Reconstruction of Aircraft Engine Noise Source using Beamforming and Compressive Sensing

A novel signal processing approach is proposed for sensor arrays to reconstruct spinning modal noise source from scattered sound wave measurements outside the jet flow downstream of an unflanged duct. The approach relies on the forward propagation model based on the Wiener-Hopf method and the key contribution is the development of the inverse acoustic scattering approach for a sensor array by combining compressive sensing and beamforming strategies in a non-classical way. In particular, the beamforming and compressive sensing methods are considered to improve the performance of the inverse reconstruction, especially in terms of array imagining resolutions and the number of sensors. Finally, numerical examples are prepared to demonstrate the performance of the proposed approach and the results show that the classical-beamforming-based method is more robust for numerical noise while the compressive-sensing-based method is more efficient. Overall, the proposed testing approach should be able to extensively expand the current acoustic array testing capability and will be especially useful for aerospace engineering applications, such as the design and evaluation of low-noise aircraft engines.