基于EMD和AR模型的水轮机尾水管动态特征信息提取

EMD and AR Model Based Dynamic Characteristic Extraction of the Draft Tube of Hydraulic Turbines

提出一种基于经验模态分解(EMD)和自回归(AR)模型的水轮机尾水管动态特征信息提取方法。对经过预处理的信号进行EMD分解,得到包含特征频率的本征模态函数(IMF),对每个IMF建立AR模型,取模型参数作为故障模式识别的特征矢量。以水轮机尾水管压力脉动信号为例,运用此方法进行了尾水管动态特征信息的提取。试验表明,基于EMD和AR模型的特征提取法是故障特征提取的有效方法。

This paper presents a new method for extracting the dynamic characteristics of the draft tube of a hydraulic turbine hased on EMD （empirical mode decomposition） and AR （auto regressive） model, The signals processed in advance are decomposed with EMD, thus the intrinsic mode functions （IMFs） containing characteristic frequencies can be obtained. The AR model can then be developed for every IMF, and the parameters of AR model can be used as the characteristic parameters for fault mode recognition. As an example, the monitoring signals of the pressure fluctuation of the draft tube are processed with the proposed method. It is shown that the method effective for extracting fault information.