Development of an Active Road Noise Control System

Oh, Chi Sung; Ih, Kang-Duck; Lee, Hae Min; Jeon, Jin Su

doi:10.1007/s38311-015-0151-5

Cited by 5 publications

(1 citation statement)

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“…( 2) The adaptive filter uses the reference signal X(n) and the error signal e(n) to update the filter weight W(n), according to Equation ( 13). ( 3) The updated filter weight is used to generate a new output signal y(n), and at the start of the next time step, steps 1 and 2 are repeated [55,56]. Using continuous adaptive updates, we can effectively reduce the noise.…”

Section: Active Noise Control System Algorithmmentioning

confidence: 99%

Development and Testing of an Active Noise Control System for Urban Road Traffic Noise

Yang,

Yin,

et al. 2023

Applied Sciences

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As urbanization accelerates, the increasing number of vehicles and travel demands contribute to escalating road traffic noise pollution. Although passive noise control techniques such as noise barriers and green belts effectively mitigate noise, they occupy urban space, exacerbating the scarcity and high cost of already congested city areas. Emerging as a novel noise reduction strategy, active noise control (ANC) eliminates the need for physical isolation structures and addresses the noise within specific frequency ranges more effectively. This paper investigates the characteristics of urban road traffic noise and develops an ANC prototype. Utilizing the Least Mean Squares (LMS) algorithm, we conduct active noise control tests for various types of single- and dual-frequency noise within the prototype’s universal platform to validate its actual noise reduction capabilities. The study demonstrates that urban road traffic noise is mostly in the mid- to low-frequency range (below 2000 Hz). The developed ANC prototype significantly reduces single- or dual-frequency noise within this range, achieving a maximum noise reduction of nearly 30 dB(A). Future research should expand noise reduction tests across more frequency bands and assess the noise reduction effectiveness against real road traffic noise.

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Section: Active Noise Control System Algorithmmentioning

confidence: 99%