Sound Quality Control Based on CEEMD Blind Source Separation and FELMS Algorithm

Abstract

The reduction in sound pressure level is the focus of noise reduction in construction machinery, but the sound quality parameters can better describe the operator’s subjective perception of noise. This paper proposes a sound quality control method for the cab, which is based on complementary ensemble empirical mode decomposition for signal decomposition and reconstruction and an adaptive control algorithm error filter. Firstly, a subjective and objective prediction model was created to identify the target parameters for the sound quality control in the cab. Secondly, the noise was reconstructed based on a complementary ensemble empirical mode decomposition method, thus evaluating the influence of each component on the sound quality and determining the frequency interval. Lastly, the active sound quality control was completed based on the variable step size filter-error least mean square algorithm. The experiments were performed in the cab of a mini-excavator to verify the method’s effectiveness. It was verified that the loudness peak drops by 0.95 sones under stationary idle working conditions. The results demonstrate that the above methods play a guiding role in the actual application of sound quality control for the cab of construction machinery.