| 旋转机械故障可视化方法的研究 |
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| 引用本文： | 雷文平,黄士涛,石金彦.旋转机械故障可视化方法的研究[J].武汉理工大学学报,2003,25(4):55-57. |
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| 作者姓名： | 雷文平 黄士涛 石金彦 |
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| 作者单位： | 郑州大学
(雷文平，黄士涛)，郑州大学(石金彦) |
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| 摘 要： | 将高维的各种故障样本数据经降维和聚类后，在二维的平面上显示出来，使每种类别的故障占据平面的不同区域，从而达到故障可视的目的。据此能很好地对新的样本进行故障识别，还可以对故障的发展趋势进行预测。采用Ko—honen的自组织神经网络方法可以对故障样本数据进行降维和聚类。实例说明了该方法的正确性。
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| 关 键 词： | 故障诊断 可视化 自组织映射 模式识别 |
| 文章编号： | 1671-4431(2003)04-0055-03 |
| 修稿时间： | 2002年10月14 |
Study on Visualization of Fault Events for Rotary Machinery |
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| Lei Wenping Huang Shitao Shi Jinyan Lei Webping: Master Student,School of Mechanical Engineering,ZZU,Zhengzhou ,China.Study on Visualization of Fault Events for Rotary Machinery[J].Journal of Wuhan University of Technology,2003,25(4):55-57. |
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| Authors: | Lei Wenping Huang Shitao Shi Jinyan Lei Webping: Master Student School of Mechanical Engineering ZZU Zhengzhou China |
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| Abstract: | Visualization of the faults, a new method of diagnosing the faults of rotary machine is presented in this paper. In order to show data of machine faults with multi-dimension characteristics in a plane, we should reduce multi dimension data to two dimension and cluster the data. That is fault visualization. The method of Kohonen's Self Organizing Map is used to reduce and cluster sample data in the paper. The visualization of the faults is valuable for practical purposes by making the distinguishing of the faults simpler and easier. The validity of the method is proved by an example. |
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| Keywords: | fault diagnosis visualization self organizing map pattern recognize |
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