Open AccessRemaining Useful Life Determination for Wind Turbines
Author(s) -
Michael Pagitsch,
Georg Jacobs,
Dennis Bosse
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1452/1/012052
Subject(s) - wind power , turbine , reliability (semiconductor) , reliability engineering , field (mathematics) , predictive maintenance , computer science , condition monitoring , marine engineering , engineering , power (physics) , mechanical engineering , electrical engineering , physics , mathematics , quantum mechanics , pure mathematics
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.