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

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.

2001 ◽  
Vol 123 (3) ◽  
pp. 685-692 ◽  
Author(s):  
D. M. W. Hoffman ◽  
D. R. Dowling

In internal combustion engine vibration modeling, it is typically assumed that the vibratory state of the engine does not influence the loads transmitted to the engine block from its moving internal components. This one-way-coupling assumption leads to energy conservation problems and does not account for Coriolis and gyroscopic interactions between the engine block and its rotating and reciprocating internal components. A new seven-degree-of-freedom engine vibration model has been developed that does not utilize this assumption and properly conserves energy. This paper presents time and frequency-domain comparisons of this model to experimental measurements made on an inline six-cylinder heavy-duty Diesel engine running at full load at peak-torque (1200 rpm) and rated (2100 rpm) speeds. The model successfully predicts the overall features of the engine’s vibratory output with model-experiment correlation coefficients as high as 70 percent for vibration frequencies up through third engine order. The results are robust to variations in the model parameters. Predictions are less successful at the detail level and at higher frequencies because of uncertainties in the actual imperfections of the test engine, and because of the influence of unmodeled engine components.


2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Jiachi Yao ◽  
Yang Xiang ◽  
Sichong Qian ◽  
Shuai Wang

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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