中国机械工程 ›› 2010, Vol. 21 ›› Issue (9): 1058-1061.

• 信息技术 • 上一篇    下一篇

轴承故障动态检测的迭代交叉信息熵方法

丁建明1;林建辉1;尹燕莉2;杨强1
  

  1. 1.西南交通大学牵引动力国家重点实验室,成都,610031
    2.重庆大学机械传动国家重点实验室,重庆,400030
  • 出版日期:2010-05-10 发布日期:2010-05-19
  • 基金资助:
    国家重点基础研究发展计划资助项目(2007CB714706,2007CB714701);“十一五”国家科技支撑计划资助项目(2008BAQG0010) 
    National Program on Key Basic Research Project (973 Program)(No. 2007CB714706,2007CB714701);
    The National Key Technology R&D Program(No. 2008BAQG0010)

Dynamic Detection of Roll Bearing Faults Using Iterative Cross Entropy

Ding Jianming1;Lin Jianhui1;Yin Yanli2;Yang Qiang1
  

  1. 1.State Key Laboratory of Traction Power,Southwest Jiaotong University,Chengdu, 610031
    2.State Key Laboratory of mechanical transmission,Chongqing University,Chongqing,400030
  • Online:2010-05-10 Published:2010-05-19
  • Supported by:
     
    National Program on Key Basic Research Project (973 Program)(No. 2007CB714706,2007CB714701);
    The National Key Technology R&D Program(No. 2008BAQG0010)

摘要:

将小波包变换和迭代交叉信息熵有机结合,从检测信号信息量差异性的角度出发,提出一种设备故障动态检测的新方法。该方法的核心是动态选取时间相邻的两帧振动信号,对两帧信号作小波包分解得到等频宽的分解信号,计算分解信号不同时间段的能量,得到信号的尺度分段时间能量矩阵,以尺度分段时间能量矩阵作为一种信息的划分,计算两帧信号的迭代交叉熵,用熵值来表征信号的差异性而检测出故障。检测实例验证了该方法的有效性,检测的实时性好、准确性高。

关键词:

Abstract:

A new dynamic detection method for roll bearing faults was proposed based on wavelet packet and cross entropy from the angles of information differences of detection signals. Two vibration signals during adjacent time were dynamically selected and transformed by wavelet packet to get sub-band signals with equal frequency bandwidth, Interval energies were computed along time axis in different sub-band signals to construct energy matrix called scales-sub-time, The information differences between two vibration signals were got through iterative symmetrical cross entropy in the energy distribution of two scales-sub-time matrixes and applied to detect bearing faults. A lot of detection examples prove the effectiveness of the way, with high real-time and high accuracy.

Key words: bearing fault, wavelet packet decomposition, scales-sub-time energy matrix, iterative cross entropy, dynamic detection

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