Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications

A Novel Fault Self-diagnosis Algorithm Based on Finite-state Machine for Space Information Network

Authors
Yuan Jiang, Ning Li, Fapeng Wang, Cong Wang, Lianguo Wu
Corresponding Author
Yuan Jiang
Available Online January 2016.
DOI
https://doi.org/10.2991/icaita-16.2016.62How to use a DOI?
Keywords
self-diagnosis; space information network (SIN); finite-state machine
Abstract
the possibility of the development of space information network (SIN) was discussed in this paper, and a novel fault self-diagnosis method was developed. There is limited research of space information network, especially in fault diagnosis domain. This paper gives expectation about future SIN features, and based on these features proposes a fault self-diagnosis algorithm based on finite-state machine. We design a series of novel fault detectors through which multiple satellites nodes can cooperate with each other in a diagnosis task. The fault detectors encode the diagnosis process to state transitions. Each satellites can participate in the fault diagnosis by transiting the detector’s current state to a new one based on local evidence and then pass the fault detector to other satellites.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
Series
Advances in Intelligent Systems Research
Publication Date
January 2016
ISBN
978-94-6252-162-9
ISSN
1951-6851
DOI
https://doi.org/10.2991/icaita-16.2016.62How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yuan Jiang
AU  - Ning Li
AU  - Fapeng Wang
AU  - Cong Wang
AU  - Lianguo Wu
PY  - 2016/01
DA  - 2016/01
TI  - A Novel Fault Self-diagnosis Algorithm Based on Finite-state Machine for Space Information Network
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
PB  - Atlantis Press
SP  - 251
EP  - 254
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaita-16.2016.62
DO  - https://doi.org/10.2991/icaita-16.2016.62
ID  - Jiang2016/01
ER  -