An improved active noise control system for construction machinery cabs under impulsive noise environments

Active Noise Control (ANC) technology offers a promising solution for reducing low-frequency noise in construction machinery cabs, where traditional passive methods prove ineffective. This paper presents a comprehensive ANC system specifically designed for hydraulic excavator cabs, addressing the challenge of impulsive noise generated during operation. First, an improved online secondary path identification method is proposed, featuring a simplified variable step-size rule and auxiliary noise scheduling strategy that achieves superior convergence and identification accuracy compared to existing Eriksson and Akhtar methods. Second, a novel ANC algorithm (NFxatanSLMS) is developed based on arctangent transformation, which effectively handles impulsive noise through a robust cost function framework and normalized step-size strategy. The algorithm parameters are optimized using Particle Swarm Optimization (PSO) to ensure optimal performance. Simulation results demonstrate that the proposed NFxatanSLMS-PSO algorithm achieves approximately 18 dB noise reduction for measured excavator cab noise and maintains stable performance under various impulsive conditions. Experimental validation conducted on an actual hydraulic excavator under three working conditions shows average noise reductions of 6.54 dB (fixed position), 6.72 dB (excavating without loading), and 2.40 dB (excavating with impact). The proposed system effectively attenuates noise in the 20–280 Hz frequency band, with peak reductions up to 12 dB, while maintaining convergence less than 1.5 seconds and robust performance under impulsive disturbances. This research provides a practical and effective solution for improving the acoustic environment in construction machinery cabs.