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《Journal of Propulsion Technology》 2011-01
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Gas-path component fault diagnosis based on gray relational analysis for aero-engine

ZHOU Jian-bo1,2,LU Feng1,HUANG Jin-quan1(1.Coll.of Energy and Power,Nanjing Univ.of Aeronautics and Astronautics,Nanjing 210016,China; 2.China Aviation Powerplant Research Inst.,Zhuzhou 412002,China)  
In order to improve the accuracy of aero-engine component fault diagnosis ability,a method of two layers fault diagnosis based on gray relational analysis was proposed.Particle swarm optimization(PSO) was introduced to optimize gray relational weighted index under various degradation to build standard fault pattern module which was used to diagnose as the first layer.Then two most possible fault patterns were selected for further diagnosis as the second layer based on gray slope relational analysis.Simulation showes that the method proposed is more simple and with less calculation compared to the single layer diagnosis,while the method has better accuracy than two layers fault diagnosis based on experiential gray relational analysis.
【CateGory Index】: V263.6
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【Citations】
Chinese Journal Full-text Database 4 Hits
1 LU Feng1,HUANG Jin-quan1,CHEN Yu1,2(1.College of Energy and Power Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;2.Guizhou Liyang Aero Engine Corporation,Guiyang 561102,China);Research on performance fault fusion diagnosis of aero-engine component[J];Journal of Aerospace Power;2009-07
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3 HAN Lei1,HONG Jie1,WANG Dong2(1.School of Jet Propulsion,Beijing Univ.of Aeronautics and Astronautics,Beijing 100083,China;2.Air Regional Representative Office in Fengtai Distric,Beijing 100074,China);Fault diagnosis of aero-engine bearings based on wavelet package analysis[J];Journal of Propulsion Technology;2009-03
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【Co-citations】
Chinese Journal Full-text Database 4 Hits
1 SHE Yunfeng,HUANG Jinquan,LU Feng (College of Energy and Power Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016);Performance Estimation of Gas Path of Turbo-shaft Engine Based on Kalman Filter[J];Journal of Changchun University of Science and Technology(Natural Science Edition);2010-03
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