| 支持向量机在燃气涡轮性能诊断中的应用 |
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| 引用本文： | 郝英,孙健国,杨国庆,白杰.支持向量机在燃气涡轮性能诊断中的应用[J].中国航空学报,2005,18(1):15-19. |
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| 作者姓名： | 郝英 孙健国 杨国庆 白杰 |
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| 作者单位： | [1]College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics,Nanjing 210016, China [2]Aeronautical Mechanics and Avionics Engineering College, Civil Aviation University of China,Tianjin 300300, China [3]Civil Aviation Administration of China , Beijing 100000, China |
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| 基金项目： | Foundation item： Civil Aviation Science Foundation of China （2003-193-22）;Science Foundation of Civil Aviation University of China （04-CAUC-11 E） |
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| 摘 要： | 由Vapnik统计学习理论得到的支持向量机是一种新的人工智能方法，它具有比人工神经网络更好的泛化性。文中构建了一种基于C—SVC的故障诊断模型（CBFDM），并采用5重交叉验证法来选择模型参数，该模型可给出3个最可能的故障原因。利用PW4000—94发动机巡航态影响系数矩阵产生仿真数据，对CBFDM研究结果表明，即使在噪声级别为正常情况下的3倍时，该模型诊断准确率仍超过93％。该诊断模型也可用于其它领域诊断问题。
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| 关 键 词： | 航空 航天推进系统 性能诊断 支持向量机 模型选择 |
| 文章编号： | 1000-9361（2005）01-0015-05 |
| 收稿时间： | 2004-06-07 |
| 修稿时间： | 2004-11-15 |
The Application of Support Vector Machines to Gas Turbine Performance Diagnosis |
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| Hao Ying;Sun JianGuo;Yang GuoQing;Bai Jie.The Application of Support Vector Machines to Gas Turbine Performance Diagnosis[J].Chinese Journal of Aeronautics,2005,18(1):15-19. |
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| Authors: | Hao Ying;Sun JianGuo;Yang GuoQing;Bai Jie |
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| Abstract: | SVMs(support vector machines) is a new artificial intelligence methodology derived from Vapnik's statistical learning theory, which has better generalization than artificial neural network. A C-support vector classifiers Based Fault Diagnostic Model (CBFDM) which gives the 3 most possible fault causes is constructed in this paper. Five fold cross validation is chosen as the method of model selection for CBFDM. The simulated data are generated from PW4000-94 engine influence coefficient matrix at cruise, and the results show that the diagnostic accuracy of CBFDM is over 93% even when the standard deviation of noise is 3 times larger than the normal. This model can also be used for other diagnostic problems. |
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| Keywords: | aerospace propulsion system performance diagnosis support vector machines model selection |
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