TY - GEN
T1 - A Fast Bayesian High-Resolution Localization Method for Rotating Blade Noise
AU - Hu, Keyu
AU - Chu, Ning
AU - Yu, Liang
AU - Yang, Weihua
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The high-resolution blade noise identification problem of axial fans is studied based on the Modal Composition Beamforming (MCB) method in this paper. To simulate blade defects, a vortex generator (VG) is put on the fan blade. Concomitatively, Phase Average Beamforming (PA-BF) and Rotating Source Identifier (ROSI) methods are also applied to process experimental signals to compare and analyze the sound source identification performance of the MCB method. In addition, Subspace Variational Bayesian (SVB) method is integrated into the above three rotating sound source localization methods, and the resolution of the localization results is significantly improved, and the performance of high-resolution localization methods based on MCB is further discussed. According to the location results of MCB-SVB, the blade noise mechanism of the five-blade axial fan used in the experiment is analyzed, and the suggestion of noise reduction is given. This study not only discusses how the MCB-SVB method is used to reduce fan blade noise, but it also illustrates the potential for using this method to identify axial fan faults.
AB - The high-resolution blade noise identification problem of axial fans is studied based on the Modal Composition Beamforming (MCB) method in this paper. To simulate blade defects, a vortex generator (VG) is put on the fan blade. Concomitatively, Phase Average Beamforming (PA-BF) and Rotating Source Identifier (ROSI) methods are also applied to process experimental signals to compare and analyze the sound source identification performance of the MCB method. In addition, Subspace Variational Bayesian (SVB) method is integrated into the above three rotating sound source localization methods, and the resolution of the localization results is significantly improved, and the performance of high-resolution localization methods based on MCB is further discussed. According to the location results of MCB-SVB, the blade noise mechanism of the five-blade axial fan used in the experiment is analyzed, and the suggestion of noise reduction is given. This study not only discusses how the MCB-SVB method is used to reduce fan blade noise, but it also illustrates the potential for using this method to identify axial fan faults.
KW - High-resolution axial-fan blade noise localization
KW - Modal composition beamforming
KW - Phase-averaged beamforming
KW - Rotating Source Identifier
KW - Subspace Variational Bayesian method
UR - http://www.scopus.com/inward/record.url?scp=85184810353&partnerID=8YFLogxK
U2 - 10.1109/ICICSP59554.2023.10390549
DO - 10.1109/ICICSP59554.2023.10390549
M3 - 会议稿件
AN - SCOPUS:85184810353
T3 - 2023 6th International Conference on Information Communication and Signal Processing, ICICSP 2023
SP - 927
EP - 931
BT - 2023 6th International Conference on Information Communication and Signal Processing, ICICSP 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th International Conference on Information Communication and Signal Processing, ICICSP 2023
Y2 - 23 September 2023 through 25 September 2023
ER -