Conventional multiple-point active noise control (ANC) systems require placing error microphones within the region of interest (ROI), inconveniencing users. This paper designs a feasible monitoring microphone arrangement placed outside the ROI, providing a user with more freedom of movement. The soundfield within the ROI is interpolated from the microphone signals using a physics-informed neural network (PINN). PINN exploits the acoustic wave equation to assist soundfield interpolation under a limited number of monitoring microphones, and demonstrates better interpolation performance than the spherical harmonic method in simulations. An ANC system is designed to take advantage of the interpolated signal to reduce noise signal within the ROI. The PINN-assisted ANC system reduces noise more than that of the multiple-point ANC system in simulations.

翻译：传统多点主动噪声控制（ANC）系统需在感兴趣区域（ROI）内布置误差麦克风，给用户带来不便。本文设计了一种可行的监测麦克风布置方案，将其置于ROI外部，从而为用户提供更大的活动自由度。通过采用物理信息神经网络（PINN），利用麦克风信号对ROI内声场进行插值。PINN利用声波方程，在有限的监测麦克风数量下辅助声场插值，并在仿真中展现出比球谐函数方法更优的插值性能。我们设计了一个ANC系统，利用插值信号来降低ROI内的噪声信号。仿真结果表明，与多点ANC系统相比，PINN辅助的ANC系统具有更强的降噪效果。