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@PHDTHESIS{Loriemi:1023832,
author = {Loriemi, Amin},
othercontributors = {Jacobs, Georg and Schmitt, Robert H.},
title = {{M}onitoring von {H}auptlagerlasten in
{W}indenergieanlagen},
school = {Rheinisch-Westfälische Technische Hochschule Aachen},
type = {Dissertation},
address = {Aachen},
publisher = {RWTH Aachen University},
reportid = {RWTH-2025-10775},
pages = {1 Online-Ressource : Illustrationen},
year = {2025},
note = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
University 2026; Dissertation, Rheinisch-Westfälische
Technische Hochschule Aachen, 2025},
abstract = {The main bearing loads of wind turbines are not monitored
as standard. To date, there is no economical and validated
method for this. However, knowledge of these loads can help
to reduce the levelized cost of energy for wind turbines. By
knowing the main bearing loads, the lifetime of the main
bearings can be calculated. By proving that the bearings
have a sufficient remaining lifetime, it is possible to
continue operating the wind turbine beyond the planned
lifetime without expensive bearing replacements. After
examining the advantages and disadvantages of various
concepts, a load estimation system based on displacement
signals was selected. This system was developed and
validated through test bench experiments. Suitable
displacement signals for load estimation were identified
through correlation analyses. Various regression models were
investigated. These models were first trained with test
bench measurements. In comparison, linear regression was
identified as the preferred regression model due to its
simplicity and sufficient accuracy. An alternative and more
economical development of the regression models based on
physical simulations of the rotor suspension was considered.
It was found that detailed FEM modelling is required to
achieve the necessary accuracy. Simplified models were
insufficient. Nevertheless, not all main bearing load
components could be determined with the required accuracy.
In addition, sensitivity analyses carried out showed that
uncertainties in the model parameters represent significant
sources of error. A main bearing load estimation using
displacement signals is possible with a co-efficient of
determination between 0.83 and 0.9. A subsequent bearing
lifetime estimation results in an error of up to $19\%.$ By
additionally taking strain signals into account, a load
estimation with a coefficient of determination between 0.89
and 0.94 can be achieved. This allows the bearing lifetime
estimation to be im-proved to an error of up to $6\%.$
However, disadvantages regarding the sensor technology for
strain measurement still remain.},
cin = {411710},
ddc = {620},
cid = {$I:(DE-82)411710_20190404$},
typ = {PUB:(DE-HGF)11},
doi = {10.18154/RWTH-2025-10775},
url = {https://publications.rwth-aachen.de/record/1023832},
}
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