Rotating acoustic source localization: A power propagation forward model and its high-resolution inverse methods

Abstract

The rotating-acoustic source localization has played an important role in rotary machine fault diagnosis, engine noise reduction and propeller recognition etc. To achieve high-resolution localization of fast rotating sources, this paper proposes an improved power propagation forward model of rotating acoustic source based on the equivalent source hypothesis. Then the ill-posed inverse problem derived from the forward power model is solved robustly by proposed two sparsity-based methods: the Least Absolute Shrinkage and Select Operator for Rotating-acoustic Sources (LASSO-RS) and Least Angle Regression for Rotating-acoustic Sources (LAR-RS). The contributions of this paper are that, at one hand, the improved forward model is indeed time-invariant for the fast-rotating source owing to the time-domain de-Doppler technique; at the other hand, high-resolution acoustic maps can be obtained by proposed LASSO-RS and LAR-RS thanks to the sparsity-based regularization, even under very low signal-to-noise ratio (SNR). Moreover, the proposed LAR-RS is the data-driven method, rather than the parameter-dependent method such as the LASSO-RS with careful selection of regularization parameter. In simulations and experiments, the proposed methods can robustly localize rotating monopoles in the condition of 3000 RPM rotation speed (50 Hz), −5 dB SNR, and 2500 Hz working frequency.