采用局部均值分解（Local Mean Decomposition，LMD）方法来识别机械系统固有频率和阻尼比。局部均值分解（LMD）方法可以自适应地将一个复杂信号分解为若干个具有一定物理意义的PF（Production Function）分量之和，采用LMD方法对脉冲激励下机械系统的加速度响应信号进行分解，得到一列具有物理意义的PF分量，每一个PF分量可以对应于某一个模态下的振动响应，进而就可以通过拟合瞬时频率和瞬时幅值曲线识别模态固有频率和阻尼比。先采用仿真信号进行了分析，使用LMD方法和经验模态分解方法（Empirical Mode Decomposition，EMD）对梁的瞬态响应实验数据进行模态识别并同仿真结果进行对比研究，结果表明用LMD进行模态分析具有较好的效果。%This method, by adopting the LMD(Local Mean Decomposition), identifies the inherent frequency and damp-ing ratio of mechanical systems. The self-adapting Local Mean Composition(LMD)method can disintegrate a complex signal to several PF(Production Function)components. Using LMD method to decompose the acceleration response sig-nal of a mechanical system with pulsed excitation gets some PF components with physical significance. With each PF component corresponding to the signal’s vibration response of one mode, the method is able to distinguish the inherent frequency and damping ratio of the signal in the modes, by matching the curves of instaneous frequency and magnitude. In this thesis, it analyses the experimental data of the transient response of a girder by adopting the simulating signal (method), and by using LMD and EMD. The comparison of the results of the two methods shows that the LMD method is of more superiorities in analysing modes.
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