极值点分组模式分解的齿轮局部断齿故障试验  

Test for partial breaking of gear tooth based on extreme point packet mode decomposition

作　　者：陈根[1] 王海宝[1] 逯全波 岳以翛 晏娟 郑岩 谭欣 CHEN Gen;WANG Haibao;LU Quanbo;YUE Yixiao;YAN Juan;ZHENG Yan;TAN Xin(School of Electronic ＆ Information Engineering, Chongqing Three Gorges University, Chongqing 404020, Chin)

机构地区：[1]重庆三峡学院电子与信息工程学院,重庆404020

出　　处：《矿山机械》2018年第4期55-60,共6页Mining & Processing Equipment

基　　金：重庆市教育委员会科学技术研究项目(KJ1601031);重庆市轻合金材料与加工工程技术研究中心资助

摘　　要：齿轮振动信号中含有大量的噪声。通过用极值点分组模式分解(Extreme Point Packet Mode Decomposition,EPPMD)的方法提取出齿轮局部断齿故障特征,验证了EPPMD的有效性。该方法首先提取出齿轮振动信号极值点,并将极值点进行分组,再用三次样条函数拟合出所有分组极值点的曲线,求取其均值曲线,最后像经验模态分解(EMD)一样求取出各个IMF分量,进行IMF的频谱分析诊断故障。There is a lot of noise in the vibration signal of the gear.In the paper,the extreme point packet mode decomposition（EPPMD）method was used to extract the fault characteristics of partial breaking of gear tooth,which verified the validity of EPPMD.In the method,the extreme points of the gear vibration signal were extracted firstly,and then the extreme points were packeted.After that,the curves of all the packeted extreme points were fitted by cubic spline function,and the curves of mean value were obtained.Finally,each IMF component was extracted like empirical mode decomposition（EMD）,and the IMF spectra were analyzed to diagnose the fault.

关 键 词：故障诊断 齿轮 极值点分组模式分解(EPPMD) EMD 

分 类 号：TH165.3[机械工程—机械制造及自动化]