Aero-engine Fan Acoustic Mode Detections via Orthogonal Matching Pursuit

Abstract

Azimuthal mode analysis (AMA) is one of the most commonly used approaches for comprehending the characteristics of the noise emitted from the aero-engine fans. This paper proposed a new azimuthal mode detection method based on compressive sensing, which breaks through the limitations of the Shannon-Nyquist sampling theorem and extends the range of mode detection. A $\ell_{0}$ -norm regularized AMA method is proposed to reconstruct the spectrum of the tonal modes of aero-engine fans. Notably, the orthogonal matching pursuit (OMP) algorithm is implemented to effectively ameliorate the solution of the $\ell_{0}$ -norm regularized problem. The feasibility of the proposed approach is verified by a series of simulations, of which the configurations are consistent with a practical case. Meanwhile, the performance of the $\ell_{1}$ -norm regularized AMA method is compared with the proposed approach. The simulation results indicated that the $\ell_{0}$ -norm regularized approach enhanced the sparsity of the estimations of the tonal noise mode spectrum. The stability and the robustness of the reconstruction results are notably improved, which leads to a higher accuracy of the amplitudes of the tonal acoustic modes and a noticeable reduction of the number of the microphones required by AMA.