Remaining Useful Life Determination for Wind Turbines

被引:4
|
作者
Pagitsch, Michael [1 ]
Jacobs, Georg [1 ]
Bosse, Dennis [1 ]
机构
[1] Rhein Westfal TH Aachen, Ctr Wind Power Drives, Aachen, Germany
来源
NAWEA WINDTECH 2019 | 2020年 / 1452卷
关键词
PREDICTION;
D O I
10.1088/1742-6596/1452/1/012052
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Since wind turbines have become one of the prevailing sources of electrical energy, their reliability and availability are of enormous importance. Predictive maintenance is a strategy for keeping both factors high and thus heavily under research. Maintenance based on the actual condition of a turbine would be the ideal way in the field of tension between benefit and effort. However, determining the condition of machine parts and elements traditionally requires the expensive application of measurement techniques and inspections. In many cases load-based maintenance - powered by few simple sensors and a model-based derivation of the condition from the history of loads - would be a good compromise. This paper presents a novel method for modeling wind turbines with minimal data requirements for the purpose of calculating inner loads and deriving the condition of machine elements. The applicability is demonstrated in the form of a remaining useful lifetime estimation of gearbox bearings.
引用
收藏
页数:8
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