Optimization method for transformer maintenance interval considering dynamic incomplete maintenance
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.
power transformermaintenance strategyincomplete maintenanceimprovement factorMonte Carlo algorithmEM algorithm
万方数据
维普
