 Clustering of chaotic dynamics of a lean gas-turbine combustorA. Fichera, C. Losenno and A. Pagano Applied Energy, 2001, vol. 69, issue 2, 117 pages Abstract: This work deals with the dynamic behaviour of a lean premixed gas turbine combustor. The study aims to achieve a classification of experimental burner dynamic behaviour and is based on the geometrical properties of the attractors of the system variables. Several experiments were performed varying the flame stoichiometric ratio [lambda] and the pilot fuel percentage PFP. The dynamics of the experimental time series of the flame front heat release were described by using vectors collecting information on the topological distribution of the attractors. Therefore, unsupervised Kohonen associative memories were trained to create clusters of operating conditions characterised by similar dynamical behaviours. Kohonen associative memories were able to divide the experimental operating conditions into different clusters according to the different values of the flame stoichiometric ratio. The results of the clustering underline the possibility of being able to define an algorithm for combustion-instability pattern recognition that takes into account the highly non-linear effects which govern combustion processes. Keywords: Combustion; instabilities; Chaotic; behaviour; Unsupervised; neural; networks (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:69:y:2001:i:2:p:101-117 Ordering information: This journal article can be ordered from Access Statistics for this article Applied Energy is currently edited by J. Yan More articles in Applied Energy from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.