Research on Condition Monitoring of Power Big Data Based on Rough Sets

DOI

10.2991/meita-15.2015.139How to use a DOI?

Keywords

power big data, data mining, condition monitoring, rough set.

Abstract

The urgency of demanding for large data in power industry will greatly exceed that of in other basic energy industries in the future. Through analyzing the power equipment condition monitoring data, we can assess more accurately the operating condition of power equipment, predict the life span of the equipment, and thus can effectively avoid economic losses caused by excessive supervision as well as shortness of supervision. To further promote the wide and deep application of power big data technology in condition monitoring, this paper summarizes equipment condition monitoring studies based on big data technology, and discusses applications of the key technologies of Big Data-Data Mining in condition monitoring. For data mining techniques, this paper uses a rough set theory to study application in knowledge and data discovery and fault monitoring. And for the presence of some problems of rough set theory applied in practical systems, some directions for further research are proposed.

Copyright

© 2015, 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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TY  - CONF
AU  - Yulong Yan
AU  - Jilai Wu
AU  - Shejun Wu
AU  - Jian Zhang
PY  - 2015/08
DA  - 2015/08
TI  - Research on Condition Monitoring of Power Big Data Based on Rough Sets
BT  - Proceedings of the 2015 International Conference on Materials Engineering and Information Technology Applications
PB  - Atlantis Press
SP  - 760
EP  - 765
SN  - 2352-5401
UR  - https://doi.org/10.2991/meita-15.2015.139
DO  - 10.2991/meita-15.2015.139
ID  - Yan2015/08
ER  -