Acoustic feature extraction for monitoring the combustion process of diesel engine based on EMD and wavelet analysis

Shunting Fang, Si Chang Li, Dong Zhen, Zhanqun Shi, Fengshou Gu, Andrew David Ball

Research output: Contribution to journalArticle

1 Citation (Scopus)


In order to analyze the combustion characteristic of the internal-combustion engine, combustion noise signal was collected, replacing the cylinder pressure signal in this paper. An acoustic signal feature extraction method using empirical mode decomposition (EMD) and wavelet analysis (WA) was proposed. Time synchronous average (TSA) is used for filtering interference noise to enhance the signal-to-noise ratio (SNR) of the measured acoustic signal as noise will affect the decomposition process resulting in over decomposition. The processed acoustic signals were decomposed into a series of intrinsic mode functions (IMF) using the method of empirical mode decomposition (EMD) in the time domain. Then wavelet analysis which has good time-frequency localization feature was applied on useful IMFs containing the information of diesel engine combustion. The root mean square (RMS) value of wavelet analysis results was calculated to achieve linear state monitoring.

Original languageEnglish
Pages (from-to)25-30
Number of pages6
JournalInternational Journal of COMADEM
Issue number3
Publication statusPublished - 1 Jul 2017


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