Evaluation of EMD and SSA sensitivity for efficient detection of aerodynamic instabilities in centrifugal compressors

Abstract

Aerodynamic instabilities in centrifugal compressors are dangerous phenomena affecting machines efficiency and in severe cases leading to failures of the compressing system due to high amplitude vibrations. Efficient instabilities detection during compressor operation is a challenge of utmost importance from economical and safety point of view. The most sensitive detection is possible with use of a pressure signal from inside of the compressor because specific pressure patterns are the first symptoms of instabilities. Detection of aerodynamic instabilities results in specific challenges, as the pressure signal is often very noisy and contains high amount of randomness. Surge -most severe instability, can develop very quickly. Therefore, the method of detection should be sensitive but also robust and quick. Another common instability, inlet recirculation is less dangerous, but it results in decrease of efficiency, which is to be avoided. Inlet recirculation often happens before surge, thus its presence can be used for surge proximity detection. The aim of this study is to investigate and compare the performance of two non-linear processing methods -Empirical Mode Decomposition (EMD) and Singular Spectrum Analysis (SSA) in the context of aerodynamic instabilities detection -inlet recirculation and surge. The comparison focuses on the robustness, sensitivity and pace of detection -crucial parameters for a successful detection method. It is shown that both methods perform similarly within the analyzed bounds for both instabilities. A slight advantage of SSA may be noticed for surge due to lower dispersion of the indicator value for the same conditions.

Comparison of Empirical Mode Decomposition and Singular Spectrum Analysis for Quick and Robust Detection of Aerodynamic Instabilities in Centrifugal Compressors

“…The choice of EMD and SSA as the methods for comparison resulted from their proven performance for compressor instability detection. A preliminary study on the pace of detection for EMD and SSA was conducted by the authors [32], which showed that the method could provide quick and robust indication of the condition. This article builds upon previous study to provide quantification of methods performance, considering the stochastic nature of the signal, give more insight into the method operation for compressor pressure signal and deliver more thoughtful conclusions that can be applied when building an instabilities detection system.…”