Advances in Manufacturing

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Models for lifetime estimation: an overview with focus on applications to wind turbines

Thomas M. Welte1 • Kesheng Wang2   

  1. 1. SINTEF Energy Research, 7465 Trondheim, Norway
    2. Department of Production and Quality Engineering, Norwegian
    University of Science and Technology, 7491 Trondheim,
    Norway
  • Received:2014-01-16 Online:2014-03-21 Published:2014-02-14
  • Contact: e-mail: thomas.welte@sintef.no

Abstract: This paper provides an overview of models and methods for estimation of lifetime of technical components. Although the focus in this paper is on wind turbine applications, the major content of the paper is of general nature. Thus, most of the paper content is also valid for lifetime models applied to other technical systems. The models presented and discussed in this paper are classified in different types of model classes. The main classification used in this paper divides the models in the following classes: physical models, stochastic models, data-driven models and artificial intelligence, and combined models. The paper provides an overview of different models for the different classes. Furthermore, advantages and disadvantages of the models are discussed, and the estimation of model parameters is briefly described. Finally, a number of literature examples are given in this paper, providing an overview of applications of different models on wind turbines.

Key words: Lifetime estimation , Model classification , Wind turbine