Offshore wind turbines are subjected to years of cyclic loads due to the interaction between wind, wave and structural dynamics. As a result offshore wind turbines are often designed to reach a certain fatigue life. The Fatigue Life Estimation research focuses on the
development of accurate data-driven approaches to estimate the fatigue life of offshore wind turbines within the constraints of the offshore environment. These results aim to serve both updating designs as well as estimating the residual life time of offshore assets.

The present research is also represented in O&O Nobelwind ( Link ) and ICON SafeLife ( Link ).


SCADA based (fatigue) load estimation

SCADA data is an integral part of each (offshore) wind turbine. The SCADA system logs several relevant parameters such as wind speed, wind direction, power and several more.

As SCADA data is becoming more abundant and sampling frequencies are going up, this data has the potential to become a useful tool for fatigue life estimates. This research aims to answer the question, how can SCADA data be used to estimate residual life-time of a wind turbine.

Read our open access publication on thrust load estimation : Link

Virtual sensing

Monitoring offshore wind turbines often is limited to sensors installed on the parts above water-level. However, fatigue critical features are often situated at locations well distanced from the water level. Research into virtual sensing aims to develop methodologies that translate measurements from any location on the structure to another location to create virtual sensors. These virtual sensors help to create a local image of the fatigue loads and serve to estimate fatigue life.

Data-driven fatigue assessment

Monitoring and estimating fatigue loads is just the start of a fatigue assessment of (offshore) wind turbines. One still must translate the measurements into a reliable tool to estimate the residual useful life of a wind turbine. One needs to account for uncertainty in measurements and models.

In this research topic a data-driven fatigue assessment framework is being developed that serves to give a reliable estimate of residual life either based on classic fatigue theory or more advanced fracture mechanics models.