Real-time stall detection of centrifugal fan based on the analysis of symmetrized dot pattern and wavelet packet transform

Abstract

This paper presents a novel stall detection method based on symmetrized dot pattern (SDP) analysis, which detects the starting point of rotating stall timely and accurately during operations of centrifugal fans. To demonstrate the proposed method, experiments were first performed on a G4-73 No. 8D centrifugal fan to measure the aerodynamic pressure signals of the air flow inside the fan during the gradual development of rotating stall. Then, the SDP technique was used to analyze the pressure signals and extract the time-domain characteristics of the pressure signal during the gradual development of rotation stall. Finally, a comprehensive autocorrelation coefficient was defined and employed as the index for real-time stall detection. In addition, to verify the accuracy of detection results, the tested signals were also analyzed off-line by wavelet transform to detect the actual starting point of rotating stall. The comparison results show that the stall detection method based on the symmetrized dot pattern (SDP) analysis can accurately detect the starting point of rotating stall in centrifugal fans within a short period of 0.05 s.