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Least Squares Support Vector Machine Based Real-Time Fault Diagnosis Model for Gas Path Parameters of Aero Engines |
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| Authors: | WANG Xu-hui HUANG Sheng-guo WANG Ye LIU Yong-jian SHU Ping |
| Institution: | 1. College of Civil Aviation,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China 2. General Civil Aviation Administration of China,Center of Aviation Safety Technology Aviation Safety Institute Technology Lab,Beijing 100028,China;General Civil Aviation Administration of China,Center of Aviation Safety Technology Aviation Safety Instit 3. General Civil Aviation Administration of China,Center of Aviation Safety Technology Aviation Safety Institute Technology Lab,Beijing 100028,China |
| Abstract: | Least squares support vector machine (LS-SVM) is applied in gas path fault diagnosis for aero engines.Firstly,the deviation data of engine cruise are analyzed.Then,model selection is conducted using pattern search method.Finally,by decoding aircraft communication addressing and reporting system (ACARS) report,a real-time cruise data set is acquired,and the diagnosis model is adopted to process data.In contrast to the radial basis function (RBF) neutral network,LS-SVM is more suitable for real-time diagnosis of gas turbine engine. |
| Keywords: | Engine diagnosis Gas path Least squares support vector machine Pattern search |
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