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基于谱插值和奇异值差分谱的滚动轴承静电监测信号去噪方法
引用本文:张营,左洪福,佟佩声,陈志雄,白芳.基于谱插值和奇异值差分谱的滚动轴承静电监测信号去噪方法[J].航空动力学报,2014,29(8):1996-2002.
作者姓名:张营  左洪福  佟佩声  陈志雄  白芳
作者单位:南京航空航天大学 民航/飞行学院, 南京 210016;南京航空航天大学 民航/飞行学院, 南京 210016;南京航空航天大学 民航/飞行学院, 南京 210016;南京航空航天大学 民航/飞行学院, 南京 210016;南昌航空大学 飞行器工程学院, 南昌 330063;南京航空航天大学 民航/飞行学院, 南京 210016
基金项目:国家自然科学基金与中国民航联合基金重点项目(60939003);国家自然科学基金与中国民航联合基金(61179058)
摘    要:采用静电传感器进行滚动轴承故障监测实验研究.针对滚动轴承静电监测中各种强噪声、故障特征难以提取的问题,提出了基于谱插值和奇异值差分谱的联合去噪方法.首先采用谱插值抑制工频干扰,然后将所得信号构造Hankel矩阵,求取奇异值差分谱并自动确定有用分量个数,最后重构信号.仿真和实验结果表明:仅采用奇异值差分谱或者小波去噪方法,无法从含有强工频干扰的信号中提取有用成分;所提出的方法相比较谱插值和小波去噪方法能够凸显早期故障特征频率.

关 键 词:滚动轴承  静电监测  谱插值  工频干扰  奇异值差分谱
收稿时间:2013/5/19 0:00:00

Denoising method for electrostatic monitoring signal of roller bearing based on spectrum interpolation and difference spectrum of singular value
ZHANG Ying,ZUO Hong-fu,TONG Pei-sheng,CHEN Zhi-xiong and BAI Fang.Denoising method for electrostatic monitoring signal of roller bearing based on spectrum interpolation and difference spectrum of singular value[J].Journal of Aerospace Power,2014,29(8):1996-2002.
Authors:ZHANG Ying  ZUO Hong-fu  TONG Pei-sheng  CHEN Zhi-xiong and BAI Fang
Institution:College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;School of Aircraft Engineering, Nanchang Hangkong University, Nanchang 330063, China;College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Abstract:Electrostatic sensor was implemented in roller bearing experiment investigation to monitor defects. In consideration of various strong noises involved in the electrostatic monitoring of roller bearings and the difficulty to obtain defect characteristics, a united denoising method was put forward based on spectrum interpolation and difference spectrum of singular value. Firstly, the spectrum interpolation was used to eliminate the power line interference; then the resultant signal was used to construct Hankel matrix; the number of useful components was automatically selected based on the difference spectrum of singular value, and finally the signal was reconstructed. Simulation and practical experiments show that the useful components of the signals involving high power line interference cannot be extracted by performing difference spectrum of singular value method or the wavelet denoising method; the presented denoising method can highlight the defect characteristic frequency in early stage more effectively than the spectrum interpolation and wavelet denosing method.
Keywords:roller bearing  electrostatic monitoring  spectrum interpolation  power line interference  difference spectrum of singular value
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