Proceedings of the 3rd International Conference on Mechatronics, Robotics and Automation

Reliability Analysis on the Injection System by Mapping T-S Fault Trees into Bayesian Networks

Authors
Yaxin Liu, Zijian Zhang, Ming Zhong
Corresponding Author
Yaxin Liu
Available Online April 2015.
DOI
https://doi.org/10.2991/icmra-15.2015.219How to use a DOI?
Keywords
reliability analysis; T-S FTA; Bayesian network; injection system; importance; pharmacy robot.
Abstract
A novel reliability analysis technique based on Bayesian network and T-S FTA is proposed in this paper. In the proposed technique, the nodes in Bayesian network can be expressed in terms of fuzzy possibilities and the magnitudes of the failure in the system are expressed in term of fuzzy variables. The paper shows that any T-S fault tree can be directly mapped into a BN and that forward inference techniques on the latter may be used to obtain classic parameters computed from the former (i.e. reliability of Top Event or any sub-system, the importance of Basic Events, etc). Furthermore, by using BN, a general diagnostic analysis (backward inference) can be performed, in which posterior probability is computed. The proposed technique is applied to analyze the reliability of the injection system of chemotherapy pharmacy robot.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 3rd International Conference on Mechatronics, Robotics and Automation
Series
Advances in Computer Science Research
Publication Date
April 2015
ISBN
978-94-62520-76-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmra-15.2015.219How 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  - Yaxin Liu
AU  - Zijian Zhang
AU  - Ming Zhong
PY  - 2015/04
DA  - 2015/04
TI  - Reliability Analysis on the Injection System by Mapping T-S Fault Trees into Bayesian Networks
BT  - Proceedings of the 3rd International Conference on Mechatronics, Robotics and Automation
PB  - Atlantis Press
SP  - 1134
EP  - 1139
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmra-15.2015.219
DO  - https://doi.org/10.2991/icmra-15.2015.219
ID  - Liu2015/04
ER  -