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Knock threshold detection is the key of closed loop control of ignition in gasoline engine, and it is also the difficult point in knock measurement. In this paper, an investigation of knock detection in turbocharged gasoline engine using bispectrum slice and ensemble empirical mode decomposition (EEMD) based on the engine cylinder head vibration signals is presented. By adding some finite amplitude Gaussian white noises to the signal, EEMD keeps the signal continuous in different time span, and therefore the mode mixing inhering in the classical empirical mode decomposition (EMD) method is alleviated. Power spectrum density (PSD) estimation is used to determine the band range of the resonance frequency generated by knock component. EEMD is used to decompose the original signals, the time-frequency characteristics of the Intrinsic Mode Functions (IMF) are analyzed using Continues Wavelet Transform (CWT) due to its excellent time-frequency resolution.

This paper reports an investigation of knock detection in spark ignition (SI) engines using EEMD-Hilbert transform based on the engine cylinder block vibration signals. Ensemble Empirical Mode Decomposition (EEMD) was used to de-compose the signal and detect knock characteristic. Hilbert transform was used to analysis the frequency information of knock characteristics. The result shows that for cylinder block vibration signals, the EEMD algorithm could extract the knock characteristic (include light knock), and the Hilbert transform result shows that the instantaneous of knock characteristics concentrate in 5000-10000Hz. At last, the knock window is then determined, based on which a new knock intensity evaluation factor K is proposed, and the results show that, the parameter K is reasonable and effective.