Abstract:The traditional time-frequency analysis method can not effectively process non-stationary signals. The empirical mode decomposition (EMD) is very suitable for processing the non-stationary signals, but the results may appear pseudo-intrinsic mode functions (IMF) and insensitive intrinsic mode functions. For the lack of EMD, the method combined with energy threshold law and sensitive IMF select wears to identify the true IMF and sensitive IMF is proposed, then the spectrum transformation of IMF satisfying these two conditions and the diagnostic results are given. The fault information can be clearly presented on spectrogram. The improved EMD decomposition is applied to the fault diagnosis of rolling bearing to prove the feasibility and accuracy of this method.
[1]蔡艳平,李艾华,石锁林,等.基于EMD与普峭度的滚动轴承故障检测改进包络谱分析[J].振动与冲击,2011, 30(2):167-172.
[2]杨宇,于德介,程军圣.基于EMD与神经网络的滚动轴承诊断方法[J].振动与冲击,2005, 24(1):85-88.
[3]程军圣,于德介.基于时—能密度分析的滚动轴承故障诊断[J].振动与冲击, 2001, 20(3):79-81.
[4]彭志科,何永勇,卢青,等.用小波时频分析方法研究发电机碰摩故障特征[J].中国电机工程学报,2003,23(5):75-79.
[5]徐玉秀, 邢 刚, 原培新.基于专家系统与神经网络集成的故障诊断的应用研究[J]. 振动与冲击, 2001, 20(1):41-43.
[6]钟佑明,秦树人,汤宝平.一种振动信号新变换法的研究[J].振动工程学报, 2002, 15(2):233-237.
[7]Huang N E, Shen Z, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time analysis[J]. Proc Roy Soc Lond A, 1998, 454(1971):903-995.
[8]Cheng J S, Yu D J, et al. App lication of frequency family separation method based upon EMD and local Hilbertenergy spectrum method to gear fault diagnosis [J]. Mechanism and Machine Theory, 2008, 43( 6):712-723.
[9]程军圣,于德介,杨宇.基于SVM和EMD包络谱的滚动轴承故障诊断方法[J].系统工程理论与实践, 2005, (9):131-136.
[10]罗洁思,于德介,彭富强.基于EMD的多尺度形态学解调方法及其在机械故障诊断中的应用[J].振动与冲击, 2009, 28(11):84-86.
[11]杨宇,于德介,程军圣, 等.经验模态分解(EMD)在滚动轴承故障诊断中的应用[J]. 湖南大学学报(自然科学版), 2003, 30(5):25-28.
[12]杨宇,于德介,程军圣.基于Hilbert边际谱的滚动轴承故障诊断方法[J].振动与冲击, 2005, 24(1):70-72.