【摘要】 针对桥梁应变信号的特点,提出了一种基于经验模态分解法的降噪方法。当信号中噪声分布在某些特定频段且与信号混叠时,现有的降噪方法如小波阈值法无法很好地对其进行处理。本文在对桥梁应变信号进行经验模态分解的基础上,具体分析分解后的本征模函数分量,对含噪较大的本征模函数分量进行特定的阈值滤波处理,并将处理后的本征模函数分量与含噪较小的本征模函数分量以及残余分量进行信号重构,得到降噪后的桥梁应变信号。将此方法用于实际测得的数据,实验结果表明,其能在保留原始信号特征的前提下,消除桥梁应变信号中的噪声,从而达到降噪的目的。更多还原

【Abstract】 This paper proposes a de-nosing method for bridge strain signal based on empirical mode decomposition.When the noise appears in some certain frequency and blends with signal,the existing de-noising method such as wavelet threshold filtering method can not work well in this regard.This paper carries on empirical mode decomposition method for actual bridge strain signal and then picks out intrinsic mode functions which contain much noise.For these IMFs we carry on specific threshold filtering process method.After this,we use remaining IMFs,processed IMFs and the residual component to reconstruct the signal.The result shows that,this method can eliminate noise of bridge strain signal under the premise of preserving features of original signal.更多还原