| Application of fuzzy SOFM neural network and rough set theory on fault diagnosis for rotating machinery | |
| Jiang, DX ; Li, K ; Zhao, G ; Diao, JH | |
| 2010-05-10 ; 2010-05-10 | |
| 会议名称 | ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 3, PROCEEDINGS ; 2nd International Symposium on Neural Networks ; Chongqing, PEOPLES R CHINA ; Web of Science ; INSPEC |
| 关键词 | Computer Science, Theory & Methods |
| 中文摘要 | This paper presents a new method that applies fuzzy logic, rough set theory and SOFM neural network to rotating machinery fault diagnosis. In this method, firstly, relationships between the fault causations and fault symptoms are established by fuzzy logics. Then the Rough Set Theory (RST) is applied to obtain a minimal sufficient subset of features, which is helpful to simplify the structure of neural network. Next, the 2-dimension output mapping of the standard fault samples (training samples) is obtained by a self-organizing neural network. Finally, we input some simulation samples (testing samples) and gain the reasonable conclusions by comparison between the two output mappings. Experimental results have demonstrated the effectiveness of this method and its nice prospect of applying to rotating machinery fault diagnosis. |
| 会议录出版者 | SPRINGER-VERLAG BERLIN ; BERLIN ; HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY |
| 语种 | 英语 ; 英语 |
| 内容类型 | 会议论文 |
| 源URL | [http://hdl.handle.net/123456789/19666]  |
| 专题 | 清华大学 |
| 推荐引用方式 GB/T 7714 | Jiang, DX,Li, K,Zhao, G,et al. Application of fuzzy SOFM neural network and rough set theory on fault diagnosis for rotating machinery[C]. 见:ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 3, PROCEEDINGS, 2nd International Symposium on Neural Networks, Chongqing, PEOPLES R CHINA, Web of Science, INSPEC. |
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