| 一种滚动轴承故障的诊断方法 |
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| 引用本文： | 王兴家,傅晓林,叶磊.一种滚动轴承故障的诊断方法[J].重庆工学院学报,2006,20(8):25-27. |
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| 作者姓名： | 王兴家 傅晓林 叶磊 |
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| 作者单位： | 重庆交通大学交通运输学院 重庆400074 |
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| 基金项目： | 重庆市教委科学技术研究资助项目（030405）. |
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| 摘 要： | 针对滚动轴承的故障特点,提出了一种小波包分析、粗糙集理论和神经网络相结合的轴承诊断方法.利用小波包变换对信号进行适当层次的小波包分解,对信号的频带进行精细的分割,以各个频带信号能量的分布情况作为故障特征量,形成故障诊断决策表;接着根据粗糙集理论进行处理得到更为简明的最优诊断规则;然后根据约简结果,建立了神经网络故障诊断系统;最后以诊断实例验证了该方法的有效性和可行性.
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| 关 键 词： | 滚动轴承 故障诊断 小波包分析 粗糙集 神经网络 |
| 文章编号： | 1671-0924（2006）08-0025-03 |
| 收稿时间： | 2006-04-28 |
| 修稿时间： | 2006年4月28日 |
A Diagnosis Method for Fault in Rolling Bearing |
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| WANG Xing-jia, FU Xiao-lin, YE Lei.A Diagnosis Method for Fault in Rolling Bearing[J].Journal of Chongqing Institute of Technology,2006,20(8):25-27. |
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| Authors: | WANG Xing-jia FU Xiao-lin YE Lei |
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| Affiliation: | School of Transportation, Chongqing Jiaotong University, Chongqing 400074, China |
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| Abstract: | In view of the fault characteristics of rolling bearings,a method for fault diagnosis of rolling bearing based on integration of wavelet packet analysis,rough sets theory and neural networks is proposed.The signal is decomposed in proper grades by using wavelet packet transform,frequency band of signal is divided precisely,distributed situation of signal energy of each bands are regarded as characteristic quantity,forming the decision table of fault diagnosis; concise diagnosis rules are obtained by processing of rough sets theory and fault diagnosis system based on neural networks is established.The validity and feasibility of this method has been demonstrated by the practical examples. |
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| Keywords: | rolling bearing fault diagnosis wavelet packet analysis rough sets neural networks |
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