Analysis and Experiment of the Compressive Sensing Approach for Duct Mode Detection

This paper describes a new mode detection method based on the compressive sensing approach, which has been developed in information technology to reduce samples required by the classical Nyquist–Shannon sampling theory. A revised approach is proposed here to detect azimuthal spinning modes from aeroengine fan noise by using a microphone array outside the bypass duct. A number of numerical simulations is prepared to examine the associated test performance, such as the reconstruction accuracy, robustness, background noise interference, and coherence impact. The mode sparsity is usually much smaller than the highest order of the modes, so the azimuthal mode is sparse at the frequency of interest to ensure a satisfactory compressive sensing-based mode detection. The current simulations show log sensors shall be generally sufficient rather than sensors required by the Shannon–Nyquist sampling theory. An experimental system is designed and implemented to demonstrate the proposed method. The test system contains a straightened and rigid duct with an enclosed spinning mode synthesizer to emulate fan noise propagation inside and scattering from a bypass duct. An outer sensor array is employed to demonstrate that the compressive sensing-based mode detection method can significantly reduce the required number of sensors, especially for modes of high order, which results in a much simplified sensor array design for aerospace noise tests.