273 / 2025-06-15 22:01:50

Improved MUSIC Algorithm for Abnormal Noise Localization in Indoor Multi-Flywheels Operational Environment

flywheel, abnormal noise, abnormal noise localization, MUSIC algorithm.

In an indoor environment with multiple flywheels operating simultaneously, abnormal noises from a flywheel are prone to being masked by complex background noise and superposition of multiple sound sources, making it difficult to locate an abnormal-noise flywheel accurately and in a timely manner through conventional manual detection. Aiming at this problem, this paper proposes an abnormal noise localization method based on the improved Multiple Signal Classification (MUSIC) algorithm based on wavelet packet decomposition and prior position information. Firstly, a uniform linear array is selected based on the flywheel layout. This array acquires sound signals from multiple simultaneously operating flywheels. Then, abnormal noise features are extracted via wavelet packet reconstruction. Finally, a broadband MUSIC algorithm with a priori position constraints is established to locate an abnormal-noise flywheel. Experimental results demonstrate that this method can accurately localize an abnormal-noise flywheel under underdetermined sensor scenarios and severe noise interference from multiple flywheels, presenting a practical solution for large-scale flywheel production testing.