Dominant duct azimuthal acoustic mode detection considering failed wall-installed microphones with amplitude or phase measurement biases

Abstract

Reliable duct mode detection results are essential for aero-engine health condition monitoring and low-noise design. Harsh aero-engine measurement environments may cause biases in amplitude and phase measurements due to the failure of wall-mounted microphones, which will decrease the performance of advanced sparse representation algorithms for duct mode detection. In this paper, two strategies to detect the duct mode with the failed microphones are proposed. An optimization problem is constructed considering the low-rankness of theoretical array measurement and row-sparsity of the failed microphone measurements. The Strategy 1 is based on the recovery of the theoretical array measurement. The recovered array measurement can be further used to detect the duct mode via the sparsity-induced duct mode detection algorithm (generalized minimax-concave penalty in this paper). With the simulation, the Strategy 1 can not recover the theoretical array measurement completely. The Strategy 2 is based on the removal of the failed microphone measurements. With the simulation and experiment, it turns out that the Strategy 2 can detect the interested mode accurately.