control Engineering of the USA.
8 pp
.
(doi:10.3397/IN_2022_0470).
Record type:
Conference or Workshop Item
(Paper)
Abstract
An active noise control (ANC) system generates an anti-noise wave to reduce the noise level at a control point, where the error microphone is conventionally placed. Virtual sensing techniques are developed for situations when the error microphone cannot be permanently placed at the control point. The remote microphone (RM) method is one of the most straightforward virtual sensing methods. Previous studies have demonstrated that the performance of the RM method is influenced by the causality between the physical and virtual error microphones, which can be resolved by introducing a delayed version of the virtual error signal. So far, the RM method has mainly been examined with the filtered reference least mean squares (FxLMS) algorithm. This paper applies the RM method in the filtered error least mean squares (FeLMS) algorithm. The FeLMS algorithm introduces an adjoint filter to reduce the computational complexity of the ANC system. The delay incurred by the adjoint filter is just right to implement the delayed virtual error signal of the RM method.
Text
Noise22_Fu_Submission
- Accepted Manuscript
More information
Published date: 1 February 2023
Venue - Dates:
The 51st International Congress and Exposition on Noise Control Engineering: Internoise 2022, Scottish Event Campus (SEC), Glasgow, United Kingdom, 2022-08-21 - 2022-08-24
Identifiers
Local EPrints ID: 484109
URI: http://eprints.soton.ac.uk/id/eprint/484109
ISSN: 0736-2935
PURE UUID: 06414254-0c40-405a-ae29-d5bcd5e8897d
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Date deposited: 10 Nov 2023 17:52
Last modified: 18 Mar 2024 04:13
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Author:
Yujie Fu
Author:
Chunyu Liu
Author:
Chuang Shi
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