Fatigue Evaluation of Offshore Wind Turbines Using In-Situ Strain Data

HOU QIAO, GUANGMING XU, CE SHEN, YONGLEI SU, WEI LI, CHUANRUI GUO

Abstract


The development of offshore wind power has increased rapidly in recent years due to its clean and renewable nature. However, the design of offshore wind turbines is difficult and costly. As a result, the development cost remains high. Among them, fatigue of the steel structures in offshore wind turbine foundations is one of the most severe structural diseases, significantly affecting offshore wind development and maintenance costs. This paper proposes a feasible approach to study the fatigue damage of offshore wind turbines using the in-situ strain data based on a statistical analysis of stress amplitude and cycles. First, the hot-spot stress at the corresponding monitoring locations is calculated using the strain monitoring data from an offshore wind farm in the East China Sea. Second, the stress amplitude and cycles are solved using the rain-flow counting method. Subsequently, the weekly distribution statistics of stress amplitude and cycles are fitted using Weibull distribution. The Chi-square test is used to verify the confidence level of the probability density function of the weekly stress amplitude and cycles. Finally, according to the statistical distribution of stress amplitude and cycles, the cumulative damage is analyzed based on the hot-spot stress S-N curve of steel structures with cathodic protection in seawater. The fatigue damage obtained based on the monitored data is roughly consistent with the numerical calculation results. However, the proposed method underestimated the fatigue damage compared to the design results obtained by numerical prediction. Though these fatigue results are not mutually consistent, they can all confirm that the wind turbine would not suffer fatigue issues at present, as the fatigue damages are all below the threshold. Further efforts should be made to handle this inconsistency in fatigue prediction.


DOI
10.12783/shm2023/37047

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