This paper proposes a new deep learning framework for the location of broken insulators(in particular the self-blast glass insulator)in aerial images.We address the broken insulators location problem in a low signal-n...This paper proposes a new deep learning framework for the location of broken insulators(in particular the self-blast glass insulator)in aerial images.We address the broken insulators location problem in a low signal-noise-ratio(SNR)setting.We deal with two modules:1)object detection based on Faster R-CNN,and 2)classification of pixels based on U-net.For the first time,our paper combines the above two modules.This combination is motivated as follows:Faster R-CNN is used to improve SNR,while the U-net is used for classification of pixels.A diverse aerial image set measured by a power grid in China is tested to validate the proposed approach.Furthermore,a comparison is made among different methods and the result shows that our approach is accurate in real time.展开更多
为研究材料类型和参数对绝缘子电场强度和电位分布的影响,采用有限元法以支柱绝缘子为对象研究了柱体和伞裙材料分别为电瓷、玻璃、高温硫化(high temperature vulcanization,HTV)硅橡胶时绝缘子及附近场强、电位分布以及沿面和干弧路...为研究材料类型和参数对绝缘子电场强度和电位分布的影响,采用有限元法以支柱绝缘子为对象研究了柱体和伞裙材料分别为电瓷、玻璃、高温硫化(high temperature vulcanization,HTV)硅橡胶时绝缘子及附近场强、电位分布以及沿面和干弧路径上场强和电位,同时研究了材料的电阻率和相对介电常数对绝缘子附近场强和电位分布的影响。结果表明:支柱绝缘子场强度、电位分布极不均匀,上金具附近场强大、电位集中,从上到下沿面场强、电位下降速度有下降趋势,材料类型基本不影响整体场强和电位以及等位线;从最大场强和电位集中程度来看HTV>电瓷>玻璃;伞裙存在会畸变其附近场强,伞裙上表面与柱体交汇处、伞裙下表面各棱底部附近场强畸变相对严重。正常范围内绝缘材料的体积电阻率对场强和电位分布未见影响;随着相对介电常数的增加最大场强减少,沿面和干弧路径上电位分布更均匀,但伞裙附近场强畸变加剧。展开更多
基金This work was supported in part by the National Natural Science Foundation of China(No.61571296)the National Science Foundation of USA(No.CNS-1619250).
文摘This paper proposes a new deep learning framework for the location of broken insulators(in particular the self-blast glass insulator)in aerial images.We address the broken insulators location problem in a low signal-noise-ratio(SNR)setting.We deal with two modules:1)object detection based on Faster R-CNN,and 2)classification of pixels based on U-net.For the first time,our paper combines the above two modules.This combination is motivated as follows:Faster R-CNN is used to improve SNR,while the U-net is used for classification of pixels.A diverse aerial image set measured by a power grid in China is tested to validate the proposed approach.Furthermore,a comparison is made among different methods and the result shows that our approach is accurate in real time.
文摘为研究材料类型和参数对绝缘子电场强度和电位分布的影响,采用有限元法以支柱绝缘子为对象研究了柱体和伞裙材料分别为电瓷、玻璃、高温硫化(high temperature vulcanization,HTV)硅橡胶时绝缘子及附近场强、电位分布以及沿面和干弧路径上场强和电位,同时研究了材料的电阻率和相对介电常数对绝缘子附近场强和电位分布的影响。结果表明:支柱绝缘子场强度、电位分布极不均匀,上金具附近场强大、电位集中,从上到下沿面场强、电位下降速度有下降趋势,材料类型基本不影响整体场强和电位以及等位线;从最大场强和电位集中程度来看HTV>电瓷>玻璃;伞裙存在会畸变其附近场强,伞裙上表面与柱体交汇处、伞裙下表面各棱底部附近场强畸变相对严重。正常范围内绝缘材料的体积电阻率对场强和电位分布未见影响;随着相对介电常数的增加最大场强减少,沿面和干弧路径上电位分布更均匀,但伞裙附近场强畸变加剧。
