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Time-frequency analysis of I.C. engine vibration signals based on EWT-PWVD

机译:I.C.的时频分析基于EWT-PWVD的发动机振动信号

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In order to effectively solve the problem of the contradiction between the cross-interference term and the time-frequency aggregation in the analysis of multi-component signals by Wigner-Ville distribution (WVD), an new time-frequency analysis method based on empirical wavelet transform (EWT) and Pseudo-Wigner distribution (PWVD), named EWT-PWVD is proposed. Firstly, the multi-component signals are decomposed by EWT and a set of intrinsic mode functions (IMF) are obtained. Then each IMF is analyzed by PWVD. Finally, the analysis results of each IMF are linear superposed to reconstruct the time-frequency distribution of the original signal. The simulation results show this method can effectively suppress the cross-interference terms of WVD and maintain its original characteristics. Meanwhile this method is applied to time-frequency analysis of Internal Combustion Engine (I.C. Engine) vibration signals. The result shows this method can clearly depict the representative characteristic of signals and eliminate the cross-interference terms. EWT-PWVD is an effective time-frequency analysis method of signals.
机译:为了有效解决Wigner-Ville分布(WVD)分析多分量信号时交叉干扰项与时频聚合之间的矛盾问题,一种基于经验小波的时频分析新方法提出了一种名为EWT-PWVD的变换(EWT)和伪维格纳分布(PWVD)。首先,通过EWT分解多分量信号,并获得一组固有模式函数(IMF)。然后通过PWVD分析每个IMF。最后,将每个IMF的分析结果进行线性叠加,以重建原始信号的时频分布。仿真结果表明,该方法可以有效地抑制WVD的交叉干扰项,并保持其原始特性。同时,该方法被应用于内燃机振动信号的时频分析。结果表明,该方法可以清晰地描述信号的代表性特征,消除了交叉干扰项。 EWT-PWVD是一种有效的信号时频分析方法。

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