基于变分模态分解和去趋势波动分析的柴油机振动信号去噪方法

为了解决柴油机工作时其振动信号的背景噪声对状态监测及故障诊断造成干扰这一问题,提出一种基于变分模态分解(VMD)和去趋势波动分析(DFA)的柴油机振动信号去噪方法。该方法首先利用变分模态分解将振动信号分解为若干分量,再利用去趋势波动分析分别计算各个分量的尺度指数,根据尺度指数的值选取具有长程相关性的分量进行信号的重构,以消除振动信号中噪声。将该方法应用于仿真信号和柴油机故障振动信号中,取得了良好的消噪效果。

Vibration Signal Denoising Method of Diesel Engines Based on VMD and DFA

In order to solve the problem that the background noise of diesel engine vibration signals interferes with operating condition monitoring and fault diagnosis, a vibration signal denoising method based on variational mode decomposition(VMD) and detrended fluctuation analysis(DFA) was proposed. The variational mode decomposition was used to decompose the vibration signal into several components, and then the detrended fluctuation analysis was used to calculate the scale index of each component to select the components with a long-range correlation for signal reconstruction, thus eliminating the noise in the vibration signals. The proposed method was applied to the simulation signals and diesel engine fault vibration signals, and a good denosing effect was obtained.