RSAS-FxLMS: A Robust Active Noise Control Method for Vibrator Operation Noise in Precast Beam Plants

To improve active noise control of 120–180 Hz vibrator noise in precast beam plants under strong impulsive disturbances, this paper proposes a robust scaled adaptive step-size filtered-x least mean square (RSAS-FxLMS) algorithm. The conventional scaled adaptive step-size filtered-x least mean square (SAS-FxLMS) algorithm is prone to weight instability and divergence under strong impacts. The proposed method embeds a dual stabilization mechanism: an adaptive divergence detector based on short-term error energy triggers weight vector reset and step-size rollback, while a norm constraint is imposed on the weight vector after each iteration. The signal preprocessing chain is optimized using a high-order bandpass filter and an offline secondary path model identified with swept-frequency excitation and a weighted-error criterion. Simulations using field-measured vibrator noise show that the proposed algorithm achieves a noise reduction of 33.3 dB at 150 Hz, which is 27.63 dB higher than that of the conventional SAS-FxLMS algorithm, and an average noise reduction of 29.10 dB across the 120–180 Hz target band, which is 20.91 dB higher than that of the conventional SAS-FxLMS algorithm. Under continuous high-intensity impacts, the weight vector remains bounded, and the error signal re-converges quickly without divergence. The algorithm also achieves faster convergence in more than 80% of the convergence period. These results demonstrate that the proposed method effectively suppresses strong impulsive narrowband vibrator noise with high reduction depth and strong robustness. The evaluation uses field-recorded vibrator noise as the input, whereas the primary and secondary acoustic paths are modelled; it is therefore an open-loop, offline assessment and does not constitute a closed-loop or real-time experimental validation of an ANC system, so that the results provide an algorithmic reference for industrial ANC rather than a demonstration of field performance.