基于变分模态分解和广义Warblet变换的齿轮故障诊断  

Gear Fault Diagnosis based on VMD and Generalized Warblet Transform

作　　者：杨琳 王衍学[1] 何水龙[1] Yang Lin;Wang Yanxue;He Shuilong(School of Mechanical and Electrical Engineering,Guilin University of Electronic Technology,Guilin 541004,China)

机构地区：[1]桂林电子科技大学机电工程学院,广西桂林541004

出　　处：《机械传动》2018年第7期157-161,共5页Journal of Mechanical Transmission

基　　金：国家自然科学基金(51475098;61463010);广西自然科学杰出青年基金(2016GXNSFFA380008);广西高校海外"百人计划";广西高校高水平创新团队及"卓越学者"计划;广西制造系统与先进制造技术重点实验室主任课题(1514030001Z;1638012004Z)

摘　　要：变分模态分解(Variational mode decomposition,VMD)作为一种新的信号处理方法,摆脱了传统自适应分解方法中的模态混叠、边界效应等缺陷,具有抗噪鲁棒性强、分解效率高等优点。广义Warblet变换(Generalized warblet transform,GWT)是一种新型参数化的信号时频分析方法,适合分析单分量瞬时频率呈周期或非周期变化的非平稳信号。融合VMD多模态信号分解优势以及广义Warblet解调性能,提出了一种基于VMD和GWT变换的齿轮故障诊断新方法,并通过实验分析验证了该方法的有效性。The variational mode decomposition（ VMD） is a novel self-adaptive decomposition method without shortcomings of traditional adaptive decomposition methods,such as mode mixing and end effects. The VMD has the advantages of strong anti-noise robustness and high efficiency. The generalized Warblet transform（ GWT） is suitable for analyzing modulated signal with periodic or nonperiodic change of instantaneous frequency. Considering the advantages of VMD in decomposing signal into sub-signals,a new method is proposed to detect gear fault based on GWT and VMD in this work. The VMD can be considered as the signal preprocessing prior to GWT. The results of the experimental analysis have demonstrated the effectiveness of the proposed method.

关 键 词：变分模态分解 广义Warblet变换 齿轮 故障诊断 

分 类 号：TH132.41[机械工程—机械制造及自动化]