A-weighted convex combination step-size based active impulsive noise control for construction vehicle noise reduction

Abstract

Construction vehicles generate significant cabin noise, which includes both consistent and impulsive noise from engines and components. The noise imposes hearing loss threats to the operators during long operation hours. Active reduction is required for efficient impulsive noise minimization. Traditional approaches such as the filtered-x least mean square (FxLMS) algorithm, often prove inadequate in effectively controlling these impulsive noises, due to non-Gaussian characteristics. Robust algorithms for active impulsive noise control (AINC) systems are required for applications to construction equipment. The convex combined step-size (CCSS) based variable step-size (VSS) along with integrating the normalized least mean square (NLMS) into a modified FxLMS (MFxLMS) with an adaptive step-size update algorithm is used for reduction of the vehicle interior noise. The A-weighted filtering enhanced the noise reduction efficiency by incorporating human auditory characteristics. This filtering also minimized unnecessary control loadings at low frequency noise components. The performance of the proposed algorithm was evaluated through experiments conducted using a portion of the actual excavator cabin. The results demonstrated robust and excellent noise reduction performance against unexpected impulsive sounds.