Fault Diagnosis and Forecast of Substation Equipment Temperature Based on Fuzzy C Means Clustering Algorithm
- 10.2991/icmse-15.2015.222How to use a DOI?
- Power equipment; temperature; fuzzy C means.
The normal operation of power equipment is directly related to the normal life of people in the relevant areas and the normal operation of the enterprise. Regardless of the quality factor of equipment, the most important factor affecting the normal operation of the equipment is the working temperature of the equipment.The traditional temperature measurement of electric power equipment is relying on manual inspection. This method not only has a large workload, high cost, but also low efficiency. The most important is that it cannot predict the temperature of the equipment in a timely manner. After considering the above factors, the fuzzy C means clustering algorithm is used to diagnose and forecast the substation equipment.
- © 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 - Jun Li AU - Jiangwen Xiao AU - Jing Wu AU - Chun Chen AU - Yiwen Xiao PY - 2015/12 DA - 2015/12 TI - Fault Diagnosis and Forecast of Substation Equipment Temperature Based on Fuzzy C Means Clustering Algorithm BT - Proceedings of the 2015 6th International Conference on Manufacturing Science and Engineering PB - Atlantis Press SP - 1215 EP - 1219 SN - 2352-5401 UR - https://doi.org/10.2991/icmse-15.2015.222 DO - 10.2991/icmse-15.2015.222 ID - Li2015/12 ER -