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基于小波分析的滚动轴承的故障特征提取技术
引用本文:刘春光,谭继文,张驰.基于小波分析的滚动轴承的故障特征提取技术[J].机械工程与自动化,2010(2):127-128,131.
作者姓名:刘春光  谭继文  张驰
作者单位:青岛理工大学,山东,青岛,266033
摘    要:提出了一种新的滚动轴承电流信号的故障特征提取方法,利用电流传感器把测得的电流信号转变成电压信号,并对该信号进行小波降噪处理,有效地剔除噪声的干扰,提高了信号的信噪比.用小波分析提取降噪后电流信号的能量特征参数,以表征滚动轴承故障特征,在频谱图中建立起故障频带能量与滚动轴承状态的映射关系,为进一步应用神经网络进行故障诊断奠定了基础.

关 键 词:滚动轴承  小波分析  故障特征

Rolling Bearing's Breakdown Feature Extraction Technology Based on Wavelet Analysis
LIU Chun-guang,TAN Ji-wen,ZHANG Chi.Rolling Bearing''s Breakdown Feature Extraction Technology Based on Wavelet Analysis[J].Mechanical Engineering & Automation,2010(2):127-128,131.
Authors:LIU Chun-guang  TAN Ji-wen  ZHANG Chi
Affiliation:LIU Chun-guang,TAN Ji-wen,ZHANG Chi(Qingdao Technological University,Qingdao 266033,China)
Abstract:This article proposes a new method extracting the breakdown characteristic from rolling bearing's electric current signal.The electric current signal is transformed into voltage signal by an electric current sensor,and then the signal is processed by wavelet denoising,to enhance the signalto-noise ratio.The energy characteristic parameter of the denoised signal attributes the rolling bearing's breakdown characteristic.This paper establishes the relationship of the breakdown frequency band energy and the rol...
Keywords:rolling bearing  wavelet analysis  breakdown feature  
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