Source identification of gasoline engine noise based on continuous wavelet transform and EEMD–RobustICA. (15th December 2015)
- Record Type:
- Journal Article
- Title:
- Source identification of gasoline engine noise based on continuous wavelet transform and EEMD–RobustICA. (15th December 2015)
- Main Title:
- Source identification of gasoline engine noise based on continuous wavelet transform and EEMD–RobustICA
- Authors:
- Bi, Fengrong
Li, Lin
Zhang, Jian
Ma, Teng - Abstract:
- Graphical abstract: Highlights: The EEMD–RobustICA method realizes the BSS of single-channel signal. The CWT using CMW is employed to represent ICs in joint time–frequency domain. The exhaust, combustion and piston slap noise are identified accurately. The two-channel noise signals are measured to verify the identification result. Abstract: In order to separate noise source of gasoline engine, ensemble empirical mode decomposition (EEMD), robust independent component analysis (RobustICA) and continuous wavelet transform (CWT) are applied to study the blind source separation and noise source identification of gasoline engine. After the signal is decomposed with EEMD into a set of intrinsic mode function (IMFs), RobustICA has been applied to extract independent sources. The combined technique alleviates the problem of mode mixing in EMD and overcomes the problem that the number of sensors must be larger than or equal to the number of separated components. At the same time, RobustICA's cost efficiency and robustness are particularly remarkable for short sample length in the absence of pre-whiten. CWT using the Complex Morlet Wavelet (CMW) is used for its better time–frequency localization features to analyze time–frequency characteristics of the ICA results. Combining the time–frequency results with different noise sources frequency spectrums, the corresponding relation of the different noise sources of gasoline engine and the independent components is determined. It turns outGraphical abstract: Highlights: The EEMD–RobustICA method realizes the BSS of single-channel signal. The CWT using CMW is employed to represent ICs in joint time–frequency domain. The exhaust, combustion and piston slap noise are identified accurately. The two-channel noise signals are measured to verify the identification result. Abstract: In order to separate noise source of gasoline engine, ensemble empirical mode decomposition (EEMD), robust independent component analysis (RobustICA) and continuous wavelet transform (CWT) are applied to study the blind source separation and noise source identification of gasoline engine. After the signal is decomposed with EEMD into a set of intrinsic mode function (IMFs), RobustICA has been applied to extract independent sources. The combined technique alleviates the problem of mode mixing in EMD and overcomes the problem that the number of sensors must be larger than or equal to the number of separated components. At the same time, RobustICA's cost efficiency and robustness are particularly remarkable for short sample length in the absence of pre-whiten. CWT using the Complex Morlet Wavelet (CMW) is used for its better time–frequency localization features to analyze time–frequency characteristics of the ICA results. Combining the time–frequency results with different noise sources frequency spectrums, the corresponding relation of the different noise sources of gasoline engine and the independent components is determined. It turns out that these independent components correspond to the exhaust, combustion and piston slap noise of the gasoline engine respectively. … (more)
- Is Part Of:
- Applied acoustics. Volume 100(2015)
- Journal:
- Applied acoustics
- Issue:
- Volume 100(2015)
- Issue Display:
- Volume 100, Issue 2015 (2015)
- Year:
- 2015
- Volume:
- 100
- Issue:
- 2015
- Issue Sort Value:
- 2015-0100-2015-0000
- Page Start:
- 34
- Page End:
- 42
- Publication Date:
- 2015-12-15
- Subjects:
- Ensemble empirical mode decomposition -- Robust independent component analysis -- Continuous wavelet transform -- Noise source identification
Acoustical engineering -- Periodicals
Periodicals
620.2 - Journal URLs:
- http://www.sciencedirect.com/science/journal/0003682X ↗
http://www.elsevier.com/journals ↗
http://www.elsevier.com/homepage/elecserv.htt ↗ - DOI:
- 10.1016/j.apacoust.2015.07.007 ↗
- Languages:
- English
- ISSNs:
- 0003-682X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1571.400000
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