| It is complicated to run a jet engine at a high efficiency during the start-up as the RPM of the system increases without exhibiting stall in the jet’s compressor section. When the compressor system approaches the maximum efficiency, the pressure rise is at its optimum, however stall may occur. Most of the research published on this topic provides essential information on the spike stall. Some research reported precursors to indicatestall100 to 220 revolutions before the event of stall. However, this is associated with modal stall inception. Stall happens in the first stage of the system and if not mitigated can cause severe damage to the system. In this thesis, a numerical method for stall precursor detection is investigated utilizing real compressor test data. .In this thesis, three different methods are utilized for the purpose to find precursors of stall: the Generalized Extreme Studentized Deviate Test (ESD) and Autoregressive models (AR).Key Words: Jet engine, Stall prediction, Generalized Extreme Studentized Deviate Test, Autoregressive models. |