• CN:11-2187/TH
  • ISSN:0577-6686

›› 2012, Vol. 48 ›› Issue (19): 65-71.

• 论文 • 上一篇    下一篇

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滚动轴承故障特征提取的频谱自相关方法

明安波;褚福磊;张炜   

  1. 清华大学摩擦学国家重点实验室;第二炮兵工程大学二系
  • 发布日期:2012-10-05

Feature Extracting Method in the Rolling Element Bearing Fault Diagnosis:Spectrum Auto-correlation

MING Anbo;CHU Fulei;ZHANG Wei   

  1. State Key Laboratory of Tribology, Tsinghua University The 2nd Department, The Second Artillery Engineering University
  • Published:2012-10-05

摘要: 冲击调制是滚动轴承发生局部故障的重要特征,在频谱上表现为调制边频且能量主要集中在高频共振区非常不利于诊断。根据冲击序列在时域与频域具有相似冲击形式的特点,将时域的自相关概念引入频域,对滚动轴承内、外圈局部故障响应信号的频谱进行自相关分析。该方法将位于高频共振区的调制边频特征有效地转移到低频区,形成以故障特征频率为基频的谐频特征;对于内圈故障信号频谱自相关结果保持了载荷调制的边频。对6220型滚动轴承外圈和内圈点蚀故障信号的分析结果表明:频谱自相关分析在不设计带通滤波器选择共振频段时,分析过程更简洁,对内圈故障特征的提取比包络分析、倒谱分析及时域的自相关方法效果更好、抗噪能力更强、可信度更高,具有较高的工程应用价值。

关键词: 包络分析, 滚动轴承, 局部缺陷/故障, 频谱自相关, 特征提取

Abstract: As one of the most important features of the rolling element bearings with a localized defect/fault, the impulse characteristic is behaved as a series of side slopes, with the main impulse energy, located at two sides of the nature frequency in the spectrum, which is not convenient for the diagnosis. While the impulse series shared the similar character in the time and frequency domain, the auto-correlation method (SAC) is introduced to extract impulse character from the frequency domain and then used to analysis the frequency response of the vibration signals caused by a defect on the outer or inner race surface. Transferred from the sides of the nature frequency, the side slopes are present as harmonics of the characteristic frequency. When the defect located on the inner race, side slopes caused by the load modulation also remains around the harmonics. This method is also applied on the 6220 type rolling element bearing fault diagnosis. Leaving out of account of designing the nature band-pass filter, the extracting procedure is more convenient and simpler. It’s shown that fault character extracted by the proposed method is more clearly and believable than methods, such as:envelope analysis, cepstrum analysis, and the auto-correlation method in the time domain, etc, when applied on the inner race fault analysis with its iterative property. SAC is proved to be valid and effective which will be valuable for the engineering application.

Key words: Envelope analysis, Feature extracting, Localized defect/fault, Rolling element bearing, Spectrum auto-correlation

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