Rotating machines in industrial environments often generate fundamental-frequency noise and its harmonics, which may affect workers’ physical and mental health. This study investigates the active control of single-frequency noise in an open sound field. A multi-harmonic active noise control (ANC) algorithm based on local secondary path (LSP) equalization is adopted to reduce computational complexity. A semi-anechoic chamber test platform is built to experimentally investigate the influence of the distance between the error microphone and the secondary source (Des), as well as collinear and non-collinear arrangements, on noise-reduction level, spatial attenuation range, and the upper frequency limit of noise control. The experimental results show that, under a 100 Hz tonal noise condition, the noise-reduction level first increases and then decreases as Des increases. This phenomenon can be explained by the phase relationship between the primary and secondary sound fields. As Des changes, the propagation delay of the secondary sound field also changes, thereby altering the interference pattern at the monitoring positions. When the phase difference approaches destructive interference, higher noise reduction is achieved, whereas further increases in Des gradually reduce the cancellation effectiveness because of phase mismatch. A relatively high noise-reduction performance is maintained when Des ranges from 200 cm to 500 cm. Secondary destructive interference may also appear at certain distances. In addition, the collinear arrangement shows a significantly higher upper frequency limit for noise reduction in comparison with the non-collinear arrangement. The results provide useful experimental evidence and practical guidance for optimizing the layout of ANC systems in complex acoustic environments such as vehicles and industrial plants.

Engine noise is a predominant source of noise in the cabin of internal combustion engine vehicles and new energy hybrid vehicles. The conventional multi-channel active noise control (ANC) system, based on the adaptive notch filtered-X least mean square algorithm, is commonly employed to mitigate such multi-tonal noise. However, the computational efficiency and convergence performance of this system may be significantly hindered by the large estimated secondary path length and the frequency-dependent convergence behavior. To overcome these limitations, this paper proposes a computationally efficient and fast-converging multi-channel ANC system by incorporating a local secondary path (LSP) equalization method. The proposed method enhances the convergence speed by equalizing the magnitude responses of estimated secondary paths and reduces the computational complexity through an improved LSP modeling approach. Accordingly, a set of low-order equalized LSP models with normalized amplitude-frequency responses is generated and employed for reference filtering. A computational complexity analysis comparing the conventional system, a recent cost-effective system, and the proposed system is presented. Numerical simulations are conducted to evaluate the convergence speed and noise attenuation performance of these three systems. Additionally, real vehicle experiments are performed using a digital signal processing controller. The results demonstrate that the proposed multi-channel ANC system achieves a superior noise reduction effect. Under accelerated conditions, the average attenuation of the second-order noise component at the four error microphones is measured at 4.4 dB(A), 6.2 dB(A), 13.4 dB(A), and 10.0 dB(A). These findings confirm the practical effectiveness of the proposed multi-channel ANC system.