Blade health monitoring and diagnosis method to enhance operational safety of wind turbine

In order to monitor blade health and detect any damage efficiently, a new diagnosis method for wind turbine blades was proposed. In consideration of harsh environments of a wind turbine rotor, high-resolution real-time blade condition monitoring was realized with the use of optic sensors and a wireless network. A hybrid algorithm, which merges a statistical method with model information, was introduced to overcome the weakness of each method. In addition, alarm limits are determined through a machine learning algorithm to enhance its reliability. The proposed algorithm was embedded in the Blade Health Monitoring and Integrity Evaluation System and was verified at a 3MW wind turbine of the Yeongheung wind farm.