Multichannel active noise control (MCANC) is widely utilized to achieve significant noise cancellation area in the complicated acoustic field. Meanwhile, the filter-x least mean square (FxLMS) algorithm gradually becomes the benchmark solution for the implementation of MCANC due to its low computational complexity. However, its slow convergence speed more or less undermines the performance of dealing with quickly varying disturbances, such as piling noise. Furthermore, the noise power variation also deteriorates the robustness of the algorithm when it adopts the fixed step size. To solve these issues, we integrated the normalized multichannel FxLMS with the momentum method, which hence, effectively avoids the interference of the primary noise power and accelerates the convergence of the algorithm. To validate its effectiveness, we deployed this algorithm in a multichannel noise control window to control the real machine noise.

翻译：多通道主动噪声控制（MCANC）被广泛应用于在复杂声场中实现显著的降噪区域。同时，滤波-x最小均方（FxLMS）算法因其计算复杂度低，逐渐成为实现MCANC的基准解决方案。然而，其收敛速度较慢，或多或少削弱了处理快速变化扰动（如打桩噪声）的性能。此外，当算法采用固定步长时，噪声功率的变化也会恶化其鲁棒性。为解决这些问题，我们将归一化多通道FxLMS与动量方法相结合，从而有效避免了主噪声功率的干扰，并加速了算法的收敛。为了验证其有效性，我们在一个多通道噪声控制窗口中部署了该算法，用于控制真实的机器噪声。