TY - JOUR
T1 - Data-driven fault detection and estimation in thermal pulse combustors
AU - Chakraborty, S.
AU - Gupta, S.
AU - Ray, A.
AU - Mukhopadhyay, A.
PY - 2008
Y1 - 2008
N2 - This paper presents the development of a dynamic data-driven statistical method for: (a) early detection of incipient faults and (b) parameter estimation for prognosis of forthcoming failures and operational disruptions (e.g. flame extinction) in thermal pulse combustors. From these perspectives, reduction in the tailpipe friction coefficient is estimated from time-series data of pressure oscillations. The algorithms for parameter estimation are built upon the principles of Symbolic Dynamics, Information Theory and Statistical Pattern Recognition. The proposed algorithms have been tested on an experimentally validated simulation model of a generic thermal pulse combustor. JAERO432
AB - This paper presents the development of a dynamic data-driven statistical method for: (a) early detection of incipient faults and (b) parameter estimation for prognosis of forthcoming failures and operational disruptions (e.g. flame extinction) in thermal pulse combustors. From these perspectives, reduction in the tailpipe friction coefficient is estimated from time-series data of pressure oscillations. The algorithms for parameter estimation are built upon the principles of Symbolic Dynamics, Information Theory and Statistical Pattern Recognition. The proposed algorithms have been tested on an experimentally validated simulation model of a generic thermal pulse combustor. JAERO432
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U2 - 10.1243/09544100JAERO432
DO - 10.1243/09544100JAERO432
M3 - Article
AN - SCOPUS:57349182500
SN - 0954-4100
VL - 222
SP - 1097
EP - 1108
JO - Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering
JF - Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering
IS - 8
ER -