为解决新型的双源无轨电车的集电杆自动识别集电盒并快速并网的问题,通过改进YOLO-V4(you only look once version 4)网络模型,得到SE-YOLO-POLY(squeeze and excitation networks-you only look once version 4-POLY)网络架构。采用该...为解决新型的双源无轨电车的集电杆自动识别集电盒并快速并网的问题,通过改进YOLO-V4(you only look once version 4)网络模型,得到SE-YOLO-POLY(squeeze and excitation networks-you only look once version 4-POLY)网络架构。采用该网络架构,解决了由于集电盒的大小不一致、高度不一致、拍照角度不一致导致识别的集电盒出现异动的形变和尺寸变化、无法顺利并网的问题。通过SE-YOLO-POLY网络的数据集的生成、模型的设计、训练环境、实际运行反标定方式的搭建等步骤完成网络的部署。改进的模型无论在训练时间、模型大小、识别精度还是在处理速度等方面,都优于传统网络,实现了复杂环境下新型的双源无轨电车的智能并网。展开更多
In this paper, we propose a SAR image ship detection model SSE-Ship that combines image context to extend the detection field of view domain and effectively enhance feature extraction information. This method aims to ...In this paper, we propose a SAR image ship detection model SSE-Ship that combines image context to extend the detection field of view domain and effectively enhance feature extraction information. This method aims to solve the problem of low detection rate in SAR images with ship combination and ship fusion scenes. Firstly, we propose STCSPB network to solve the problem of ship and non-ship object fusion by combining image contextual feature information to distinguish ship and non-ship objects. Secondly, we combine SE Attention to enhance the effective feature information and effectively improve the detection accuracy in combined ship driving scenes. Finally, we conducted extensive experiments on two standard base datasets, SAR-Ship and SSDD, to verify the effectiveness and stability of our proposed method. The experimental results show that the SSE-Ship model has P = 0.950, R = 0.946, mAP_0.5:0.95 = 0.656 and FPS = 50 on the SAR-Ship dataset and mAP_0.5 = 0.964 and R = 0.940 on the SSDD dataset.展开更多
锂-硒电池因其超高的体积能量密度和硒的高电导率而被认为是一种极具有发展前景的锂离子电池。然而,循环过程中电极严重的体积膨胀和多硒化物溶解,以及硒的低负载,阻碍了锂-硒电池应用的发展。解决这三个问题的一种行之有效的方法是将...锂-硒电池因其超高的体积能量密度和硒的高电导率而被认为是一种极具有发展前景的锂离子电池。然而,循环过程中电极严重的体积膨胀和多硒化物溶解,以及硒的低负载,阻碍了锂-硒电池应用的发展。解决这三个问题的一种行之有效的方法是将硒限制在具有丰富孔体积的碳基质中,并同时增强硒与碳的界面相互作用。通过将Se浸入酒石酸盐衍生的蜂窝状三维多孔炭中,合成出了一种具有Se―C键的蜂窝状三维多孔炭@硒(HPC@Se)的新型正极材料用于锂-Se电池。得到的蜂窝状三维多孔炭的孔体积可达1.794 cm^(3)g^(-1),能够均匀包封65%硒。此外,硒与碳之间的强化学键有利于稳定硒,从而进一步缓解其巨大的体积膨胀和多硒化物的溶解,还可促进循环过程中的电荷转移。该HPC@Se正极呈现出极好的循环性能和倍率性能。在0.2 C的电流密度下,经200次循环后,其比容量可保持在561 m Ahg^(-1)(为理论比容量的83%),每次循环的比容量衰减率仅为0.058%。此外,在5 C的高电流密度下,HPC@Se正极还可以达到472.8 m Ahg^(-1)的可观容量。展开更多
文摘为解决新型的双源无轨电车的集电杆自动识别集电盒并快速并网的问题,通过改进YOLO-V4(you only look once version 4)网络模型,得到SE-YOLO-POLY(squeeze and excitation networks-you only look once version 4-POLY)网络架构。采用该网络架构,解决了由于集电盒的大小不一致、高度不一致、拍照角度不一致导致识别的集电盒出现异动的形变和尺寸变化、无法顺利并网的问题。通过SE-YOLO-POLY网络的数据集的生成、模型的设计、训练环境、实际运行反标定方式的搭建等步骤完成网络的部署。改进的模型无论在训练时间、模型大小、识别精度还是在处理速度等方面,都优于传统网络,实现了复杂环境下新型的双源无轨电车的智能并网。
文摘In this paper, we propose a SAR image ship detection model SSE-Ship that combines image context to extend the detection field of view domain and effectively enhance feature extraction information. This method aims to solve the problem of low detection rate in SAR images with ship combination and ship fusion scenes. Firstly, we propose STCSPB network to solve the problem of ship and non-ship object fusion by combining image contextual feature information to distinguish ship and non-ship objects. Secondly, we combine SE Attention to enhance the effective feature information and effectively improve the detection accuracy in combined ship driving scenes. Finally, we conducted extensive experiments on two standard base datasets, SAR-Ship and SSDD, to verify the effectiveness and stability of our proposed method. The experimental results show that the SSE-Ship model has P = 0.950, R = 0.946, mAP_0.5:0.95 = 0.656 and FPS = 50 on the SAR-Ship dataset and mAP_0.5 = 0.964 and R = 0.940 on the SSDD dataset.
文摘锂-硒电池因其超高的体积能量密度和硒的高电导率而被认为是一种极具有发展前景的锂离子电池。然而,循环过程中电极严重的体积膨胀和多硒化物溶解,以及硒的低负载,阻碍了锂-硒电池应用的发展。解决这三个问题的一种行之有效的方法是将硒限制在具有丰富孔体积的碳基质中,并同时增强硒与碳的界面相互作用。通过将Se浸入酒石酸盐衍生的蜂窝状三维多孔炭中,合成出了一种具有Se―C键的蜂窝状三维多孔炭@硒(HPC@Se)的新型正极材料用于锂-Se电池。得到的蜂窝状三维多孔炭的孔体积可达1.794 cm^(3)g^(-1),能够均匀包封65%硒。此外,硒与碳之间的强化学键有利于稳定硒,从而进一步缓解其巨大的体积膨胀和多硒化物的溶解,还可促进循环过程中的电荷转移。该HPC@Se正极呈现出极好的循环性能和倍率性能。在0.2 C的电流密度下,经200次循环后,其比容量可保持在561 m Ahg^(-1)(为理论比容量的83%),每次循环的比容量衰减率仅为0.058%。此外,在5 C的高电流密度下,HPC@Se正极还可以达到472.8 m Ahg^(-1)的可观容量。
