Several Key Issues of Local Mean Decomposition for the Mechanical Fault Diagnosis
WANG Yan-xue1,2 HE Zhengjia2 ZI Yanyang2 YUAN Jing2
1.Guilin University of Electronic Technology, Guilin 541004;2. State Key Laboratory for Manufacturing and System Engineering, Xi’an Jiaotong University, Xi’an 710049
摘要如何有效地从振动信号中提取有用信息成分一直以来都是故障诊断领域研究的热点。局部均值分解(Local Mean Decomposition, LMD)是一种新的信号自适应分解方法。本文研究基于LMD的瞬时频率求解、时频分析及其故障诊断的应用。LMD的时频分析方法成功提取出实验室转子碰摩特征以及实际低速变载轧机齿轮局部故障信息，这证实了方法的有效性。
Abstract：Extracting the useful component from the vibration signals is always the hot issue in the field of fault diagnosis. Local mean decomposition (LMD) is a novel signal decomposition method in the time-frequency domain. This paper discusses the calculation of the instantaneous frequency and instantaneous time-frequency spectrum. Then LMD is applied to the fault diagnosis of rubbing rotor and gearbox in a mill. Results demonstrate the effectiveness of the LMD for the early detection of faults, and it may find wide applications for machine surveillance in the near future.
王衍学;;何正嘉;訾艳阳;袁静. 基于LMD的时频分析方法及其机械故障诊断应用研究[J]. , 2012, 31(9): 9-12.
WANG Yan-xue;HE Zhengjia ZI Yanyang YUAN Jing. Several Key Issues of Local Mean Decomposition for the Mechanical Fault Diagnosis . , 2012, 31(9): 9-12.
2012, Vol. 31 
