Citation: | GU Yaxiong, FENG Shuangshuang. A Holistic Segmentation Method for Faulty Electrical Equipment under Complex Background[J]. Infrared Technology , 2023, 45(5): 455-462. |
[1] |
王启银, 薛建东, 任新辉. 一种自适应的变电站设备红外图像分割方法[J]. 红外技术, 2016, 38(9): 770-773. http://hwjs.nvir.cn/article/id/hwjs201609010
WANG Qiyin, XUE Jiandong, REN Xinhui. An adaptive infrared image segmentation method for substation equipment[J]. Infrared Technology, 2016, 38(9): 770-773. http://hwjs.nvir.cn/article/id/hwjs201609010
|
[2] |
王小芳, 毛华敏. 一种复杂背景下的电力设备红外图像分割方法[J]. 红外技术, 2019, 41(12): 1111-1116. http://hwjs.nvir.cn/article/id/hwjs201912004
WANG Xiaofang, MAO Huamin. Infrared image segmentation method for power equipment under complex background[J]. Infrared Technology, 2019, 41(12) : 1111-1116. http://hwjs.nvir.cn/article/id/hwjs201912004
|
[3] |
林颖, 郭志红, 陈玉峰. 基于卷积递归神经网络的电流互感器红外故障图像诊断[J]. 电力系统保护与控制, 2015, 43(16): 87-94. DOI: 10.7667/j.issn.1674-3415.2015.16.013
LIN Ying, GUO Zhihong, CHEN Yufeng. Convolutional-recursive network based current transformer infrared fault image diagnosis[J]. Power System Protection and Control, 2015, 43(16): 87-94. DOI: 10.7667/j.issn.1674-3415.2015.16.013
|
[4] |
陈跃伟, 彭道刚, 夏飞, 等. 基于区域生长法和BP神经网络的红外图像识别[J]. 激光与红外, 2018, 48(3): 401-408. DOI: 10.3969/j.issn.1001-5078.2018.03.024
CHEN Yuewei, PENG Daogang, XIA Fei, et al. Infrared image recognition based on region growing method and BP neural network[J]. Laser & Infrared, 2018, 48(3): 401-408. DOI: 10.3969/j.issn.1001-5078.2018.03.024
|
[5] |
贾鑫, 张惊雷, 温显斌. 双监督信号深度学习的电气设备红外故障识别[J]. 红外与激光工程, 2018, 285(7): 32-38. https://www.cnki.com.cn/Article/CJFDTOTAL-HWYJ201807005.htm
JIA Xin, ZHANG Jinglei, WEN Xianbin. Infrared fault identification of electrical equipment based on dual supervised signal deep learning[J]. Infrared and Laser Engineering, 2018, 285(7): 32-38. https://www.cnki.com.cn/Article/CJFDTOTAL-HWYJ201807005.htm
|
[6] |
尹阳. 基于红外图像的变电站设备识别与热状态监测系统研究[D]. 西安: 西安科技大学, 2018.
YIN Yang. Research on Substation Equipment Identification and Thermal State Monitoring System Based on Infrared Image[D]. Xi'an: Xi'an University of Science and Technology, 2018.
|
[7] |
余成波, 曾亮, 张林. 基于OTSU和区域生长的电气设备多点故障分割[J]. 红外技术, 2018, 40(10): 1008-1012. http://hwjs.nvir.cn/article/id/hwjs201810013
YU Chengbo, ZENG Liang, ZHANG Lin. Multipoint fault segmentation for electrical equipment based on OTSU and regional growth[J]. Infrared Technology, 2018, 40(10): 1008-1012. http://hwjs.nvir.cn/article/id/hwjs201810013
|
[8] |
赵梦. 基于红外图像的电力设备故障分析研究[D]. 西安: 西安理工大学, 2020.
ZHAO Meng. Research on Fault Analysis of Power Equipment Based on Infrared Image [D]. Xi 'an: Xi 'an University of Technology, 2020.
|
[9] |
任新辉. 基于红外技术的变电站设备识别与热故障诊断[D]. 成都: 西南交通大学, 2016.
REN Xinhui. Substation Equipment Identification and Thermal Fault Diagnosis Based on Infrared Technology[D]. Chengdu: Southwest Jiaotong University, 2016.
|
[10] |
张锦文. 变电站电气设备红外图像分割方法研究[D]. 北京: 华北电力大学, 2018.
ZHANG Jinwen. Research on Infrared Image Segmentation Method of Electrical Equipment in Substation[D]. Beijing: North China Electric Power University, 2018.
|
[11] |
康龙. 基于红外图像处理的变电站设备故障诊断[D]. 北京: 华北电力大学, 2016.
KANG Long. Fault Diagnosis of Substation Equipment Based on Infrared Image Processing[D]. Beijing: North China Electric Power University, 2016.
|
[12] |
郭铭. 基于红外成像技术的变电站电气设备热故障诊断研究[D]. 阜新: 辽宁工程大学, 2019.
