Active noise control based on the momentum multichannel normalized filtered-x least mean square algorithm
Multichannel active noise control (MCANC) is widely utilized to achieve significant noise cancellation area in the complicated acoustic field. Meanwhile, the filter-x least mean square (FxLMS) algorithm gradually becomes the benchmark solution for the implementation of MCANC due to its low computati...
Saved in:
Main Authors: | , , , , |
---|---|
Other Authors: | |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/169436 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-169436 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-1694362023-08-18T15:39:15Z Active noise control based on the momentum multichannel normalized filtered-x least mean square algorithm Shi, Dongyuan Gan, Woon-Seng Lam, Bhan Wen, Shulin Shen, Xiaoyi School of Electrical and Electronic Engineering 49th International Congress and Exposition on Noise Control Engineering (INTERNOISE 2020) Science::Physics::Acoustics Noise Control Filtered-X LMS (FXLMS) Algorithms Multichannel active noise control (MCANC) is widely utilized to achieve significant noise cancellation area in the complicated acoustic field. Meanwhile, the filter-x least mean square (FxLMS) algorithm gradually becomes the benchmark solution for the implementation of MCANC due to its low computational complexity. However, its slow convergence speed more or less undermines the performance of dealing with quickly varying disturbances, such as piling noise. Furthermore, the noise power variation also deteriorates the robustness of the algorithm when it adopts the fixed step size. To solve these issues, we integrated the normalized multichannel FxLMS with the momentum method, which hence, effectively avoids the interference of the primary noise power and accelerates the convergence of the algorithm. To validate its effectiveness, we deployed this algorithm in a multichannel noise control window to control the real machine noise. Ministry of National Development (MND) National Research Foundation (NRF) Submitted/Accepted version This research is supported by the Singapore Ministry of National Development and the National Research Foundation, Prime Minister’s O ce under the Cities of Tomorrow (CoT) Research Programme (CoT Award No. COT-V4-2019-1). 2023-08-16T03:00:48Z 2023-08-16T03:00:48Z 2020 Conference Paper Shi, D., Gan, W., Lam, B., Wen, S. & Shen, X. (2020). Active noise control based on the momentum multichannel normalized filtered-x least mean square algorithm. 49th International Congress and Exposition on Noise Control Engineering (INTERNOISE 2020). https://hdl.handle.net/10356/169436 en COT-V4-2019-1 © 2020 Korean Society for Noise & Vibration Engineering (KSNVE). All rights reserved. This paper was published in Proceedings of 49th International Congress and Exposition on Noise Control Engineering (INTERNOISE 2020) and is made available with permission of Korean Society for Noise & Vibration Engineering (KSNVE). application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
Science::Physics::Acoustics Noise Control Filtered-X LMS (FXLMS) Algorithms |
spellingShingle |
Science::Physics::Acoustics Noise Control Filtered-X LMS (FXLMS) Algorithms Shi, Dongyuan Gan, Woon-Seng Lam, Bhan Wen, Shulin Shen, Xiaoyi Active noise control based on the momentum multichannel normalized filtered-x least mean square algorithm |
description |
Multichannel active noise control (MCANC) is widely utilized to achieve significant noise cancellation area in the complicated acoustic field. Meanwhile, the filter-x least mean square (FxLMS) algorithm gradually becomes the benchmark solution for the implementation of MCANC due to its low computational complexity. However, its slow convergence speed more or less undermines the performance of dealing with quickly varying disturbances, such as piling noise. Furthermore, the noise power variation also deteriorates the robustness of the algorithm when it adopts the fixed step size. To solve these issues, we integrated the normalized multichannel FxLMS with the momentum method, which hence, effectively avoids the interference of the primary noise power and accelerates the convergence of the algorithm. To validate its effectiveness, we deployed this algorithm in a multichannel noise control window to control the real machine noise. |
author2 |
School of Electrical and Electronic Engineering |
author_facet |
School of Electrical and Electronic Engineering Shi, Dongyuan Gan, Woon-Seng Lam, Bhan Wen, Shulin Shen, Xiaoyi |
format |
Conference or Workshop Item |
author |
Shi, Dongyuan Gan, Woon-Seng Lam, Bhan Wen, Shulin Shen, Xiaoyi |
author_sort |
Shi, Dongyuan |
title |
Active noise control based on the momentum multichannel normalized filtered-x least mean square algorithm |
title_short |
Active noise control based on the momentum multichannel normalized filtered-x least mean square algorithm |
title_full |
Active noise control based on the momentum multichannel normalized filtered-x least mean square algorithm |
title_fullStr |
Active noise control based on the momentum multichannel normalized filtered-x least mean square algorithm |
title_full_unstemmed |
Active noise control based on the momentum multichannel normalized filtered-x least mean square algorithm |
title_sort |
active noise control based on the momentum multichannel normalized filtered-x least mean square algorithm |
publishDate |
2023 |
url |
https://hdl.handle.net/10356/169436 |
_version_ |
1779156412826386432 |