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.
Final Paper
Xu Li / Beihang University (Beijing University of Aeronautics and Astronautics)
Baoyu Shi / AECC Harbin Dongan Engine Co., Ltd.
Tian He / Beihang University (Beijing University of Aeronautics and Astronautics)
Hong Wang / Beijing Key Laboratory of Long-life Technology of Precise Rotation and Transmission Mechanisms
Haibing Xu / AECC Harbin Dongan Engine Co., Ltd.
Qilong Bian / Beihang University (Beijing University of Aeronautics and Astronautics)
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. To address this problem, this paper proposes an improved MUSIC-based abnormal noise localization method, integrating wavelet packet decomposition and a priori 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.
Important Date
  • Conference Date

    Aug 01

    2025

    to

    Aug 04

    2025

  • Aug 20 2025

    Draft paper submission deadline

Sponsored By
中国机械工程学会设备智能运维分会
Organized By
新疆大学