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This paper reports on the analysis of flame kinematics and cycle variation in port fuel injection (PFI) spark ignition (SI) engine. The engine was equipped with a four-valve head and with an external boost device. Different operating conditions were considered. Cycle-resolved digital imaging was used to investigate flame motion and the effects of an abnormal combustion due to the firing of fuel deposition near the intake valves and on the piston surface. Various algorithms are applied to the acquired images. Coefficients of Proper Orthogonal Decomposition (POD) were computed and used for a statistical analysis of cycle variability. The advantage is that the analysis can be run on a small number of scalar coefficients rather than on the full data set of pixel valued luminosity.

Data decomposition techniques have become a standard approach for the analysis of 2D imaging data originating from optically accessible internal combustion engines. In particular, the method of Proper Orthogonal Decomposition (POD) has proven to be a valuable tool for the evaluation of cycle-to-cycle variability based on luminous combustion imaging and particle image velocimetry (PIV) measurements. POD basically permits to characterize the dominant structures of the process under consideration. Recently, an alternative procedure based on Independent Component Analysis (ICA) has been introduced in the engine field. Unlike POD, the method of ICA identifies the patterns corresponding to physical processes that are statistically independent. In this work, a Group-ICA approach is applied to 2D cycle-resolved images of the luminosity emitted by the combustion process. The analysis is meant to characterize cyclic variability of a port fuel injection spark ignition (PFI SI) engine.