基于ITD-FE-SVD的水轮发电机组振动信号去噪方法

De-noising Method of Vibration Signal of Hydro-turbine Generator Set based on ITD-FE-SVD

针对水轮发电机组振动信号呈现为非平稳、非线性且易受周围环境噪声影响导致机组振动信号特征难以准确提取的问题,提出固有时间尺度分解(Intrinsic time scale decomposition,ITD)结合模糊熵(fuzzy entropy,FE)奇异值差分谱(singular value decomposition,SVD)的水轮发电机组振动信号去噪方法。利用ITD先对振动数据进行分解以模糊熵为阈值,选取模糊熵值小于2的分量进行重构,达到第一次去噪的效果。再在这个去噪的基础上进行SVD分解,根据奇异值差分谱中奇异值变化较大的点来选择重构阶数对数据进行重构,从而达到几乎完全去噪的效果。最后将本方法和局部均值分解(LMD)结合模糊熵和奇异值差分谱的方法进行对比发现,ITD-FE-SVD去噪效果更好,能够保留更多的原信号信息。

Aiming at the problem that the vibration signal of the hydro-generator unit is non-stationary,non-linear and susceptible to ambient noise,it is difficult to accurately extract the characteristics of the vibration signal of the unit.Inherent time scale decomposition(ITD)combined with fuzzy entropy(FE)singular value difference spectrum is proposed.(SVD)De-noising method for vibration signal of hydro-generator unit.Use ITD to first decompose the vibration data with fuzzy entropy as the threshold,and select the components with fuzzy entropy value less than 2 for reconstruction to achieve the first de-noising effect.Then,SVD decomposition is performed on the basis of this denoising,and the reconstruction order is selected to reconstruct the data according to the points where the singular value changes in the singular value difference spectrum,so as to achieve an almost complete denoising effect.Finally,comparing this method with local mean decomposition(LMD)combined with fuzzy entropy and singular value difference spectrum method,it is found that ITD-FE-SVD has a better denoising effect and can retain more original signal information.