Wind turbine generator blade anomaly detection method and device based on vibration
The embodiment of the invention discloses a vibration-based wind turbine generator blade anomaly detection method and device. The method comprises the following steps: acquiring SCADA data and cabin vibration data of a wind turbine generator in a target time period; inputting the acquired data into...
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| creator | LIU QIANG ZHENG SHUQIAN ZHAN XIAOMING XU ZHENENG WANG QING WANG BOTE XU JINGTAO DENG YIWEI |
| description | The embodiment of the invention discloses a vibration-based wind turbine generator blade anomaly detection method and device. The method comprises the following steps: acquiring SCADA data and cabin vibration data of a wind turbine generator in a target time period; inputting the acquired data into a pre-trained paddle anomaly detection model, the paddle anomaly detection model comprising a vibration feature extraction layer, an SCADA feature extraction layer and an anomaly detection layer, the vibration feature extraction layer is used for extracting vibration features in the cabin vibration data based on a variational mode decomposition technology and a kernel principal component analysis technology, and the SCADA feature extraction layer is used for extracting SCADA features in the SCADA data according to an ABT network. The anomaly detection layer is used for outputting a detection result according to a comparison result of the target residual value and a normal residual value range obtained by pre-traini |
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The method comprises the following steps: acquiring SCADA data and cabin vibration data of a wind turbine generator in a target time period; inputting the acquired data into a pre-trained paddle anomaly detection model, the paddle anomaly detection model comprising a vibration feature extraction layer, an SCADA feature extraction layer and an anomaly detection layer, the vibration feature extraction layer is used for extracting vibration features in the cabin vibration data based on a variational mode decomposition technology and a kernel principal component analysis technology, and the SCADA feature extraction layer is used for extracting SCADA features in the SCADA data according to an ABT network. The anomaly detection layer is used for outputting a detection result according to a comparison result of the target residual value and a normal residual value range obtained by pre-traini</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | BLASTING CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING HEATING LIGHTING MACHINES OR ENGINES FOR LIQUIDS MECHANICAL ENGINEERING OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR PHYSICS PRODUCING MECHANICAL POWER WEAPONS WIND MOTORS WIND, SPRING WEIGHT AND MISCELLANEOUS MOTORS |
| title | Wind turbine generator blade anomaly detection method and device based on vibration |
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