电力线电晕放电紫外图像精确分割方法
[1] 王胜辉. 基于紫外成像的污秽悬式绝缘子放电检测及评估[D].北京: 华北电力大学 , 2011. WANG Shenghui. Detection and Assessment of Contaminated Suspension Insulator Discharge Based on Ultraviolet Imaging[D]. Beijing: North China Electric Power University, 2021.
[2] 张显. 基于紫外检测技术的绝缘子电晕放电特性研究 [D].长沙: 长沙理工大学, 2016. ZHANG Xian. Research the Characteristics of Insulator Corona Discharge based on UV Imaging Technology[D]. Changsha: Changsha University of Science & Technology, 2016.
[3] 赵太飞 , 李晗辰 , 张港, 等. 无人机巡线的紫外放电检测研究 [J]. 电子测量与仪器学报, 2020, 34(12): 36-42. ZHAO Taifei, LI Hanchen, ZHANG Gang, et al. Ultraviolet discharge detection research for UAV patrol[J]. Journal of Electronic Measurement and Instrumentation, 2020, 34(12): 36-42 .
[4] WANG S, LV F, LIU Y. Estimation of discharge magnitude of composite insulator surface corona discharge based on ultraviolet imaging method[J]. IEEE Transactions on Dielectrics & Electrical Insulation, 1328 2014, 21(4): 1697-1704.
[5] ZHANG Z, WEI Z, ZHANG D, et al. Comparison of different characteristic parameters acquired by UV imager in detecting corona discharge[J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2016, 23(3): 1597-1604.
[6] LIN Y, CHEN Y, ZHOU J, et al. Gray Standard deviation based ultraviolet image segmentation for electrical equipment[C]//Journal of Physics: Conference Series, 2019, 1169(1): 012051.
[7] 艾建勇 , 金立军. 基于紫外图像的接触网棒瓷绝缘子污秽状态检测 [J]. 电工技术学报, 2016, 31(10): 112-118. AI Jianyong, JIN Lijun. Rod porcelain insulator filth state detection of catenary based on ultraviolet image[J]. Transactions of China Electrotechnical Society, 2016, 31(10): 112-118.
[8] 刘云鹏 , 李泳霖, 裴少通, 等. 基于紫外成像技术的彩色光斑映射识别算法研究[J].华北电力大学学报 : 自然科学版, 2022(4): 1-9 . LIU Yunpeng, LI Yonglin, PEI Shaotong, et al. Research on color spot mapping recognition algorithm based on ultraviolet imaging technology[J]. Journal of North China Electric Power University: Nature Science, 2022(4): 1-9.
[9] 李勋, 张宏钊, 胡元潮 , 等. 基于 C-V模型的电晕放电紫外成像分割及特征量研究 [J].高压电器, 2017, 53(8): 123-128. LI Xun, ZHANG Hongzhao, HU Yuanchao, et al. Ultraviolet image segmentation and characteristic quantities of corona discharge based on C-V model[J]. High Voltage Apparatus, 2017, 53(8): 123-128.
[10] 闵超波, 顾燕, 杨锋. 基于泊松分布的日盲紫外电晕检测 [J].红外技术, 2020, 42(8): 715-721. MIN Chaobo, GU Yan, YANG Feng. Corona detection of solar-blind ultraviolet via Poisson distribution[J]. Infrared Technology, 2020, 42(8): 715-721.
[12] Ronneberger O, Fischer P, Brox T. U-net: Convolutional networks for biomedical image segmentation[C]//Medical Image Computing and Computer-Assisted Intervention–MICCAI , 2015: 234-241
[13] Otsu N. A threshold selection method from gray-level Histograms[J]. IEEE Transactions on Systems Man & Cybernetics, 2007, 9(1): 62-66.
[14] Kapur J, Sahoo P K, Wong A. A new method for gray-level picture thresholding using the entropy of the histogram[J]. Computer Vision, Graphics, and Image Processing, 1985, 29(3): 273-285.
[15] Kittler J, Illingworth J. Minimum error thresholding[J]. Pattern Recognition, 1986, 19(1): 41-47.
[16] XU X, XU S, JIN L, et.al. Characteristic analysis of Otsu threshold and its applications[J]. Pattern Recognition Letters, 2011, 32(7): 956-961.
[17] 袁小翠, 吴禄慎, 陈华伟. 基于 Otsu方法的钢轨图像分割[J].光学精密工程, 2016, 24(7): 1772-1781. YUAN Xiaocui, WU Lushen, CHEN Huawei. Rail image segmentation based on Otsu threshold method[J]. Optics and Precision Engineering, 2006, 24(7): 1772-1781.
刘赫, 赵天成, 刘俊博, 矫立新, 袁小翠, 许志浩. 电力线电晕放电紫外图像精确分割方法[J]. 红外技术, 2023, 45(12): 1322. LIU He, ZHAO Tiancheng, LIU Junbo, QIAO Lixin, YUAN Xiaocui, XU Zhihao. New Corona Discharge Segmentation Method for Power Line Based on Ultraviolet Image[J]. Infrared Technology, 2023, 45(12): 1322.