摘要
局部均值分解方法(Local Mean Decomposition,LMD)是一种性能优越的旋转机械故障诊断的方法,它不仅可以准确地反映非平稳信号的时频分布,而且非常适合处理含有多分量成分的非平稳信号。但是由于LMD方法本身的缺陷,使得该方法存在着诸如端点效应的处理方法、迭代终止条件的确定等问题。在介绍LMD方法的基础上,分别以改进的“自适应延拓法”和“信息熵判据”解决以上两个问题,并结合仿真软件上验证改进结果。
Local mean decomposition(LMD)is an excellent method for fault diagnosis of rotating machinery.It can not only accurately reflect the time-frequency distribution of non-stationary signals,but also is very suitable for processing non-stationary signals with multi-component components.However,due to the limitations of LMD method,there are some problems such as the treatment of endpoint effect and the determination of iteration termination conditions.On the basis of introducing the LMD method,the above two problems are solved by the improved"adaptive continuation method"and"information entropy criterion"respectively,and the improved results are verified by simulation software.
作者
骆东松
裴阳
黄涛
LUO Dongsong;PEI Yang;HUANG Tao(Lanzhou University of Technology,Lanzhou 730050)
出处
《舰船电子工程》
2019年第10期204-207,共4页
Ship Electronic Engineering
关键词
LMD方法
端点效应
自适应延拓
迭代终止条件
信息熵判据
LMD method
endpoint effect
adaptive extension
iterated termination condition
information entropy criterion
