The effect of environmental and operational variabilities on damage detection in wind turbine blades

This contribution is submitted to the invited session on vibration-based damage assessment for civil engineering structures It is a well-known fact that changes in the environmental and operational conditions may seriously influence the performance of structural health monitoring (SHM) methods. The present paper demonstrates how certain environmental and operational variations affect the damage detection in the blade of an operating wind turbine. The considered vibration-based SHM setup was measuring blade accelerations over a period of 3.5 months, while simultaneously recording the environmental and operational conditions. In the period, a damage of three different sizes was introduced by gradually cutting open the trailing edge of the blade. The damage index used in the study is composed of Mahalanobis-squared distances based on the covariance matrix of the accelerations. It is demonstrated how temperature and wind speed along with rotational speed and pitch can mask the damaged-induced changes, hence leading to false-negative classifications. It is found that the highest correlation exists between the damage index and variabilities in the temperature and rotational speed. Limiting the operational variabilities by using correlated measurements and filtering out the environmental variabilities by principal component analysis provides a clear detection of the three introduced damages.