|本期目录/Table of Contents|

[1]武晓蕊,郑 琳,余 强,等.基于SURF的变电检测仪器面板数据精准定位方法[J].工业仪表与自动化装置,2021,(05):88-93.[doi:10.19950/j.cnki.cn61-1121/th.2021.05.019]
 WU Xiaorui,ZHENG Lin,YU Qiang,et al.Accurate positioning method of panel data of subversion testing instrument based on SURF transform[J].Industrial Instrumentation & Automation,2021,(05):88-93.[doi:10.19950/j.cnki.cn61-1121/th.2021.05.019]
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基于SURF的变电检测仪器面板数据精准定位方法

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2021年05期
页码:
88-93
栏目:
出版日期:
2021-10-15

文章信息/Info

Title:
Accurate positioning method of panel data of subversion testing instrument based on SURF transform
作者:
武晓蕊1郑 琳1余 强1李 佳1罗 浪1吴宇睿2许志浩2
1.国网湖北省电力有限公司检修公司,湖北 武汉 430050;
2.南昌工程学院,江西 南昌 330099
Author(s):
WU Xiaorui1ZHENG Lin1YU Qiang1LI Jia1LUO Lang1WU Yurui2XU Zhihao2
1.maintenance company of State Grid Hubei Electric Power Co., Ltd., Wuhan 430050,China;
2. Nanchang Institute of Technology, Nanchang, 330099, China
关键词:
仪器面板尺度不变性精准定位鲁棒性
Keywords:
instrument panel scale invariance precise positioning robustness
分类号:
TM932
DOI:
10.19950/j.cnki.cn61-1121/th.2021.05.019
文献标志码:
A
摘要:
提出了一种基于尺度不变性特征变换的检测仪器面板关键数据精准定位方法,针对变电检测常用仪器在分辨率变化、角度变化、光线变化、雨水/积灰/泥土杂质干扰等状态下共1020张图片进行了关键数据定位测试。结果表明,该方法对以上干扰均具有良好的特征定位鲁棒性,对拍摄角度不超过45°的整体随机样本的特征定位准确率达96%以上,可用于复杂现场环境下变电检测仪器面板数据精准定位及提取辅助。
Abstract:
A method for precise positioning of key data of detection instrument panels based on scale invariance feature transformation is proposed.Commonly used instruments for substation detection have a total of 1020 in terms of resolution change,angle change,light change,rain/ash/soil impurity interference,etc.A key data positioning test was performed on this picture, and the results show that the method has good feature positioning robustness against the above interference,and the feature positioning accuracy of the overall random sample with a shooting angle of not more than 45° is over 96%,which can be used for Accurate positioning and extraction assistance for panel data of substation detection instrument in complex field environment.

参考文献/References:

[1] XING H , QIAN A , QIU R C , et al. A big data architecture design for smart grids based on random matrix theory[J]. IEEE Transactions on Smart Grid, 2017, 8(2):674-686.

[2] CHU L, QIU R C, HE X, et al. Massive streaming PMU data modeling and analytics in smart grid state evaluation based on multiple high-dimensional covariance tests[J].IEEE Transactions on Big Data, 2018, 4(1): 55-64.
[3] HE X, CHU L, QIU R C, et al. Invisible units detection and estimation based on random matrix theory[J]. IEEE Transactions on Power Systems, 2019, 35(3): 1846-1855.?div>[4] 杨龙.电气试验数据现场记录分析系统的设计与实现[D].四川:电子科技大学,2019.
[5] 郑昌庭,王俊,郑克.基于图像识别的变电站巡检机器人仪表识别研究[J].工业仪表与自动化装置,2020(05):57-61.
[6] 虎玲,常霞,纪峰.图像边缘检测方法研究新进展[J].现代电子,2018,41(23):32-37.
[7] 杨鼎鼎,陈世强,刘静漪.基于车牌背景和字符颜色特征的车牌定位算法[J].计算机应用与软件,2018,35(12):216-221.
[8] 陈宏照,谢正光,卢海伦.颜色与边缘纹理相结合的车牌定位方法[J].现代电子技术,2018,41(21):67-70+75.
[9] 吕秀丽,杨士东.基于像素间双通道差异值的车牌定位算法[J].工业仪表与自动化装置,2020(02):128-130+135.
[10] 巩方超,王硕禾.基于SURF和FLANN算法的变电所仪表定位与读数识别[J].石家庄铁道大学学报(自然科学版),2020,33(01):110-115.
[11] 刘宏利,吕俊杰,邵磊,等.基于多特征融合的仪表屏幕定位方法[J].现代电子技术,2021,44(02):22-26.
[12] 刘爽,崔国光,刘同海,等.基于旋转校正和滑动窗口定位的智能仪表字符识别[J].电测与仪表,2013,50(06):20-23.

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备注/Memo

备注/Memo:
收稿日期:2021-04-22

基金项目:
国网湖北省电力有限公司检修公司科技项目《输变电设备检测数据采集分析模式及关键技术研究》(52152020003J)

作者简介:
武晓蕊(1990),女,硕士,主要从事高电压与绝缘技术方向的工作。
更新日期/Last Update: 1900-01-01