一种改进的Hilbert-Huang变换方法及其应用

中文摘要: 针对希尔伯特-黄变换方法中存在的端点效应和虚假模态分量等问题，分析其产生原因，提出一种基于边界极值均值延拓的端点效应抑制与虚假模态分量剔除相结合的改进方法。该方法首先根据信号两侧端点和其临近极值点的特性，对包络线在信号两端点处的位置进行约束，从而改善包络线拟合结果，在一定程度上抑制端点效应问题的产生。然后，依据各模态分量间的正交性原理，通过虚假模态分量剔除算法，选取能够反映信号特征的敏感模态分量，以保证分析的准确性。通过数值仿真，验证了所提方法的有效性。最后，应用于发动机异响故障诊断中，诊断结果表明该方法有效抑制了传统希尔伯特-黄变化方法的端点效应和虚假模态问题，可有效提取发动机异响信号的故障特征。
Abstract:Aiming at the shortcoming of Hilbert-Huang transform method,where the end effect and false intrinsic mode function issue exist during its application,based on the analysis of the reasons of these problems,an improved Hilbert-Huang transform method was proposed by using boundary extreme mean extension and false mode selecting approach.Firstly,according to the characteristics of the signal endpoint and its adjacent extreme points,the value of the envelope at the two ends of the signal was estimated,and the estimated value were added to the extreme value sequence,therefore the data extension was reasonable and the end effect could be solved.Then,the false mode selecting algorithm based on the orthogonality of each intrinsic mode function was used to select sensitive mode functions.The validity of this improved method was verified by a simulation signal analysis.Finally,the method was applied into engine abnormal sound fault diagnosis.The results showed that the improved method has a good result in dealing with the shortcoming of traditional Hilbert-Huang transform and the fault feature of engine abnormal sound signal can be obtained effectively.