http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Risk assessment of aviation DC series arc based on reconstructed CBAM‑CNN
Haoqi Yang,Cong Gao,Hongjuan Ge,Yiqin Sang,Yongshuai Wang 전력전자학회 2023 JOURNAL OF POWER ELECTRONICS Vol.23 No.5
The hazards of sustained arc and un-sustained arc are different. However, during the stage of arc development, there is a lack of effective methods to identify them, which is not conducive to the timely accurate assessment of arc risk. Therefore, this paper proposes a risk assessment method for aviation DC series arc based on a reconstructed CBAM-CNN. First, in the process of generating the feature set, a feature evaluation function is defined to screen the features. Then the existing convolution block attention module (CBAM) is improved by adding a reshaped layer and redefining spatial attention, which results in the reconstructed CBAM-CNN. Finally, the reconstructed CBAM-CNN takes the feature set as its input and output arc risk assessment results on the basis of enhancing the attention of important features. The validity of the reconstructed CBAM-CNN method is verified on an aviation DC arc generation platform. It is found that the proposed method has a higher training efficiency and evaluation accuracy than the CNN method and CBAM-CNN method. In addition, the reconstructed CBAM-CNN involves fewer parameters to be measured, which can reduce its dependence on computing resources.