GUO Ming. Research on Thermal Fault Diagnosis of Electrical Equipment In Substation Based on Infrared Imaging Technology[D]. Fuxin: Liaoning Engineering University, 2019.
|
[13] |
刘辉, 石小龙. 结合显著性和超像素改进的GrabCut图像分割[J]. 红外技术, 2018, 40(1): 55-61. http://hwjs.nvir.cn/article/id/hwjs201801010
LIU H, SHI X L. Improved grab cut segmentation based on salience and superpixels[J]. Infrared Technology, 2018, 40(1): 55-61. http://hwjs.nvir.cn/article/id/hwjs201801010
|
[14] |
Levinshtein A, Stere A, Kutulakos K N, et al. Turbopixels: fast superpixels using geometric flows[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31(12): 2290-2297. DOI: 10.1109/TPAMI.2009.96
|
[15] |
REN X F, Malik J. Learning a classification model for segmentation[C]//Proceedings of the Ninth IEEE International Conference on Computer Vision, 2003: 10.
|
[16] |
Veksler O, Boykov Y, Mehrani P. Superpixels and supervoxels in an energy optimization framework[C]//European Conference on Computer Vision(ECCV), 2013: 13-35.
|
[17] |
赵文涛, 曹昕鸷, 田志勇. 基于自适应阈值区域生长的红外舰船目标分割方法[J]. 红外技术, 2018, 40(2): 158-163. http://hwjs.nvir.cn/article/id/hwjs201802010
ZHAO Wentao, CAO Xinzhi, TIAN Zhiyong. Infrared ship target segmentation based on adaptive threshold region growth[J]. Infrared Technology, 2018, 40(2): 158-163. http://hwjs.nvir.cn/article/id/hwjs201802010
|
[18] |
ZUCKER S W. Region growing: Childhood and adolescence[J]. Computer Graphics Image Processing, 1976(5): 382-399. http://ar.newsmth.net/att/dfd6fe6c43255/Region_growing_Childhood_and_adolescence.pdf
|
[19] |
LI J, QIU M, ZHANG Y, et al. A fast obstacle detection method by fusion of double-layer region growing algorithm and grid-SECOND detector[J]. IEEE Access, 2020, 9: 32053-32063. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9309211
|
[20] |
WANG W, WANG X J, LIU X W, et al. Image segmentation algorithm based on image complexity[J]. Journal of Detection & Control, 2015, 37(3): 5-9.
|
[1] | XU Shiwen, WANG Heng, ZHANG Hua, PANG Jie. Human Fall Detection Method Based on Key Points in Infrared Images[J]. Infrared Technology , 2021, 43(10): 1003-1007. |
[2] | ZHANG Zhipeng, SHAO Xuejun, PANG Qing. Research on the Key Technology of 3D Laser Inverted Scanning[J]. Infrared Technology , 2021, 43(8): 752-756. |
[3] | A Method of Object Tracking Based on Feature Point Matching[J]. Infrared Technology , 2016, 38(7): 597-601. |
[4] | ZHAO De-li, ZHU You-pan, LI Yan, ZENG Bang-ze, PAN Chao, LUO Lin, WU Cheng. Investigation on Infrared and Low Light Level Image Registration Algorithm Based on Point Feature and Freeman Chain Code[J]. Infrared Technology , 2015, (6): 467-471. |
[5] | ZHAO De-li, ZHU You-pan, WU Cheng, LI Ze-min, ZENG Bang-ze, LUO Lin, YANG Peng-wei, WANG Bing, LI Yan. Investigation on Improved Infrared Image Registration Algorithm Based on Point Feature and Gray Feature[J]. Infrared Technology , 2014, (10): 820-826. |
[6] | YU Hong-sheng, JIN Wei-qi. SIFT Key-points Self-adaptive Extraction Algorithm for Video Images[J]. Infrared Technology , 2013, (12): 768-772. |
[7] | YANG Li, YANG Hua. The Key Techniques and Applications of Infrared False Target[J]. Infrared Technology , 2006, 28(9): 531-534. DOI: 10.3969/j.issn.1001-8891.2006.09.009 |
[8] | ZHAO Qin, ZHOU Tao, SHU Qin. Discussion of Image Registration Based on Feature Points[J]. Infrared Technology , 2006, 28(6): 327-330. DOI: 10.3969/j.issn.1001-8891.2006.06.005 |
[9] | Study on the Key Techniques of the Imaging Infrared Guidance for AAM[J]. Infrared Technology , 2003, 25(4): 45-48. DOI: 10.3969/j.issn.1001-8891.2003.04.011 |
[10] | Modification of the Infrared Point Measurement for Temperature[J]. Infrared Technology , 2002, 24(3): 49-51,55. DOI: 10.3969/j.issn.1001-8891.2002.03.013 |
1. |
邢志坤. 基于LabVIEW的变电站移动机器人轨迹跟踪虚拟仿真系统设计. 自动化与仪表. 2024(07): 67-71 .
![]() | |
2. |
李辉,余大成,陈耀. 基于OWA算子和CWAA算子的变电站巡视周期优化. 广西电力. 2024(05): 50-54 .
![]() |