DocumentCode
3012543
Title
The influence estimation of aging factor in MV cable using Weibull distribution and Neural Networks
Author
Kim Sung-min ; Jang-seob Lim ; Beong-suk Kim ; Jin Lee ; Won-suck Choi ; Kun-ho Lee ; Yeon-ha Jung ; Tae-Wan Kim
fYear
2012
fDate
23-27 Sept. 2012
Firstpage
1223
Lastpage
1226
Abstract
Transition from TBM(Time-Based Maintenance) to CBM(Condition-Based Maintenance) is required on maintenance method of cable. For maximize the cable maintenance efficiency, sequential reinforcement standards must establish in accordance with estimation of aging factor. This paper estimates that each aging factor has an effect on the cable status using the Weibull distribution and Neural Networks.
Keywords
Weibull distribution; ageing; maintenance engineering; neural nets; power cables; power engineering computing; CBM; MV cable; TBM; Weibull distribution; aging factor estimation; cable maintenance efficiency; cable maintenance method; condition-based maintenance; medium-voltage cables; neural networks; sequential reinforcement standards; time-based maintenance; Aging; Artificial neural networks; Estimation; Monitoring; Power cables; Aging Factor; NDIS; Neural Networks; SCADA; SOMAS; Weibull distribution;
fLanguage
English
Publisher
ieee
Conference_Titel
Condition Monitoring and Diagnosis (CMD), 2012 International Conference on
Conference_Location
Bali
Print_ISBN
978-1-4673-1019-2
Type
conf
DOI
10.1109/CMD.2012.6416382
Filename
6416382
Link To Document