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    Abnormal State Identification Method for Wind Turbines Based on Improved DBSCAN and Random Forests

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    JLEED9.EYENG-6058.pdf (1.896Mb)
    Date
    2026
    Author
    Li, Wei
    Wang, Honghui
    Zhang, Yu
    Fang, Xin
    Tian, Xiaojie
    Leng, Dingxin
    Xie, Yingchun
    Liu, Guijie
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    Abstract
    AbstractAs a crucial component of wind power generation systems, wind turbines must operate safely to prevent sudden failures. This requires effective identification of abnormal operational states. In this study, we propose a novel approach for ...
    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4311977
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