Publication:
Ice Detection Model of Wind Turbine Blades Based on Random Forest Classifier

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dc.contributor.authorZhang, Lijun
dc.contributor.authorLiu, Kai
dc.contributor.authorWang, Yufeng
dc.contributor.authorOmariba, Zachary
dc.date.accessioned2024-03-01T08:20:50Z
dc.date.available2024-03-01T08:20:50Z
dc.date.issued2018-09-25
dc.description.abstractWhen wind turbine blades are icing, the output power of a wind turbine tends to reduce, thus informing the selection of two basic variables of wind speed and power. Then other features, such as the degree of power deviation from the power curve fitted by normal sample data, are extracted to build the model based on the random forest classifier with the confusion matrix for result assessment. The model indicates that it has high accuracy and good generalization ability verified with the data from the China Industrial Big Data Innovation Competition. This study looks at ice detection on wind turbine blades using supervisory control and data acquisition (SCADA) data and thereafter a model based on the random forest classifier is proposed. Compared with other classification models, the model based on the random forest classifier is more accurate and more efficient in terms of computing capabilities, making it more suitable for the practical application on ice detection.
dc.description.sponsorshipNational Key Research and Development Program of China,Fundamental Research Funds for Central Universities of China,National Natural Science Foundation of China.
dc.identifier.citationZhang, Lijun, Kai Liu, Yufeng Wang, and Zachary Bosire Omariba. 2018. "Ice Detection Model of Wind Turbine Blades Based on Random Forest Classifier" Energies 11, no. 10: 2548. https://doi.org/10.3390/en11102548
dc.identifier.urihttps://www.researchgate.net/publication/327874875_Ice_Detection_Model_of_Wind_Turbine_Blades_Based_on_Random_Forest_Classifier
dc.identifier.urihttps://repository.nrf.go.ke/handle/123456789/617
dc.language.isoen
dc.publisherEnergies
dc.subjectUniversity of Science and Technology Beijing
dc.titleIce Detection Model of Wind Turbine Blades Based on Random Forest Classifier
dc.typeArticle
dspace.entity.typePublication

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