Preventive maintenance strategy for offshore wind turbine based on state adaptive assessment

被引：0

作者：

Fu Y. ^{[1
]}

Huang L. ^{[1
]}

Liu L. ^{[1
]}

Wei S. ^{[1
]}

Ren H. ^{[2
]}

Wang Y. ^{[2
]}

Tang G. ^{[2
]}

机构：

[1] Department of Electrical Engineering, Shanghai University of Electric Power, Shanghai

[2] Shanghai Green Environmental Protection Energy Co., Ltd., Shanghai

来源：

Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2022年 / 42卷 / 01期

关键词：

Incremental dictionary learning; Offshore wind turbine; Preventive maintenance; State adaptive assessment; State space partition;

D O I：

10.16081/j.epae.202110009

中图分类号：

学科分类号：

摘要：

In order to solve the problems of incremental learning of fault characteristics and active maintenance for OWT(Offshore Wind Turbine), a preventive maintenance strategy for OWT based on state adaptive assessment is proposed. Firstly, the non-normal population hypothesis is used to test and quantify the information difference between the real-time state and the typical state of OWT, and the typical state characteristics of OWT are captured by the incremental dictionary learning. Then, an adaptive state assessment model of OWT is built based on support vector machine. Secondly, combined with the effective service life of the components, the component maintenance strategy is optimized with the probability vector of state as the decision constraints and the minimum single maintenance cost as the objective function. At the same time, the preventive maintenance model of OWT based on state adaptive assessment is established with the minimum total maintenance cost as the objective function and the daily maintenance time as the constraints, taking into account the loss caused by early or delayed maintenance when the components are grouped. Finally, an offshore wind turbine is taken as an example to verify the effectiveness of the proposed maintenance strategy, and the influence of maintenance times and accessibility on the maintenance strategy is analyzed. © 2022, Electric Power Automation Equipment Press. All right reserved.

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页码：1 / 9

页数：8

共 20 条

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