风力发电机覆冰在线监测动态预警模型

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中图分类号：TM614 文献标志码：A 文章编号：1000-582X（2026）03-001-12

A dynamic early warning model for online monitoring of wind turbine blade icing

HU Qin，RAO Lipeng，WANG Li，JIANG Xingliang，SHU Lichun （Xuefeng Mountain Energy Equipment Safety National Observation and Research Station， Chongqing University， Chongqing 400044， P.R. China）

Abstract： Blade icing frequently occurs on wind turbines operating in cold weather conditions，leading to reduced power output，unstable equipment operation，and even severe mechanical failures.Therefore，developing effective early warning methods for wind turbine icing is of great practical significance.In this study，Supervisory Control and Data Acquisition （SCADA） operational data are analyzed，and key features are constructed based on wind speed，power output，and ambient temperature.An early warning model for blade icing events is established using arandom forest algorithm.In addition，real-time monitoring of ice thicknessisachieved through a rotating cylindricalarraydevice，based on which a real-time icing early warning model and a dynamic warning mechanism are developed. A 3.2MW wind turbine at the Wanbao Wind Farm in Chongqing is used as a case study to validate the proposed approach.The results show that the icing occurrence warning model achieves aclasification accuracy exceeding 95% ，and warning signals are issued multiple times within 1h prior to blade icing events. Furthermore，thereal-time warning model continues to generate alerts after icing ocurs，demonstrating its capability to continuously track the evolution of the turbine icing environment.Overall，the proposed dynamic early warning model provides effective decision support for the safe operation and efficient management of wind turbines.

Keywords： wind turbine; blade icing online monitoring; rotating cylindrical array; dynamic early warning

随着全球对可再生能源的需求日益增长，风力发电作为一种环保、可持续的能源形式受到了广泛关注[2]。（剩余12758字）