一种基于VMD与欧式距离的柴油机振动信号去噪方法

A Vibration Signal Denoising Method for Diesel Engine Based on VMD and Euclidean Distance

针对柴油机振动信号存在强背景噪声的问题,提出一种基于变分模态分解(VMD)与欧氏距离的去噪方法。首先建立多分量、非平稳、非高斯含噪仿真信号,采用VMD对其进行分解;然后计算各模态分量与信号概率密度函数之间的欧氏距离,以此为依据对主要模态分量进行重构,从而消除噪声干扰;最后与其他方法进行去噪效果比较,验证提出方法的有效性。应用该方法对发动机连杆轴承故障时的振动信号进行分析,结果表明:该方法的去噪效果显著,有助于提取柴油机连杆轴承磨损故障特征及故障诊断。

To solve the problem of loud background noise in vibration signal of diesel engine,the paper proposes a denoising method based on variational mode decomposition( VMD) and Euclidean distance. It firstly establishes multi-component,non-stationary,and non-Gauss and noisy simulation signal,and decomposes it with VMD. Then,it calculates the Euclidean distance between modal component and signal probability density function,and reconstructs the main modal component to eliminate noise interference. Finally,it verifies the validity of the method by comparing it with other denoising methods. The analysis on vibration signal of engine fault bearing with this method shows that this method contributes to fault feature extraction and fault diagnosis of engine connecting-rod bearings.