Research on Condition Monitoring of Power Big Data Based on Rough Sets
- 10.2991/meita-15.2015.139How to use a DOI?
- power big data, data mining, condition monitoring, rough set.
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.
- © 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/).
Cite this article
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 -