针对低信噪比泄流结构振动信号有效信息难以提取问题，提出将小波阈值与经验模态分解（EMD）联合的信号降噪方法。利用小波阈值滤除大部分高频白噪声，降低 EMD 端点效应；进行 EMD 分解获得具有相对真实物理意义的固态模量（IMF）；通过频谱分析重构特征信息 IMF 获得降噪信号。构造仿真信号，将该方法与数字滤波、小波分析及EMD 降噪效果进行对比。结果表明，该方法能精确滤除泄流结构的振动噪声保留信号特征信息，滤波降噪较优越。将其用于拉西瓦拱坝水弹性模型，精确分析坝体结构振动优势频率，为坝体结构的安全运行与在线监测提供基础，亦为大型泄流结构在强背景噪声下的结构有效信息提取提供捷径。%In view of the difficulty in extracting useful characteristics from the vibration signal of flood discharge structure with low signal to noise ratio,a novel de-noising method,combining wavelet threshold and empirical mode decomposition (EMD),was proposed.First of all,a part of white noises were filtered out with the wavelet threshold method,which can reduce the endpoint effect of EMD;then the signal was decomposed with EMD,to obtain a series of intrinsic mode functions (IMFs) which contains real physical meanings;finally the IMFs including characteristic information were reconstructed to achieve the de-noised signal through spectrum analysis.Constructing a simulation signal, and comparing the filtering effect of this method with the conventional method of digital filter,wavelet threshold and EMD on the signal,it is shown that,the method presented is a superior de-noising method,which can filter the vibration noise of flood discharge structure accurately and retain the characteristic information.It has been used in the Laxiwa arch dam hydro-elastic model test,analyzing the dominate frequency of dam structure precisely,and providing the basis for safe operation and on-line monitoring of the dam structure.
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