@inproceedings{aefc000a0dbc4a8fbd9a8cea47de25f0,
title = "A framework design of automatic fault diagnosis system",
abstract = "To resolve a lasting suitable cabin environment for the astronauts, this paper proposes an effective framework design for automatic fault diagnosis system. This framework can implement a real-time online diagnosis and decision support for fault, and carry out an early diagnosis for weak fault. Finally, this paper achieves an online automatic fault diagnosis system by using neural network's self-learning characteristics and expert knowledge. In two-men-two-days simulated manned space flight test, the software of diagnosis system framework worked well, which has been assessed and verified comprehensively.",
keywords = "Automatic fault diagnosis system, Decision-making support, Expert system, Neural networks, Space station",
author = "Wei Hu and Deng, \{Yi Bing\} and Feng, \{Hong Qi\} and Wu, \{Qing E.\} and Bin Tang and Zou, \{Jian Hua\}",
year = "2013",
doi = "10.4028/www.scientific.net/AMM.330.635",
language = "英语",
isbn = "9783037857250",
series = "Applied Mechanics and Materials",
pages = "635--638",
booktitle = "Materials Engineering and Automatic Control II",
note = "2nd International Conference on Materials Engineering and Automatic Control, ICMEAC 2013 ; Conference date: 18-05-2013 Through 19-05-2013",
}