A Novel Fault Self-diagnosis Algorithm Based on Finite-state Machine for Space Information Network
Yuan Jiang, Ning Li, Fapeng Wang, Cong Wang, Lianguo Wu
Available Online January 2016.
- https://doi.org/10.2991/icaita-16.2016.62How to use a DOI?
- self-diagnosis; space information network (SIN); finite-state machine
- 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.
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 -