Experimental investigation on axial compressor stall phenomena using aeroacoustics measurements via empirical mode and proper orthogonal decomposition methods

Abstract

Abstract In this work, we conduct experimental investigations on a single-stage axial compressor to shed lights on the dynamic stall phenomena via acoustic measurements. For this, 8 acoustic pressure sensors are installed equally around the circumference of the compressor intake. The acoustic pressure data is simultaneously logged in real-time. Classical and conventional Fourier-transform based methods revealed that the compressor stall will occur beyond a critical pressure ratio or flow coefficient as revealed on a compressor map. However, there is no warning precursor obtained from the conventional signal analysis methods. Further investigations were conducted using a number of advanced signal processing techniques, such as empirical mode decomposition (EMD) and proper orthogonal decomposition (POD) and continuous wavelet (CW) methods. EMD analysis revealed that the compressor stall is corresponding to a low-frequency intrinsic mode function (IMF). It is growing rapidly from negligible amplitude random disturbances to limit cycle oscillations. POD showed that the number of the dominant acoustic modes contributing to more than 98.5% of the total fluctuation energy is changed from 3 to 7, when the stall occurs. This is insightful for low-order modeling of the compressor stall phenomena. Finally, applying CW transform could provide a warning of 0.05 s precursor on the tested compressor. In general, the present work opens up an alternative approach to study the dynamic physics of a compressor stall by applying an array of acoustic sensors with proper advanced data-processing methods implemented.