TY - JOUR
T1 - High-Resolution Fast-Rotating Sound Localization Based on Modal Composition Beamforming and Bayesian Inversion
AU - Chu, Ning
AU - Hu, Keyu
AU - Yu, Liang
AU - Mohammad-Djafari, Ali
AU - Yang, Weihua
N1 - Publisher Copyright:
© 1994-2012 IEEE.
PY - 2023
Y1 - 2023
N2 - Rotating source beamforming techniques have been effective means of noise localization on rotary machines. In this letter, we derive an alternative expression for modal composition beamforming (MCB) and subsequently consider the equivalent source assumption and cyclostationarity of the constant angular-speed rotating sound source so that a rotating sound source power (RSP) propagation model is derived. By estimating a suitable solution for the RSP model using the subspace variational Bayesian (SVB) technique with sparsity and total variation (TV) priors, the validity of the RSP model was established. According to the simulation results, the proposed RSP-SVB method leads to a significantly higher resolution than the MCB method. It can localize multiple fast-rotating sound sources accurately, rapidly, and effectively in environments with strong background noise interference. Therefore, our proposed RSP-SVB can offer a reliable solution for identifying fast-rotating blade noise.
AB - Rotating source beamforming techniques have been effective means of noise localization on rotary machines. In this letter, we derive an alternative expression for modal composition beamforming (MCB) and subsequently consider the equivalent source assumption and cyclostationarity of the constant angular-speed rotating sound source so that a rotating sound source power (RSP) propagation model is derived. By estimating a suitable solution for the RSP model using the subspace variational Bayesian (SVB) technique with sparsity and total variation (TV) priors, the validity of the RSP model was established. According to the simulation results, the proposed RSP-SVB method leads to a significantly higher resolution than the MCB method. It can localize multiple fast-rotating sound sources accurately, rapidly, and effectively in environments with strong background noise interference. Therefore, our proposed RSP-SVB can offer a reliable solution for identifying fast-rotating blade noise.
KW - modal composition beamforming
KW - Rotating acoustic localization
KW - rotating sound source power propagation model
KW - subspace variational bayesian method
UR - https://www.scopus.com/pages/publications/85153385036
U2 - 10.1109/LSP.2023.3263800
DO - 10.1109/LSP.2023.3263800
M3 - 文章
AN - SCOPUS:85153385036
SN - 1070-9908
VL - 30
SP - 349
EP - 353
JO - IEEE Signal Processing Letters
JF - IEEE Signal Processing Letters
ER -