Core Concepts
This study presents a stochastic modeling approach to analyze the fatigue damage evolution and predict the failure probabilities of wind turbine composite blades under uncertain wind loads.
Abstract
This paper proposes a methodology for analyzing the fatigue failure probability of wind turbine composite blades using monitoring-based stochastic deterioration modeling. The key highlights and insights are:
The analysis of wind load on the composite blades is simplified as wind pressure based on the wind speed measurements. The internal stresses in the composite blades are then obtained from finite element analysis.
The fatigue damage evolution in composite materials is modeled using a non-linear stiffness degradation model that can capture the entire fatigue life cycle, including the initial, middle, and final stages.
The gamma process, a stochastic process suitable for modeling gradual damage accumulation, is used to simulate the uncertain fatigue damage evolution over time. This allows for time-dependent reliability analysis.
The failure probabilities are predicted for different critical fatigue damage thresholds (70%, 80%, 90%, 95%) to assist in determining optimal inspection and maintenance strategies for the composite blades.
A numerical case study is presented to demonstrate the applicability of the proposed stochastic fatigue damage model. The results show that the model can provide reliable predictions of the time-dependent failure probabilities for wind turbine composite blades.
Stats
The maximum internal stress in the composite blades is 718 MPa, and the ultimate stress is 1548 MPa.
Quotes
"The gamma process is a continuous stochastic process {X(t), t≥0} with the following three properties: (1) X(t)=0 with probability one; (2) X(t) has independent increments; (3) X(t)-X(s)~Ga(v(t-s),u) for all t>s≥0, as described in [4]"