Zeolitic Imidazolate Framework-8(ZIF-8)material was prepared by chemical precipitation method.The microstructure and physical properties of the as-prepared samples were characterized by XRD,BET,FESEM and UV spectropho...Zeolitic Imidazolate Framework-8(ZIF-8)material was prepared by chemical precipitation method.The microstructure and physical properties of the as-prepared samples were characterized by XRD,BET,FESEM and UV spectrophotometer.The self-made four-channel measurement device was used to test the gas sensitivity of ZIF-8 material toward ethanol gas under photo-thermal synergistic excitation.The results showed that the sample was typical ZIF-8(E_(g)=4.96 eV)with a regular dodecahedron shape and the specific surface is up to 1793 m^(2)/g.The as-prepared ZIF-8 has a gas response value of 55.04 to 100 ppm ethanol at 75℃ and it shows good gas sensing selectivity and repeated stability.The excellent gas sensitivity can be attributed to the increase of free electron concentration in the ZIF-8 conduction band by photo-thermal synergistic excitation,and the large specific surface area of ZIF-8 material provides more active sites for gas-solid surface reaction.The reaction mechanism of ZIF-8 material under multi-field excitation was also discussed.展开更多
电力系统架空线巡线机器人对于提高架空输电线的维护效率进而保障电力系统的安全稳定运行具有重要作用。针对架空线巡线机器人巡线过程中需要有效识别线路中的附属障碍物并采取相应障碍规避动作的问题,文章研究了基于深度学习的巡线机...电力系统架空线巡线机器人对于提高架空输电线的维护效率进而保障电力系统的安全稳定运行具有重要作用。针对架空线巡线机器人巡线过程中需要有效识别线路中的附属障碍物并采取相应障碍规避动作的问题,文章研究了基于深度学习的巡线机器人架空线附属障碍物识别方法。论述了基于深度学习的架空线巡线机器人系统的整体结构,在整体系统结构的基础上分析了YOLOv8(you only look once version 8)模型的结构及其应用,进而基于增强的架空线障碍物数据集对所述方法进行了有效性验证。实验结果表明,文中所述基于YOLOv8的巡线机器人障碍物识别模型具有更快的识别速度和更高的识别率,能够更好满足巡线机器人的避障需求。展开更多
基金supported by the National Natural Science Foundation of China(No.51864028)the Yunnan Province Science and Technology Major Project for Materials Genetic Engineering of Rare and Precious Metal(No.202002AB080001)+2 种基金the Yunnan Province Funds for Distinguished Young Scientists,(No.2019FJ005)the Science Research Foundation of Yunnan Provincial Education Department(No.2022J0441)the Sichuan Science and Technology Program(No.22QYCX0097)。
文摘Zeolitic Imidazolate Framework-8(ZIF-8)material was prepared by chemical precipitation method.The microstructure and physical properties of the as-prepared samples were characterized by XRD,BET,FESEM and UV spectrophotometer.The self-made four-channel measurement device was used to test the gas sensitivity of ZIF-8 material toward ethanol gas under photo-thermal synergistic excitation.The results showed that the sample was typical ZIF-8(E_(g)=4.96 eV)with a regular dodecahedron shape and the specific surface is up to 1793 m^(2)/g.The as-prepared ZIF-8 has a gas response value of 55.04 to 100 ppm ethanol at 75℃ and it shows good gas sensing selectivity and repeated stability.The excellent gas sensitivity can be attributed to the increase of free electron concentration in the ZIF-8 conduction band by photo-thermal synergistic excitation,and the large specific surface area of ZIF-8 material provides more active sites for gas-solid surface reaction.The reaction mechanism of ZIF-8 material under multi-field excitation was also discussed.
文摘电力系统架空线巡线机器人对于提高架空输电线的维护效率进而保障电力系统的安全稳定运行具有重要作用。针对架空线巡线机器人巡线过程中需要有效识别线路中的附属障碍物并采取相应障碍规避动作的问题,文章研究了基于深度学习的巡线机器人架空线附属障碍物识别方法。论述了基于深度学习的架空线巡线机器人系统的整体结构,在整体系统结构的基础上分析了YOLOv8(you only look once version 8)模型的结构及其应用,进而基于增强的架空线障碍物数据集对所述方法进行了有效性验证。实验结果表明,文中所述基于YOLOv8的巡线机器人障碍物识别模型具有更快的识别速度和更高的识别率,能够更好满足巡线机器人的避障需求。
