Stochastic averaging for identification of feedback nonlinearities in thermoacoustic systems / Gregory Hagen in Transactions of the ASME . Journal of dynamic systems, measurement, and control, Vol. 133 N° 6 (Novembre 2011)  

Public ISBD [article]  inTransactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 133 N° 6 (Novembre 2011) . - 10 p. Titre : Stochastic averaging for identification of feedback nonlinearities in thermoacoustic systems Type de document : texte imprimé Auteurs : Gregory Hagen, Auteur Année de publication : 2012 Article en page(s) : 10 p. Note générale : Dynamic systems Langues : Anglais (eng) Mots-clés : Gaussian processes Iterative methods Thermoacoustics Time series Vibrations Index. décimale : 553 Géologie économique. Minérographie. Minéraux. Formation et gisements de minerais Résumé : We present algorithms based on stochastic averaging for estimating nonlinear feedback parameters obtained from time series data with application to noise-driven nonlinear vibration systems, with particular emphasis on limit-cycling thermo-acoustic systems. The harmonic and Gaussian components of relevant signals are estimated from the probability density function (pdf) of an output signal from a single experiment. The respective feedback gains, along with a phase-shifting element are fit to a nominal (given) linear oscillator model from which the parameters of a nonlinearity are fit. When input-output data are available from multiple experiments, the feedback nonlinearity can be estimated point-wise via an iterative algorithm, applicable when the appropriate input signals have a constant (Gaussian) variance. The estimation procedures are demonstrated on a benchmark thermo-acoustic model and applied to time-series data obtained from a limit-cycling combustor rig experiment. In the latter case, relations between the feedback parameters and the fuel to air ratio are briefly discussed. DEWEY : 553 ISSN : 0022-0434 En ligne : http://asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA000133000006 [...] [article] Stochastic averaging for identification of feedback nonlinearities in thermoacoustic systems [texte imprimé] / Gregory Hagen, Auteur . - 2012 . - 10 p. Dynamic systems Langues : Anglais (eng) in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 133 N° 6 (Novembre 2011) . - 10 p. Mots-clés : Gaussian processes Iterative methods Thermoacoustics Time series Vibrations Index. décimale : 553 Géologie économique. Minérographie. Minéraux. Formation et gisements de minerais Résumé : We present algorithms based on stochastic averaging for estimating nonlinear feedback parameters obtained from time series data with application to noise-driven nonlinear vibration systems, with particular emphasis on limit-cycling thermo-acoustic systems. The harmonic and Gaussian components of relevant signals are estimated from the probability density function (pdf) of an output signal from a single experiment. The respective feedback gains, along with a phase-shifting element are fit to a nominal (given) linear oscillator model from which the parameters of a nonlinearity are fit. When input-output data are available from multiple experiments, the feedback nonlinearity can be estimated point-wise via an iterative algorithm, applicable when the appropriate input signals have a constant (Gaussian) variance. The estimation procedures are demonstrated on a benchmark thermo-acoustic model and applied to time-series data obtained from a limit-cycling combustor rig experiment. In the latter case, relations between the feedback parameters and the fuel to air ratio are briefly discussed. DEWEY : 553 ISSN : 0022-0434 En ligne : http://asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA000133000006 [...]

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