首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于Lipschitz指数熵的轴承故障检测方法
引用本文:徐晶,张秋杰,单净,姜萍.基于Lipschitz指数熵的轴承故障检测方法[J].科技导报(北京),2009,27(15):101-103.
作者姓名:徐晶  张秋杰  单净  姜萍
作者单位:黑龙江科技学院数学力学系,哈尔滨,150027 
基金项目:黑龙汪省教育厅科学技术研究项目 
摘    要:针对利用小波奇异点进行故障检测无法克服噪声影响的不足,提出采用Lipschitz指数熵作为特征进行故障检测.该方法以信号在小波域上分解形成的Lipschitz指数谱向量的熵值作为故障的诊断特征,建立了基于Lipschitz指数熵的故障检测模型,并提出了基于粒子群优化的特征阈值选择方法.将该方法同基于小波能量谱、小波包能量谱熵特征和小波奇异点检测的方法进行比较,实验结果表明采用Lipschitz指数熵作为特征都能有效克服噪声影响,在检测时间及检测率上较另外3种方法有显著提高.

关 键 词:故障检测  小波模极大值  奇异点  Lipschitz指数熵

Fault Detection for Bearings Based on Signal Lipschitz Spectrum Entropy
XU Jing,ZHANG Qiujie,SHAN Jing,JIANG Ping.Fault Detection for Bearings Based on Signal Lipschitz Spectrum Entropy[J].Science & Technology Review,2009,27(15):101-103.
Authors:XU Jing  ZHANG Qiujie  SHAN Jing  JIANG Ping
Institution:XU Jing,ZHANG Qiujie,SHAN Jing,JIANG Ping Department of Mathematics , Mechanics,Heilongjiang Institute of Science , Technology,Harbin 150027,China
Abstract:It is known that the wavelet-singular point detection-based method is sensitive to noises;to solve this problem,a method of fault detection for bearings based on wavelet transform modulus maximum Lipschitz spectrum entropy is proposed by combining wavelet analysis with entropy theory,including the detection scheme of bearing vibration faults and the threshold selection method based on swarm intelligence.The proposed method is compared with the methods based on wavelet energy spectrum and wavelet packet ener...
Keywords:fault detection  wavelet transform modulus maximum  singular point  Lipschitz spectrum entropy  
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号