基于样条的振动信号局域均值分解方法

Spline-Based Local Mean Decomposition Method for Vibration Signal

局域均值分解(Local mean decomposition,LMD)的主要思想是把一个时间序列的信号,分解成不同尺度的包络信号和纯调频信号,然后获得信号的时频分布。LMD算法用极值点来定义局部均值函数和局域包络函数,然后用滑动平均来平滑均值和包络函数,针对用滑动平均平滑均值和包络函数误差较大的缺点,提出了采用三次样条对上、下极值点分别插值求得上下包络线,然后由上下包络线的平均获得局部平均函数,由上下包络线相减的绝对值获得局部包络的方法。通过对非线性和实例振动信号的实验研究表明,基于样条的LMD方法的分析精度比LMD方法高。

The local mean decomposition （LMD） is a new approach for demodulating amplitude and frequency modulated signals. Such signals are decomposed into an envelope signal and a frequency modulated signal to obtain the time-varying instantaneous frequency moving averaging. The LMD algorithm uses extrema to define the local mean and envelope, then to smooth the mean and envelope. To decrease errors in the smoothing process by using moving averaging, a new local mean and envelope definition method（the spline-based LMD） is proposed. The upper envelope and the lower envelope are obtained by connecting the local maxima and the local minima using a cubic spline line. The local mean is defined as a mean of the upper envelope and the lower envelope. A nonlinear simulation signal and a practical vibration signal are decomposed by the LMD and the spline-based LMD. Results show that the spline-based LMD method is more precise than the LMD. The study result can be used in vibration signal analysis field.