A fatigue reliability assessment approach for wind turbine blades based on continuous time Bayesian network and FEA

Abstract

AbstractWind turbine blades made by composite materials (CWTBs), encounter fatigue failures, such as cracks, fractures, delamination, etc. Finite Element Analysis (FEA) is applied for fatigue performance simulations of CWTBs as the full‐scale testing is costly. To consider correlated failures and uncertainties in load and material parameters, this paper proposes a fatigue reliability assessment method based on continuous time Bayesian network and FEA. Specifically, the dangerous regions of each component of CWTBs are determined by finite element fatigue simulation. The failure probability distributions of components are then computed by quantifying the uncertainties of several factors including the load and material parameters. A continuous time Bayesian network model is constructed for the fatigue reliability of CWTBs. The performance of the proposed method is verified by a comprehensive analysis with the results of discrete time Bayesian networks.