摘要
经验模式分解(EMD)作为一种信号处理技术,它是基于数据本身的,且能在空间域中将信号进行分解,从而可以区分噪声和有用信号。应用经验模式分解(EMD)对模拟信号及实测油气水三相流压差波动信号进行滤波去噪处理,分别与db8小波及Haar小波的滤波去噪效果进行定量比较。结果表明:EMD方法与小波方法一样能有效地处理短时瞬态及含宽带噪声的信号,但EMD方法更直接,更方便,且不受小波基函数选择的影响,因此EMD方法更具有通用性和稳定性,从而为三相流流型信号的预处理提供了又一种有效的方法。
As one of signal processing techniques, empirical mode decomposition （EMD） can differentiate signals from the noise, for it can decompose the signal in spatial domain based on data itself. With EMD, the noise of simulated signals and pressure fluctuation signals of oil-air-water three-phase flow can be eliminated. Compared EMD with db8 wavelet and Haar wavelet quantitatively, it shows that EMD can deal with transient signals signals mixed with broadband noise as effectively as wavelet. Because of directness, convenience and influence engendered in the selection of mother wavelet, the EMD method is more universal and stable. and the stopping EMD is another effective method for pre-processing three-phase flow signal.
出处
《化学工程》
CAS
CSCD
北大核心
2010年第3期30-33,共4页
Chemical Engineering(China)
基金
国家自然科学基金资助项目(50706006)
关键词
经验模式分解(EMD)
油气水三相流
压差波动信号
去噪
empirical mode decomposition （EMD）
oil-air-water three-phase flow
pressure fluctuation signal
denoising
