Stall Warning of Axial Compressor Using Spatial FFT and Combined Analysis of Multiple Statistical Parameters

Abstract

In order to study an effective algorithm for the pre-stall warning of axial compressor, a pre-stall warning algorithm based on Spatial Fast Fourier Transform (Spatial FFT) and combined analysis of multiple statistical parameters is proposed to solve the problems of insufficient accuracy of stall judgment and short warning time margin in view of the existing pre-stall warning research. Taking the dynamic pressure signal at the tip of the first stage stator of a multi-stage axial compressor as the research object, the circumferential multi-channel signals which are reconstructed from the single-channel sensor signal by using the signal translation method is decomposed to obtain the multi-order modal amplitudes through the spatial FFT. Analyzing the 1st-order modal amplitude coefficient by using a variety of statistical parameter methods, several conclusions were obtained. Compared with the one-dimensional analysis methods, the spatial FFT analysis method has better warning time margin; Compared with the two statistical parameters of kurtosis and autocorrelation coefficient, the parameter analysis method combining autocovariance and autocorrelation function is less computationally intensive, has a larger difference between stable and stall conditions, lower misjudgment rate, better early warning effect, and can achieve a warning time margin of 0.04~0.137s.