Summary
Icing on the surface of wind turbine blades is one of the most critical problems for wind turbines installed at sites in cold climate. It can significantly affect the performance of the entire wind turbine. A number of deicing methods and techniques have been developed to address this problem. However, first of all, timely icing detection and estimation can provide the necessary information, such as the amount and location of icing, which are very useful for optimizing the deicing process. In this work, first, the thermodynamic processes during icing on the surface of wind turbine blades were presented to understand the characteristics of the varying temperature related to icing process. In the experimental section, a wind turbine blade model was tested in the low‐temperature laboratory. High‐performance distributed fiber optic sensors were attached to the surface of the wind turbine blade to measure the temperature change. This sensor can provide the temperature information as much as possible, which enables the identification of the initiation time of icing and the estimation of the amount of icing. As a result, the relationship between the amount of icing and the temperature change can be obtained. It indicates that the proposed estimation method is efficient and sensitive for ice monitoring of wind turbine blades. Finally, finite element analysis was implemented to explore the effects of airflow on the temperature curves.