改进的EMD方法在车辆振动信号提取中的应用

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为了能在强噪声背景下准确地进行振动信号的特征提取，对经验模式分解进行了研究和改进，并将其应用于车辆振动信号的特征提取中。首先对系统中各输入信号进行了多次自相关处理，有效地降低信号中的噪声。然后对处理的信号进行经验模式分解，得到了各固有模态函数分量。最后对感兴趣的固有模态函数分量进行希尔伯特变换和谱分析，从而得到信号的特征信息。仿真和试验分析说明了改进的经验模式分解方法的可行性，并且对同类工程问题具有一定的参考价值。 In order to truly obtain the feature extraction of vibration signals under the strong background noise, the analysis and improvement of empirical mode decomposition （EMD） is carried on. After that, the improved EMD is applied to the feature extraction of vehicle vibration signals. First, the multi-autocorrelation method is adopted in each input signal,so the noise is reduced effectively. Then, EMD is used to deal with these signals,and the intrinsic mode functions （IMFs） are obtained. Finally, for obtaining the feature information of these signals, the Hilbert transformation and the spectrum analysis are performed in some IMFs. Theoretical analysis and ex- periment verify the effectiveness of the method, which are valuable reference for the same engineering problems.