基于多通道振动主元特征的风电机组叶片自监督异常识别方法
Self-supervised anomaly recognition method for wind turbine blade based on multi-channel vibration principal features
基于多通道振动主元特征的风电机组叶片自监督异常识别方法 |
| 王博特,王卿,刘强,金波 |
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Self-supervised anomaly recognition method for wind turbine blade based on multi-channel vibration principal features |
| Bote WANG,Qing WANG,Qiang LIU,Bo JIN |
| 图 5 叶片扫塔后出现的低频振荡特征 |
| Fig.5 Low-frequency oscillation characteristics appearing after blade sweep of tower |
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