可再生能源2025，Vol.43Issue(3)：346-352,7.
基于改进模式识别的无人值守风电场群组机器人集中巡检研究
Research on centralized inspection of unmanned wind farm group robots based on improved pattern recognition
摘要
Abstract
Due to the wide variety of wind farm equipment and complex operating environment,it is usually unattended and difficult to find faults in time.The traditional inspection method takes a long time and has low identification accuracy.As a result,the fault is not handled in time,which affects the stable operation and power generation efficiency of wind farms.Therefore,a robot centralized inspection scheme based on improved pattern recognition is proposed for unattended wind farm groups.For transformer faults,equipment temperature anomalies and gearbox sound anomalies in wind farms,BP neural network algorithm,fuzzy pattern recognition algorithm and empirical mode decomposition algorithm are used to carry out inspection,and the proposed method is tested experimentally in a large wind power station.The results show that the proposed method can realize the inspection of various faults in wind farms.The first time to obtain the fault signal,to avoid the occurrence of security accidents;The recognition accuracy rate remains above 92.3%,and the recall rate and F1 score are also better than the comparison method,indicating that the proposed method is more comprehensive in identifying fault samples and can detect faults more effectively.关键词
改进模式识别/BP神经网络算法/经验模态分解算法/齿轮箱声音异常/变压器故障Key words
improving pattern recognition/BP neural network algorithm/empirical mode decomposition algorithm/abnormal gearbox sound/transformer failure分类
能源科技引用本文复制引用
董礼,程丽敏,赵博,王雁冰,商志强,朱盼盼..基于改进模式识别的无人值守风电场群组机器人集中巡检研究[J].可再生能源,2025,43(3):346-352,7.基金项目
国家自然科学基金(51675498). （51675498）
