DOIONLINE 
DOIONLINE Publish In |
International Journal of Mechanical and Production Engineering (IJMPE)-IJMPE |
 Journal Home Volume Issue |
||||||||
Issue |
Volume-11,Issue-2 ( Feb, 2023 ) | |||||||||
Paper Title |
Detection of Wind Turbine Blade Damage with 1d CNN Classifier | |||||||||
Author Name |
Pawel Knap, Patryk Balazy, Krzysztof Lalik | |||||||||
Affilition |
||||||||||
Pages |
20-23 | |||||||||
Abstract |
Wind power plants are taking an active part in global electricity production. The number of wind turbines being installed is increasing every year, and the amount of energy they produce is growing as a result. As the number of wind turbines increases, so does the amount of potential damage to turbine rotor blades. This article presents an algorithm for the prediction of such damage in order to ensure the continuous operation of the device, which is followed by the continuous supply of electricity from wind turbines. The damage prediction algorithm is based on machine learning elements. By limiting the algorithm's input to a few maximum amplitudes of the fast Fourier transform, short processing times are achieved. The precision of the algorithm oscillates around 94% with 4 classes of rotor blade damage. Keywords - Wind Turbine, Blade Damage Detection, Predictive Maintenance, Vibro diagnostics | |||||||||
| View Paper | ||||||||||
