Proceedings of the 2017 2nd International Conference on Automation, Mechanical and Electrical Engineering (AMEE 2017)

Design and Study of Real-time Online Assessing System for Marine Power Station Reliability

Authors
Zhiliang Wu, Yubin Yao, Dan Wang
Corresponding Author
Zhiliang Wu
Available Online September 2017.
DOI
10.2991/amee-17.2017.37How to use a DOI?
Keywords
Marine power station; reliability; reliability model; assessment system
Abstract

Establish reliability model of marine power station under different working conditions. On this basis, the reliability model database of ship power station system is established. Through the real-time online detecting the different working conditions of the marine power station, the corresponding reliability model of the database is called accordingly, and the reliability of the ship power station is evaluated online and in real time. The results of research have important reference value for the research on reliability and maintainability of marine power station.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 2nd International Conference on Automation, Mechanical and Electrical Engineering (AMEE 2017)
Series
Advances in Engineering Research
Publication Date
September 2017
ISBN
10.2991/amee-17.2017.37
ISSN
2352-5401
DOI
10.2991/amee-17.2017.37How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zhiliang Wu
AU  - Yubin Yao
AU  - Dan Wang
PY  - 2017/09
DA  - 2017/09
TI  - Design and Study of Real-time Online Assessing System for Marine Power Station Reliability
BT  - Proceedings of the 2017 2nd International Conference on Automation, Mechanical and Electrical Engineering (AMEE 2017)
PB  - Atlantis Press
SP  - 180
EP  - 182
SN  - 2352-5401
UR  - https://doi.org/10.2991/amee-17.2017.37
DO  - 10.2991/amee-17.2017.37
ID  - Wu2017/09
ER  -