Cloud Neural Network Based Fault Detection and Diagnosis of Space Propulsion System

XU Zong-ben;FAN Zhong-ze

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  • Sponsored by: China Association for Science and Technology (CAST)

    Editor-In-Chief: Xu Yida

    ISSN 1000-1093

    　

  • Hosted By: China Ordnance Society

    Published By: Acta Armamentarii

    CN 11-2176/TJ

Acta Armamentarii, a Chinese monthly journal, was first published in 1979. The journal is supervised by China Association for Science and Technology, sponsored by China Ordnance Society，and edited and published by Editorial Board of Acta Armamentarii. The Journal is included in all important domestic databases，and also collected by Engineering Index (EI, USA), Chemical Abstracts (CA, USA), Science Abstracts (SA, UK）, Abstract Journal (AJ, Russia), and Current Bibliography on Science and Technology(CBST).Acta Armamentarii has been selected into the journal Of Ordnance Science and Technology (Weapons Industry) Field Of High Quality Scientific and Technological Periodical Classification Catalogue (2022 edition), ranking T1, and the journal of Automotive Engineering Field of High Quality Scientific and technological Periodical classification Catalogue, ranking T2.
Acta Armamentarii ›› 2009, Vol. 30 ›› Issue (6) : 727-732. DOI: 10.3969/j.issn.1000-1093.2009.06.013
Paper

Cloud Neural Network Based Fault Detection and Diagnosis of Space Propulsion System

  • XU Zong-ben1, FAN Zhong-ze1,2
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Abstract

An approach of cloud neural network was proposed and used for fault detection and diagnosis of the space propulsion system. A physical propulsion system of space vehicle was used to validate the approach. The simulated result demonstrates that the new approach can provide a real-time description for work state of the propulsion system with higher identify precision and makes fault defection deci?sion in time.

Key words

propulsion system of aviation and aerospace / neural network / cloud model / space propul?sion system / fault detection and diagnosis / fault simulation

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XU Zong-ben, FAN Zhong-ze. Cloud Neural Network Based Fault Detection and Diagnosis of Space Propulsion System. Acta Armamentarii. 2009, 30(6): 727-732 https://doi.org/10.3969/j.issn.1000-1093.2009.06.013

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