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Time analysis for aero-engine acoustic modes exploiting block sparsity
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作者 Zepeng LI Baijie QIAO +3 位作者 Bi WEN Yuanshi LIU Xuefeng CHEN andreas jakobsson 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2024年第11期254-264,共11页
Acoustic Mode Analysis(AMA)for aero-engines can offer valuable insights for the design of silent engines as well as for fault diagnosis.Commonly,this is done in the(spatial)Fourier domain,necessitating the use of mult... Acoustic Mode Analysis(AMA)for aero-engines can offer valuable insights for the design of silent engines as well as for fault diagnosis.Commonly,this is done in the(spatial)Fourier domain,necessitating the use of multiple uniformly spaced microphones to ensure adequate resolution.Recent works show that sub-Nyquist estimation is feasible using sparse reconstruction frameworks,although such modelling generally introduces an estimation bias that has to be compensated for.Moreover,there is a growing interest in monitoring mode amplitude over continuous time,as it can offer crucial insights for diagnosing operational conditions.In this work,we introduce a Block Orthogonal Matching Pursuit(BOMP)method for continuous time mode analysis,exploiting the underlying structural sparsity of the signal model.Specifically,the(pseudo)‘0ànorm penalty is employed to induce sparsity in the wavenumber domain,whereas a block structure is imposed as a constraint to monitor the amplitude variation in the time domain.The effectiveness of the BOMP is evaluated using both numerical simulations and experimental measurements,indicating the proposed method's preferable performance as compared to the classic Least Absolute Shrinkage and Selection Operator(LASSO)and Orthogonal Matching Pursuit(OMP)methods. 展开更多
关键词 Block sparsity Orthogonal matching pursuit Acoustic mode analysis Acoustic testing Sparse estimate
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