Improved active noise control algorithm based on the convex combination method

Noise can be harmful in certain situations, which leads to the need of controlling it. In general, a particular method of active noise control basically consists of creating a destructive overlap between noise and a reference signal (both with the same frequency and amplitude but with an opposite ph...

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Vydáno v:Journal of the Brazilian Society of Mechanical Sciences and Engineering Ročník 43; číslo 3
Hlavní autoři: Félix, Fernando Basílio, de Castro Magalhães, Max, de Souza Papini, Guilherme
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2021
Springer Nature B.V
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ISSN:1678-5878, 1806-3691
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Abstract Noise can be harmful in certain situations, which leads to the need of controlling it. In general, a particular method of active noise control basically consists of creating a destructive overlap between noise and a reference signal (both with the same frequency and amplitude but with an opposite phase). Different algorithms can be used for this purpose, each of them having distinct features, like convergence, velocity, and steady state attenuation level. The convex combination method for active noise control (C-ANC) has been used successfully as it combines different characteristics of most algorithms found in literature. This method combines two distinct active noise control algorithms into a single one. For instance, it can use algorithms such as FXLMF, which has good attenuation velocity, and the FXLMS algorithm, which has a significant attenuation level. This work proposes a modified convex combination algorithm, named MC-FXLMS-F, in order to maximize the overall attenuation level. Modification of the convex combination method was implemented using the FXLMS-F algorithm. The new proposed algorithm was compared to others found in literature, such as the FXLMS, FXLMS-F, and C-FXLMS-F algorithms. The modified convex combination algorithm (MC-FXLMS-F) showed improvement in both convergence speed and attenuation level. It achieved the best performance among the most popular existing algorithms.
AbstractList Noise can be harmful in certain situations, which leads to the need of controlling it. In general, a particular method of active noise control basically consists of creating a destructive overlap between noise and a reference signal (both with the same frequency and amplitude but with an opposite phase). Different algorithms can be used for this purpose, each of them having distinct features, like convergence, velocity, and steady state attenuation level. The convex combination method for active noise control (C-ANC) has been used successfully as it combines different characteristics of most algorithms found in literature. This method combines two distinct active noise control algorithms into a single one. For instance, it can use algorithms such as FXLMF, which has good attenuation velocity, and the FXLMS algorithm, which has a significant attenuation level. This work proposes a modified convex combination algorithm, named MC-FXLMS-F, in order to maximize the overall attenuation level. Modification of the convex combination method was implemented using the FXLMS-F algorithm. The new proposed algorithm was compared to others found in literature, such as the FXLMS, FXLMS-F, and C-FXLMS-F algorithms. The modified convex combination algorithm (MC-FXLMS-F) showed improvement in both convergence speed and attenuation level. It achieved the best performance among the most popular existing algorithms.
ArticleNumber 163
Author Félix, Fernando Basílio
de Castro Magalhães, Max
de Souza Papini, Guilherme
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Active noise control
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Snippet Noise can be harmful in certain situations, which leads to the need of controlling it. In general, a particular method of active noise control basically...
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SubjectTerms Active noise control
Algorithms
Attenuation
Control algorithms
Control theory
Convergence
Engineering
Mechanical Engineering
Noise control
Reference signals
Technical Paper
Title Improved active noise control algorithm based on the convex combination method
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