Aiming at the limited historical maintenance data of power transformers and the existence of missing data,and the problem that previous maintenance strategies rarely considered the dynamic changes in actual maintenance costs,an optimization method considering incomplete maintenance and dynamic maintenance costs is proposed.This method is based on the expectation maximization algorithm and Monte Carlo algorithm,which solves the distribution fitting problem of defect deletion data under small sample conditions,and uses dynamic incomplete maintenance improvement factors to better describe the dynamic changes in maintenance costs.The verification results show that under the premise of meeting reliability constraints,maintenance costs can be reduced by 13.221％.And through further research,it was concluded that as the maintenance cycle extends,the dominant maintenance cost factor shifts from corrective maintenance to preventive maintenance.
关键词
电力变压器/维修策略/不完全维修/改善因子/蒙特卡洛算法/EM算法
Key words
power transformer/maintenance strategy/incomplete maintenance/improvement factor/Monte Carlo algorithm/EM algorithm
维普
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