基于改进的G-SVSLMS与冗余提升小波的滚动轴承故障诊断
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摘要
噪声的干扰导致滚动轴承早期故障信号不易被发现,有效滤除噪声信号是实现设备早期故障诊断的关键。对基于Sigmoid函数的变步长自适应算法(G-SVSLMS)进行相关性改进,并将该方法应用于振动信号的初始降噪。根据冗余提升原理对一次降噪后信号进行再降噪,从而实现设备振动信号的有效的提取。实验及工程数据分析表明该复合方法的应用效果明显高于单一滤波方法。
The early fault signal of rolling bearing is not easy to be discovered,effective filtering of the noise signal is the key to early fault diagnosis. The correlation of variable step size adaptive algorithm is improved based on Sigmoid function and the algorithm is used to filter the original signal,according to the principle of redundant lifting to reduce the noise the signal again,So as to realize the effective extraction of early fault signals. The results of experiments and engineering data show that this method is more effective than single filtering method.
The early fault signal of rolling bearing is not easy to be discovered,effective filtering of the noise signal is the key to early fault diagnosis. The correlation of variable step size adaptive algorithm is improved based on Sigmoid function and the algorithm is used to filter the original signal,according to the principle of redundant lifting to reduce the noise the signal again,So as to realize the effective extraction of early fault signals. The results of experiments and engineering data show that this method is more effective than single filtering method.
引文
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[2]郭玉荣,崔玲丽,高立新,等.冗余提升小波的最优分解层数的确定[J].机械设计与制造,2014(11):147-149.GUO Y R,CUI L L,GAO L X,et al.The Determination of Optimal Decomposition Level of Redundant Lifting Wavelet[J].Mechanical Design&Manufacturing,2014(11):147-149.
[3]阳子婧.基于提升小波的轴承微弱故障特征提取方法的研究[D].北京:北京工业大学,2012.
[4]DRAGOMIRETSKIY K,ZOSSO D.Variational Mode Decomposition[J]. TEEE Transactions on Signal Processing,2014,62(3):531-544.
[5]WANG Y,MARKERT R,XIANG J,et al.Research on Variational Mode Decomposition and Its Application in Detecting Rub-impact Fault of the Rotor System[J]. Mechanical Systems and Signal Processing,2015,60:243-251.
[6]路翠华,李国林,谢鑫,等.基于相关特性的改进G-SVSLMS算法[J].电讯技术,2013(10):1285-1288.LU C H,LI G L,XIE X,et al.Improved G-SVSLMS Algorithm Based on Correlation Characteristics[J].Telecommunication Technology,2013(10):1285-1288.
[7]钱林,康敏,傅秀清,等.基于VMD的自适应形态学在轴承故障诊断中的应用[J].振动与冲击,2017,36(3):227-233.QIAN L,KANG M,FU X Q,et al.Application of Adaptivemorphology in Bearing Fault Diagnosis Based on VMD[J].Journal of Vibration and Shock,2017,36(3):227-233.
[8]张红梅,韩万刚.一种新的变步长LMS自适应滤波算法研究及其应用[J].仪器仪表学报,2015,36(8):1822-1830.ZHANG H M,HAN W G.A New Variable Step LMS Algorithm and Its Application[J]. Chinese Journal of Scientific Instrument,2015,36(8):1822-1830.
[9]TOMIC M,SERSIC D.Adaptive Edge-preserving Denoising by Point-wise Wavelet Basis Selection[J]. IET Signal Processing,2012,6(1):1-7.
[10]刘自然,文金选,何涛.小波阈值降噪技术在齿轮箱振动信号处理中的应用研究[J].现代制造工程,2010(4):75-77.LIU Z R,WEN J X,HE T.Application of Wavelet Threshold De-noising Technique in the Gearbox Vibration Signal Processing[J]. Modern Manufacturing Engineering,2010(4):75-77.