Mechanical signature analysis using time-frequency signal processing: application to internal combustion engine knock detection

1996 ◽  
Vol 84 (9) ◽  
pp. 1330-1343 ◽  
Author(s):  
B. Samimy ◽  
G. Rizzoni
Keyword(s):  
Signal Processing ◽  
Internal Combustion Engine ◽  
Combustion Engine ◽  
Internal Combustion ◽  
Signature Analysis ◽  
Frequency Signal ◽  
Processing Application ◽  
Time Frequency ◽  
Engine Knock ◽  
Knock Detection

The Time-Frequency Analysis Method Based on EMD White Noise Energy Density Distribution Characteristics of the Internal Combustion Engine Vibration

2013 ◽  
Vol 328 ◽  
pp. 367-375 ◽  
Author(s):  
Guo Yan Feng ◽  
Yan Ping Cai ◽  
Yan Ping He
Keyword(s):  
Energy Density ◽  
Internal Combustion Engine ◽  
White Noise ◽  
Combustion Engine ◽  
Vibration Signal ◽  
Internal Combustion ◽  
Distribution Characteristics ◽  
Energy Density Distribution ◽  
Time Frequency ◽  
Engine Vibration

For the limitations of HHT of the internal combustion engine vibration signal analysis, and the problem of WVD cross-term suppression methods existing aggregation and cross-term component suppression conflicting, the time-frequency analysis method based on EMD white noise energy density distribution characteristics of the internal combustion engine vibration is proposed. First, the internal combustion engine vibration signal was decomposed into the independent series intrinsic mode function (IMF) with different characteristic time scales by using EMD decomposition method. Then, based on the energy density distribution characteristics of the white noise in EMD decomposition, used the distribution interval estimation curve of the IMFs energy density logarithm of white noise with the same length of the original signal as cordon for false pattern component, identified and eliminated false mode component of vibration signal IMFs component, analysised of each IMF with Wigner-Ville. Finally, the Wigner-Ville analysis results of each IMF were linear superposed in order to reconstruct the original signal time-frequency distribution. Simulation and engine vibration time-frequency analysis results show that this method has an excellent time-frequency characteristics, and can successfully extract feature information of the internal combustion engine cylinder head vibration signal.

Detection and modelling of incipient failures in internal combustion engine driven generators using Electrical Signature Analysis

2017 ◽  
Vol 149 ◽  
pp. 30-45 ◽  
Author(s):  
P.L. Mendonça ◽  
E.L. Bonaldi ◽  
L.E.L. de Oliveira ◽  
G. Lambert-Torres ◽  
J.G. Borges da Silva ◽  
...  
Keyword(s):  
Internal Combustion Engine ◽  
Combustion Engine ◽  
Internal Combustion ◽  
Signature Analysis

scholarly journals Radiation Noise Separation of Internal Combustion Engine Based on Gammatone-RobustICA Method

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Jiachi Yao ◽  
Yang Xiang ◽  
Sichong Qian ◽  
Shuai Wang
Keyword(s):  
Internal Combustion Engine ◽  
Filter Bank ◽  
Noise Source ◽  
Combustion Engine ◽  
Near Field ◽  
Source Separation ◽  
Internal Combustion ◽  
Combustion Noise ◽  
Time Frequency ◽  
Separation Results

In the internal combustion engine noise source separation process, the combustion noise and the piston slap noise are found to be seriously aliased in time-frequency domain. It is difficult to accurately separate them. Therefore, the noise source separation method which is based on Gammatone filter bank and robust independent component analysis (RobustICA) is proposed. The 6-cylinder internal combustion engine vibration and noise test are carried out in a semianechoic chamber. The lead covering method is adopted to isolate the interference noise from numbers 1 to 5 cylinder parts, with only the number 6 cylinder parts left bare. Firstly, many mode components of the measured near-field radiated noise signals are extracted through the designed Gammatone filter bank. Then, the RobustICA algorithm is utilised to extract the independent components. Finally, the spectrum analysis, the continuous wavelet time-frequency analysis, the correlation function method, and the drag test are employed to further identify the separation results. The research results show that the frequency of the combustion noise and the piston slap noise are, respectively, concentrated at 4025 Hz and 1725 Hz. Compared with the EWT-RobustICA method, the separation results obtained by the Gammatone-RobustICA method have very fewer interference components.

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