Minkowski logarithmic error: A physics-informed neural network approach for wind turbine lifetime assessment
. In this contribution we present a physics-informed neural network (PINN) approach for wind turbine fatigue estimation. This PINN incorporates physical information of the structure’s fatigue profile in its loss function, referred to as Minkowski logarithmic error (MLE) - an extension of the log loss for any given L p space. The function is mathematically analysed and differentiated in order to better understand its behaviour. The results obtained using the MLE are favourably compared with previous efforts using the mean squared logarithmic error. Finally, the long-term error is evaluated based on the effect of p .
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Minkowski logarithmic error: A physics-informed neural network approach for wind turbine lifetime assessment
Semantic Scholar · Physics · 2022
Abstract
. In this contribution we present a physics-informed neural network (PINN) approach for wind turbine fatigue estimation. This PINN incorporates physical information of the structure’s fatigue profile in its loss function, referred to as Minkowski logarithmic error (MLE) - an extension of the log loss for any given L p space. The function is mathematically analysed and differentiated in order to better understand its behaviour. The results obtained using the MLE are favourably compared with previous efforts using the mean squared logarithmic error. Finally, the long-term error is evaluated based on the effect of p .