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
基金supported by the National Natural Science Foundation of China(No.52075414)the China Postdoctoral Science Foundation(No.2021M702595)the China Scholarship Council。
文摘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.
