广义经验模态分解性能分析与应用  

Performance analysis and application of generalized empirical mode decomposition

作　　者：郑近德[1] 程军圣[1] 曾鸣[1] 罗颂荣[1] 

机构地区：[1]湖南大学汽车车身先进设计制造国家重点实验室,长沙410082

出　　处：《振动与冲击》2015年第3期123-128,155,共7页Journal of Vibration and Shock

基　　金：国家自然科学基金(51175158;51075131);湖南省自然科学基金(11JJ2026);湖南省研究生科研创新项目资助(CX2013B144);湖南省机械设备健康维护重点实验室开放基金资助项目(201202)

摘　　要：针对经验模态分解(Empirical Mode Decomposition,EMD)的均值曲线采用三次样条拟合而容易引起包络过冲和不足等缺陷,相关学者提出了许多改进均值曲线的变种EMD方法,取得了一定的效果。广义经验模态分解(Generalized EMD,GEMD)方法综合了多种改进EMD方法,通过定义不同的均值曲线对信号进行逐阶筛分,从得到的每一阶分量中选取最优作为最终的广义内禀模态函数(Generalized Intrinsic Mode Function,GIMF),由于每一阶的GIMF分量都是最优的,因此相较于EMD等单一均值曲线筛分方法,GEMD分解结果也是最优的。论文对GIMF分量准则进行了改进以及对GEMD性能进行了分析,并将GEMD应用于仿真和实测信号的分析,结论表明GEMD分解是完备的和正交的,有比EMD更强的分解能力,而且适合机械振动信号的处理和故障诊断。Aiming at that the mean curve defined in empirical mode decomposition （EMD）fitted with cubic spline may cause envelope overshoot and undershoot,many improved EMDs for improving the mean curve are proposed and some good effects are achieved.Generalized empirical mode decomposition （GEMD）integrates several improved EMD methods and selects the best component from components obtained by sifting different mean curves in each rank as the final generalized IMF （GIMF）.Since the GIMF is the best in each rank,the corresponding results of GEMD are also the best. Here,GEMD was introduced firstly and then an improved criterion of GIMF was developed.Furthermore,GEMD was employed to analyze simulated and actual mechanical vibration signals.The results showed that GEMD is complete and orthogonal,it has a better capacity of decomposition than that of EMD,it is suitable for mechanical fault diagnosis as well.

关 键 词：经验模态分解 广义经验模态分解 局部特征尺度分解 分解能力 故障诊断 

分 类 号：TH165.3[机械工程—机械制造及自动化] TN911[电子电信—通信与信息系统]