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| 基于小波分形和一类辨识的航空发动机故障诊断 |
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罗俊1, 何立明2, 陈超3
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1.西安空军工程大学工程学院 陕西西安710038;2.西安空军工程大学工程学院 陕西西安710039;3.西安空军工程大学工程学院 陕西西安710040
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| 摘要: |
| 在支持向量机理论的基础上,针对支持向量机的二类辨识传统,引入了基于支持向量机的一类辨识理论。设计了航空发动机几种典型故障的一类分类器,使得发动机的故障诊断更加简单可行。同时,将小波分形方法引入到航空发动机振动信号的特征提取中。通过对航空发动机典型故障的成功诊断,证明了该方法的有效性。 |
| 关键词: 航空发动机 一类辨识+ 支持向量机+ 小波分形+ 故障诊断 |
| DOI： |
| 分类号:V263.6 |
| 基金项目: |
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| Aeroengine fault diagnoisis based on one-class classification and wavlet-fractal |
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LUO Jun1, HE Li-ming2, CHEN Chao3
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1.Engineering Inst.,Air Force Engineering Univ.,Xi’an 710038,China;2.Engineering Inst.,Air Force Engineering Univ.,Xi’an 710039,China;3.Engineering Inst.,Air Force Engineering Univ.,Xi’an 710040,China
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| Abstract: |
| Based on SVM(support vector machines) theory,one-class identification theory was introduced.Several classification models,which make the aeroengine fault diagnosis become more simple and viable,were designed based on one-class identification theory.In addition,wavlet-fractal was used to extract feature of aeroengine vibration data.Successful application has been achieved to detect several typical fault of aeroengine.The results show that the one class identification can provide a new effective technology to reveal fault of aeroengine. |
| Key words: Aeroengine One-class identification+ SVM+ Wavlet-fractal Fault diagnosis |
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