DocumentCode :
497345
Title :
Health Diagnosis for Aircraft Based on EMD and Neural Network
Author :
Cui, Jianguo ; Zheng, Xinqi ; Li, Ming ; Li, Zhonghai ; Liu, Dong
Author_Institution :
Autom. Coll., Shenyang Inst. of Aeronaut. Eng., Shenyang, China
Volume :
1
fYear :
2009
fDate :
11-12 April 2009
Firstpage :
677
Lastpage :
680
Abstract :
To effectively diagnose the aircraft structure components fatigue damages, a new kind of health diagnosis approach for the aircraft, based on experience modal decomposition (EMD) and probabilistic neural network (PNN), is proposed in this paper. The advanced acoustic emission (AE) technique is used to monitor the aircraft stabilizer health state and get the AE information. And the AE information from the aircraft stabilizer is decomposed into the limited inherent modality function (IMF) by the EMD, which is quite fit for dealing with the non-linear and non-steady signal. The IMF energy is extracted to construct the eigenvectors. Then the health status of the aircraft can be diagnosed with the eigenvectors by PNN health monitor. Experiments show that this method can effectively monitor the fatigue crack of the aircraft stabilizer. It presents a new approach to diagnose effectively health state of aircraft structure components.
Keywords :
acoustic signal processing; aerospace components; aircraft; condition monitoring; eigenvalues and eigenfunctions; fatigue cracks; fault diagnosis; mechanical engineering computing; neural nets; advanced acoustic emission technique; aircraft stabilizer; aircraft structure components fatigue damages; eigenvectors; experience modal decomposition; fatigue crack; health diagnosis; health diagnosis approach; non-linear signal; non-steady signal; probabilistic neural network; Aerospace engineering; Aircraft manufacture; Aircraft propulsion; Educational institutions; Frequency domain analysis; Monitoring; Neural networks; Signal analysis; Signal processing; Wavelet domain; AE; EMD; IMF energy; PNN; health diagnosis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on
Conference_Location :
Zhangjiajie, Hunan
Print_ISBN :
978-0-7695-3583-8
Type :
conf
DOI :
10.1109/ICMTMA.2009.554
Filename :
5203063
Link To Document :
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