Denoising method for electrostatic monitoring signal of roller bearing based on spectrum interpolation and difference spectrum of singular value
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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.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.
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