Application of Active Impulsive Noise Control (AINC) for Excavator Cabin Using Advanced Convex-Combined Normalized step size Algorithm and Verification of Robustness
Donghyeon Lee, Narae Kim, Yeonjin Jang, Yeonjin Jang, Junhong ParkConventional Active Noise Control (ANC) algorithms, such as Filtered-x least mean square (FxLMS), is not suitable for Active Impulse Noise Control (AINC). Because it lacks robustness to the impulsive sample input, it is unstable and diverges very easily. Therefore, AINC algorithm must be robust to impulse. The heavy equipment such as excavators often occur frequent impulse noise during operations. Also, in working environment of operating excavator, impulsive noise is prone to occurred by other heavy equipment. Therefore, it is necessary to examine the AINC algorithm that is suitable for excavators and its robustness. In this study, Convex Combined Step Size (CCSS), which is simulated better effects in AINC than conventional ANC algorithms, is tried to AINC of excavator. In addition, the noise reduction performance and robustness to undesirable sound were verified in the simulated experiment environment of the excavator cabin.