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

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.

2018 ◽  
Vol 2018 ◽  
pp. 1-14
Author(s):  
Yang Xiang ◽  
Jiachi Yao ◽  
Qiang Zhou ◽  
Sichong Qian ◽  
Shuai Wang

Internal combustion engine noise sources are complex and changeable. Combustion noise is usually drowned out by mechanical noise and aerodynamic noise. Traditional noise source identification methods can only qualitatively identify combustion noise. In order to quantitatively obtain the independent pure combustion noise of an internal combustion engine, it is necessary to design and build a separate noise source simulation test bench. In this paper, the combustion noise separation test bench based on transfer function method is designed and implemented. In the test, a pressure pulse device is installed in the combustion chamber. When the piston is at top dead center (TDC), pulse pressure is generated to excite the internal combustion engine to radiate noise. The pressure signal and noise signal are utilized to obtain the transfer function of combustion pressure and noise. Then, according to the cylinder pressure and transfer function, the combustion noise can be directly calculated. The test was carried out on 4120SG diesel engine. Experimental results show that when the internal combustion engine is under 1500 rpm and no-load condition and 800 rpm and no-load condition, the frequency components of independent pure combustion noise are both mainly concentrated at 1100 Hz, 1400 Hz, and 3000 Hz. Furthermore, the internal combustion engine vibration test method and the combustion noise empirical formula calculation method are both carried out to show accuracy and effectiveness of the obtained independent combustion noise through the combustion noise separation test based on transfer function method.


2019 ◽  
Vol 2019 ◽  
pp. 1-19 ◽  
Author(s):  
Jiachi Yao ◽  
Yang Xiang ◽  
Sichong Qian ◽  
Shuai Wang

The separation and identification technology of noise sources is the focus and hot spot in the field of internal combustion engine noise research. Combustion noise and piston slap noise are the main noise sources of an internal combustion engine. However, both combustion noise and piston slap noise occur almost at the top dead center. They mix in the time domain and frequency domain. It is difficult to accurately and effectively separate them. A single-channel algorithm which combines time-varying filtering-based empirical mode decomposition (TVF-EMD) and robust independent component analysis (RobustICA) methods is proposed to separate them. Firstly, the TVF-EMD method is utilized to decompose the single-channel noise signal into several intrinsic mode functions (IMFs). Then, the RobustICA method is applied to extract the independent components. Finally, related prior knowledge and time-frequency analysis are employed to identify noise sources. Furthermore, the spectral filtering method and the calculation method of piston slap noise based on the dynamic model are further carried out to verify separation results. The simulation and experimental research results show the effectiveness of the proposed method.


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.


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