Introduction.- Failure pattern and corresponding mechanism analysis of liquid Rocket engines (LRE).- Analysis method of failure model for LRE.- Failure characteristics analysis of LRE.- Fault diagnosis of LRE based on artificial neural net.- Fault diagnosis method based on Wavelet transform.- Fault diagnosis method based on artificial immune system.- Fault diagnosis method based on fuzzy theory.- Fault analysis and diagnosis method based on statistical learning theory.- Fault diagnosis method based on hide Markov model.- Fault prediction method of LRE.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Wei Zhang received the specialized M.S. degrees in mechanics from Xi'an Jiaotong University in 1995, and the Ph.D. degrees in ordnance science and technology from Xi'an High-tech institute, Shaanxi, China, in 2003. He is currently a Professor of aeronautical science and technology in Xi'an High-tech institute, Shaanxi, China. His research interests include non-destructive testing technology, condition monitoring, fault diagnosis and signal processing. He is one of the fifth executive directors of the fault diagnosis professional committee in the Chinese Society of Vibration Engineering. The funding of the projects he has involved or been responsible for has exceeded $ 1000,000. He has published 3 books and about 150 papers. Many papers have been indexed by SCI and EI.
Gan Tian received the B.S. degrees in mechanics from Xi'an High-tech institute, Shaanxi, China, in 2003, and the specialized M.S. degrees in aeronautical and astronautical science and technology from Xi'an High-tech institute, Shaanxi, China, in 2009. He is currently a Lecturer of aeronautical science and technology in Xi'an High-tech institute, Shaanxi, China. His research interests include non-destructive testing technology and fault diagnosis. Zhigao Xu received the B.S. degrees in mechanics from Xi'an High-tech institute, Shaanxi, China, in 1999, the specialized M.S. degrees in aeronautical and astronautical science and technology from Xi'an High-tech institute, Shaanxi, China, in 2003 and the Ph.D. degrees in ordnance science and technology from Xi'an High-tech institute, Shaanxi, China, in 2009. He is currently an Associate Professor of aeronautical science and technology in Xi'an High-tech institute, Shaanxi, China. His research interests include fault diagnosis and signal processing. Zhengwei Yang received the B.S. degrees in mechanics from Xi'an High-tech institute, Shaanxi, China, in 2005, and the Ph.D. degrees in ordnance science and technology from Xi'an High-tech institute, Shaanxi, China, in 2011. He is currently a Lecturer of aeronautical science and technology in Xi'an High-tech institute, Shaanxi, China. His research interests include non-destructive testing technology, condition monitoring, and signal processing.Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book concentrates on the subject of health monitoring technology of Liquid Rocket Engine (LRE), including its failure analysis, fault diagnosis and fault prediction. Since no similar issue has been published, the failure pattern and mechanism analysis of the LRE from the system stage are of particular interest to the readers. Furthermore, application cases used to validate the efficacy of the fault diagnosis and prediction methods of the LRE are different from the others. The readers can learn the system stage modeling, analyzing and testing methods of the LRE system as well as corresponding fault diagnosis and prediction methods.This book will benefitresearchers and students who are pursuing aerospace technology, fault detection, diagnostics and corresponding applications. 416 pp. Englisch. N° de réf. du vendeur 9783662492529
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The first book available on the fault characteristic analysis of LREIncludes detailed modeling program of the LRE whole system with different faultsInvolves several applications of artificial neural net (ANN), wavelet analysis, artificial i. N° de réf. du vendeur 106033824
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