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机械工程学报

机械工程学报 ›› 2017, Vol. 53 ›› Issue (3): 63-72.doi: 10.3901/JME.2017.03.063

• 机械动力学 • 上一篇    下一篇

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利用粒子滤波与谱峭度的滚动轴承故障诊断*

李宏坤, 杨蕊, 任远杰, 何德鲁, 郭斌   

  1. 大连理工大学机械工程学院 大连 116023
  • 出版日期:2017-02-05 发布日期:2017-02-05
  • 作者简介:

    作者简介：李宏坤(通信作者)，男，1974年出生，教授，博士研究生导师。主要研究方向为机械设备动态分析与故障诊断。

    E-mail：lihk@dlut.edu.cn

  • 基金资助:
    * 国家自然科学基金(51175057)和中央高校基本科研业务费专项(DUT14ZD204)资助项目; 20151210收到初稿，20161024收到修改稿;

Rolling Element Bearing Diagnosis Using Particle Filter and Kurtogram

LI Hongkun, YANG Rui, REN Yuanjie, HE Delu, GUO Bin   

  1. School of Mechanical Engineering， Dalian University of Technology， Dalian 116023
  • Online:2017-02-05 Published:2017-02-05

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摘要：

针对快速谱峭度在低信噪比情况下分析效果差的问题，提出应用粒子滤波的前处理降噪方法来提高信噪比，从而解决谱峭度受噪声干扰效果差的问题，进而提高滚动轴承故障诊断的成功率。建立振动信号的状态方程，提取原始信号的背景噪声，将其与状态方程之和作为观测方程。联立状态方程与观测方程来建立状态空间模型。采用粒子滤波对信号重新估计，得到新序列即是降噪之后的信号，结合快速谱峭度方法，获取最佳分析频带。并结合频谱分析得出故障频率。对比快速谱峭度与经验模式分解(Empirical mode decomposition， EMD)方法降噪的谱峭度分析诊断结果，证明所提方法的有效性。

关键词: 粒子滤波, 谱峭度, 状态空间, 滚动轴承

Abstract:

Fast Kurtogram has a low performance for the signal with low signal-to-noise ratio (SNR). Particle filter is used as preprocessing method to improve the SNR. It can be used to solve the problem about low performance and improve the fault diagnosis accuracy. State function of the vibration signal can be established. The background noise of origin signal can be extracted. State function and background noise are combined together as the observation function. State function together with observation function is used to construct the state space model. Particle filter is used to estimate new sequence for the noise-reduced signal. The optimal analysis band is obtained by using fast Kurtogram for the noise-reduced signal. Fault characteristic frequency can be obtained based on spectrum analysis. Comparison with fast Kurtogram and empirical mode decomposition filter as preprocessing method for fast Kurtogram, it can be concluded that the proposed method has good performance for rolling element bearing pattern recognition.

Key words: Kurtogram, particle filter, state space, rolling element bearing

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