摘要
针对振动信号中的趋势项成分的提取,提出一种基于希尔伯特-黄变换(HHT)的新方法。先用经验模态分解(EMD)方法将信号分解为一系列固有模态函数(IMF),然后对各IMF分量进行Hilbert变换得到希尔伯特边际谱;通过计算各IMF希尔伯特边际谱,可以获得各IMF的主频成分,对属于趋势项的IMF分量进行判别,最终确定趋势项。仿真结果表明,该方法能准确的提取振动信号中的趋势项成分。
In order to extract the trend in vibration signals,a new method based on Hilbert-Huang Transform(HHT) is proposed in this paper.After decomposing the signal into a small number of intrinsic mode functions(IMFs) based on empirical mode decomposition(EMD),the Hilbert transform of each IMF is performed and the Hilbert marginal spectrum of each IMF is calculated.Then,we can obtain the dominant frequency of each IMF from the Hilbert marginal spectrum of each IMF.After distinguishing the IMF belongs to trend,the trend in vibration signal can be calculated at last.The extensive simulations show that this method is indeed capable of extracting the trend in the vibration signal.
出处
《电子测量技术》
2013年第2期119-122,共4页
Electronic Measurement Technology
基金
国家科技支撑计划基金(2007BAG06B06)资助项目
关键词
趋势项
经验模态分解
希尔伯特边际谱
trend
empirical mode decomposition
Hilbert marginal spectrum
