Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)

Fault Diagnosis of Complex Electric Power System Using the Improved Grey Incidence Degree Model

Authors
Xin Ren, Yuan Li, Tie-Ying Wu, Sheng Qu, Li Ma
Corresponding Author
Xin Ren
Available Online April 2017.
DOI
10.2991/icmmct-17.2017.235How to use a DOI?
Keywords
complex electric power system; fault diagnosis; analysis
Abstract

The fault diagnosis of complex electric power systems in marine is very complex and hard, in order to prohibit or further reduce the misoperation after the faults occurring of complex electric power system, the model based on weighted degree of grey incidence of optimized entropy and fault diagnosis system are proposed in this paper, and some simulation experiments about the typical faults of complex electric power system are conducted. And the results show that the system is more stable and its conclusion is right and can satisfy diagnosis in real time, and higher faults subjection degrees resolving power can be achieved. So a novel means is provided for the diagnosis of the fault in complex electric power system.

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 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)
Series
Advances in Engineering Research
Publication Date
April 2017
ISBN
10.2991/icmmct-17.2017.235
ISSN
2352-5401
DOI
10.2991/icmmct-17.2017.235How 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  - Xin Ren
AU  - Yuan Li
AU  - Tie-Ying Wu
AU  - Sheng Qu
AU  - Li Ma
PY  - 2017/04
DA  - 2017/04
TI  - Fault Diagnosis of Complex Electric Power System Using the Improved Grey Incidence Degree Model
BT  - Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)
PB  - Atlantis Press
SP  - 1203
EP  - 1206
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-17.2017.235
DO  - 10.2991/icmmct-17.2017.235
ID  - Ren2017/04
ER  -