A nonlinear active noise control algorithm using the FEWT and channel-reduced recursive Chebyshev filter. (1st March 2022) - Chen, Bin; Guo, Rongrong; Zeng, Kailin
Highlights: A novel NANC system based on FEWT and recursive third-order Chebyshev expansion is proposed. The FEWT with order-statistic filtering is applied to stabilize non-stationary noise. A RTOCN filter is presented for compensating the higher-order nonlinear distortions. The channel-reduced diagonal structure is designed to optimize the RTOCN filter. Experiment results indicate that proposed method outperforms conventional methods. Abstract: Active noise control (ANC) has been widely studied to eliminate low-frequency noise. However, efficiently controlling higher-order distortions of nonlinear primary and secondary path is still a major challenge. To address this, this paper proposes a novel nonlinear ANC algorithm based on the fast empirical wavelet transform and recursive Chebyshev nonlinear filter. In this method, the fast empirical wavelet transform based on order-statistic filtering is first applied to decompose non-stationary noise into empirical mode functions (EMFs) which are more stationary and easy to control. Furthermore, a novel third-order Chebyshev nonlinear filter including the non-recursive subsection and recursive one is proposed to individually expand EMFs for compensating higher-order nonlinear distortions from primary path and secondary path. Moreover, the strategy of channel-reduced diagonal structure is designed to optimise the number of expanded channels, and the computational complexity of proposed algorithm is also investigated. Experimental results demonstrate that proposed method performs the highest noise reduction over the conventional algorithms but also has a fast convergence rate.