International Journal of Mechanical and Production Engineering (IJMPE)
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Statistics report
Apr. 2024
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 130
Paper Published : 2388
No. of Authors : 6802
  Journal Paper


Paper Title :
Detection of Wind Turbine Blade Damage with 1d CNN Classifier

Author :Pawel Knap, Patryk Balazy, Krzysztof Lalik

Article Citation :Pawel Knap ,Patryk Balazy ,Krzysztof Lalik , (2023 ) " Detection of Wind Turbine Blade Damage with 1d CNN Classifier " , International Journal of Mechanical and Production Engineering (IJMPE) , pp. 20-23, Volume-11,Issue-2

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

Type : Research paper

Published : Volume-11,Issue-2


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