An Improved LMD-based Denoising Algorithm for Fault Diagnosis of Rotating Machinery

doi:10.3969/j.issn.1006-1335.2015.02.036

›› 2015, Vol. 35 ›› Issue (2): 160-164.DOI: 10.3969/j.issn.1006-1335.2015.02.036

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An Improved LMD-based Denoising Algorithm for Fault Diagnosis of Rotating Machinery

Received:2014-08-20 Revised:2014-09-29 Online:2015-04-18 Published:2015-04-18

LMD滤噪算法及在旋转机械转子故障诊断中的应用

杨梅¹,陈思汉¹,余建波²

（ 1. 上海大学机电工程与自动化学院，上海 200027；
2. 山东省特种设备检验研究院，济南 250101；
3. 同济大学机械与能源工程学院，上海 200092 )

通讯作者: 杨梅

Abstract

摘要：

利用噪声统计特性及局部均值分解算法(local mean decomposition, LMD)在信号分解过程中的自适应性，提出了一种新的基于LMD的自适应滤噪算法。该算法完全由数据驱动，可对信号自适应降噪，并将降噪后的信号分解为若干个瞬时频率具有物理意义的 PF (Product function)分量。重构的信号可有效提高功率谱故障诊断的性能。通过对2种非平稳信号的仿真实验及在实际运行状态下采集的旋转机械转子振动信号降噪的应用，结果表明提出的算法降噪性能优于中值降噪、均值降噪、小波降噪、EMD软阀值降噪等典型滤噪算法。该算法也可在频域有效地用于旋转机械转子故障的诊断。

关键词: 振动与波, 旋转机械, 故障诊断, 局部均值分解, 自适应滤噪

CLC Number:

TH113.1

杨梅1，陈思汉 1，吴昊 2，余建波 3. LMD滤噪算法及在旋转机械转子故障诊断中的应用[J]. 噪声与振动控制, 2015, 35(2): 160-164.

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An Improved LMD-based Denoising Algorithm for Fault Diagnosis of Rotating Machinery

LMD滤噪算法及在旋转机械转子故障诊断中的应用

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