摘要
针对传统形态学滤波方法在提取高速列车轴箱轴承故障特征时过于依赖先验知识,结构元素相关参数(长度L和高度h)未结合信号特征做自适应选取的问题,文章在数学形态学滤波(Mathematical Filter,MF)、布谷鸟算法(Cuckoo Search Algorithm,CS)、实际工程应用方面做了深入研究。通过布谷鸟算法对结构元素的长度和高度进行自适应寻优,然后使用最优结构元素对信号进行处理,提取出信号中的冲击成分和故障特征,对比传统的解调方法可以发现该方法更准确、更快速。
Aiming at the problem that the traditional morphological filtering method is too dependent on a priori knowledge when extracting the fault characteristics of the axle box bearing of high-speed trains,and the relevant parameters of the structural elements(length L and height h)are not combined with the signal characteristics for adaptive selection.This thesis has made in-depth research on morphological filter,Cuckoo Search Algorithm and practical engineering applications.Through the cuckoo algorithm,the length and height of the structural elements are adaptively optimized,and then the signal is processed using the optimal structural elements to extract the shock components and fault features in the signal.Compared with traditional demodulation methods,this method can be found to be more accurate and faster.
作者
王茂辉
王涛
陈娇
夏伟
杨浩
吴震
WANG Maohui;WANG Tao;CHEN Jiao;XIA Wei;YANG Hao;WU Zhen(Institute of Intelligent Manufacturing and Automotive,Chongqing Technology and Business Institute,Chongqing 401520,China;State Key Laboratory of Traction Power,Southwest Jiaotong University,Chengdu 610031 Sichuan,China)
出处
《铁道机车车辆》
北大核心
2022年第4期46-51,共6页
Railway Locomotive & Car
基金
重庆工商职业学院校级项目(NDYB2020-13)。
关键词
高速列车
滚动轴承
形态学滤波
布谷鸟算法
峭度
High-speed train
rolling bearing
morphological filter
cuckoo algorithm
kurtosis
作者简介
王茂辉(1988-)男,助教。
