摘要
提出了一种改进的集总平均经验模态分解(M-EEMD)方法,并阐述了其基本原理。通过仿真试验,证实了M-EEMD不仅能够很好地解决经验模态分解(EMD)中模态混叠问题,而且能够抑制集总平均经验模态分解(EEMD)的噪声残余和模态分裂等问题。作为实例,对一个4缸4冲程内燃机气缸盖罩的振动信号进行M-EEMD分解,并对分解得到的IMF分量进行时频分析。结果表明M-EEMD能够成功地将内燃机气门拍击引起的机械激励成分与燃烧激励成分分离。
A modified ensemble empirical mode decomposition（M-EEMD） method is proposed with its basic principle expounded.Simulation tests demonstrate that the M-EEMD technique can not only tackle the mode mixing problem of the empirical mode decomposition（EMD） method,but also restrain the noise residue and mode splitting problem of the EEMD method.As an example,an M-EEMD decomposition is conducted on the vibration signals of cylinder heat cover in a four cylinder four-stroke engine,followed by a time-frequency analysis on the intrinsic mode functions（IMFs） component obtained by decomposition.The results indicate that the mechanical excitation by valve-slap and combustion excitation in an engine can be successfully separated by M-EEMD.
出处
《汽车工程》
EI
CSCD
北大核心
2011年第11期930-936,共7页
Automotive Engineering
基金
国家科技支撑项目(2011BAE22B05)资助
