A Fault Diagnosis Method of Quadrotor UAV Based on Self-attention Mechanism.
2023 7th International Symposium on Computer Science and Intelligent Control (ISCSIC)(2023)
摘要
Due to the different flight actions of the quadrotor unmanned aerial vehicle (UAV), the distribution of condition monitoring data in time dimension is inconsistent. The data-driven diagnostic model is difficult to extract fault features, which reduces the diagnostic performance. In this paper, a fault diagnosis method for quadrotor UAV based on self-attention mechanism is proposed. The attention mechanism is used to extract the long-term dependence of the data in time dimension. Then, a convolution module is added for further feature extraction, which can improve the capability of fault feature extraction. Experimental results show that the accuracy of UAV fault diagnosis under multi-action flight reaches 98.81%, which verify the effectiveness of the proposed method.
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关键词
fault diagnosis,unmanned aerial vehicle,self-attention mechanism,Convolution
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