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.
Blind separation of internal combustion engine vibration signals by a deflation method