EMD密集模态识别研究及在电站厂房中的应用
wf(2017)
Abstract
针对传统经验模态分解(EMD)密集模态分解能力不足的问题,提出信号调频预处理和优化模态筛选准则相结合的改进方法.研究了模态筛选准则、迭代次数、信号调频与EMD模态分解能力的关系,并给出了信号调频的具体过程;提出基于窗函数、信号调频和改进EMD模态筛选准则的密集模态识别方法,并分别通过仿真信号和电站厂房实测振动信号的模态参数识别进行验证.试验成果表明,改进方法能够有效识别密集模态参数,为EMD应用于电站厂房等密集模态结构参数识别奠定了基础.
MoreTranslated text
Key words
empirical mode decomposition,closely spaced modes,parameter identification,frequency modulation,selection criterion
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined