Abstract
Detection and prediction of thermoacoustic instabilities are major challenges in the development and operation of combustion systems. In this paper, we introduce a tool for categorizing dynamical states and detecting early warning signals of thermoacoustic instability in a combustor. This tool, named complexity-entropy causality space (CECS), exploits the permutation entropy and Jensen–Shannon complexity of both the pressure and heat release rate signal. We identify the early warning stage of thermoacoustic instability in both the experimental and numerical system by applying k-medoids clustering in CECS. This study constitutes the development and demonstration of a novel framework that can accurately detect the onset of impending thermoacoustic instabilities.
Published Version
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