Open AccessFault diagnosis of wind turbine bearing based on CNN-XGBoost
Author(s) -
Zhou Yang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2033/1/012200
Subject(s) - turbine , convolutional neural network , bearing (navigation) , feature extraction , computer science , fault (geology) , correctness , grayscale , artificial intelligence , wind power , pattern recognition (psychology) , fault detection and isolation , control theory (sociology) , engineering , algorithm , pixel , electrical engineering , seismology , geology , mechanical engineering , control (management) , actuator