摘要
为了抑制电网工频干扰对电流信号的影响,通过对复杂电流信号奇异值分解特性和小波熵分离特性的研究,提出一种高精度故障特征分离方法。该方法先结合SVD较强的消噪特性,对复杂电流信号做去噪处理;再对去噪后的电流信号,结合小波熵法进行故障特征分离。研究结果表明,该方法可以有效剔除电网工频的干扰,实现微弱信号的特征提取。
To restrain the effect of power frequency interference on current signals,this paper studies the characteristics of singular value decomposition（SVD） and wavelet entropy and proposes a high-precision separation method of faults,in which the strong denoising capability of SVD is used to effectively eliminate the complex nose signal and the method of wavelet entropy is used to separate the fault current signals.The results show that the method can be used to effectively eliminate the power frequency interference and detect the weak signal.
出处
《机械制造与自动化》
2017年第4期186-188,194,共4页
Machine Building & Automation
基金
甘肃省青年科技基金计划(1506RJYA139)
关键词
机电系统
小波熵
电流信号
奇异值分解
故障诊断
motor system
wavelet entropy
current signals
singular value decomposition
fault diagnosis
