Abstract

Combustion instability has many detrimental effects on flight-propulsion dynamics and structural integrity of gas turbine engines and its early detection is one of the important tasks in engine health monitoring and prognostics. Combustion in-stability is characterized by self-sustained, large-amplitude pressure oscillations and periodic shedding of coherent vor-tex structures at varied spatial scales. It is caused when lo-calized hydrodynamic perturbations in fluid flow fluctuations are augmented by heat release, coupled with acoustics of the combustion chamber. This paper proposes a dynamic data-driven approach, where a large volume of sequential hi-speed (greyscale) images is used to analyze the temporal evolution of coherent structures in combustion chamber for early detec-tion of combustion instability at various operating conditions.