基于全自动跟拍的多功能车载巡检技术

doi:10.11930/j.issn.1004-9649.201812091

中国电力 ›› 2020, Vol. 53 ›› Issue (5): 18-23.DOI: 10.11930/j.issn.1004-9649.201812091

基于全自动跟拍的多功能车载巡检技术

王海鹏¹, 文艳², 李建祥¹, 周大洲¹, 杨尚伟¹

1. 国网智能科技股份有限公司，山东济南 250101;
2. 国网山东省电力公司，山东济南 250002

收稿日期:2018-12-25 修回日期:2019-12-10 发布日期:2020-05-05
作者简介:王海鹏(1982-),男,硕士,高级工程师,从事电力机器人技术研究,E-mail:1528718898@qq.com;杨尚伟(1987-),男,通信作者,硕士,工程师,从事电力机器人技术研究,E-mail:979893971@qq.com
基金资助:
国家电网有限公司科技项目(配电线路车载、沟道内无人机智能巡检关键技术研究与开发，5206001601XX)

Multifunctional Vehicle Inspection Technology Based on Full-Automatic Tracking

WANG Haipeng¹, WEN Yan², LI Jianxiang¹, ZHOU Dazhou¹, YANG Shangwei¹

1. State Grid Intelligence Technology Co., Ltd., Jinan 250101, China;
2. State Grid Shandong Electric Power Company, Jinan 250002, China

Received:2018-12-25 Revised:2019-12-10 Published:2020-05-05
Supported by:
This work is supported by Science and Technology Project of SGCC (Key Research and Development of Distribution Line Vehicle and Intelligent Inspection of UAV in Channels, No.5206001601XX)

摘要/Abstract

摘要： 配电线路巡检主要采用“人工走巡”方式，存在巡检耗时长、巡检质量低、缺陷易发展、记录易出错等问题。为解决上述问题，研究了全自动跟拍的多功能车载巡检技术，设计开发了配电网车载巡检系统。该系统以巡检车辆为移动平台，搭载集成多功能检测模块的“复眼探头”，配置融合智能边缘算法的车内控制中心，实现线路自动追踪、数据同步采集、缺陷就地研判和数据实时回传。该系统在某配电线路巡检中进行了试点应用，各项功能均达到预期目标，具有工程实践和推广意义。

关键词: 配电线路巡检, 多功能车载巡检技术, 智能边缘算法, 线路自动追踪, 数据同步采集

Abstract: At present, the manual patrol mode is widely used for distribution line inspection, which has such problems as time-consuming, poor quality, defect- omission, and error-prone records. To resolve these problems, a research is made on the multifunctional vehicle inspection technology with full-automatic tracking, and a distribution network vehicle inspection system is designed. The system uses the patrol vehicle as mobile platform, which is equipped with compound-eye probe of multifunctional detection module and vehicle control center based on intelligent edge algorithms. It can realize automatic line tracking, data synchronization acquisition, on-site analysis of defects, and real-time data transmission. The system has been applied in distribution lines inspection and all the functions have reached the expected objective.

Key words: distribution line inspection, multifunctional vehicle inspection technology, intelligent edge algorithms, automatic line tracking, data synchronization acquisition

王海鹏, 文艳, 李建祥, 周大洲, 杨尚伟. 基于全自动跟拍的多功能车载巡检技术[J]. 中国电力, 2020, 53(5): 18-23.

WANG Haipeng, WEN Yan, LI Jianxiang, ZHOU Dazhou, YANG Shangwei. Multifunctional Vehicle Inspection Technology Based on Full-Automatic Tracking[J]. Electric Power, 2020, 53(5): 18-23.

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参考文献

[1] 曾懿辉, 何通, 郭圣, 等. 基于差分定位的输电线路多旋翼无人机智能巡检[J]. 中国电力, 2019, 52(7): 24–30
ZENG Yihui, HE Tong, GUO Sheng, et al. Research on multi-rotor UAV intelligent power line inspection based on differential positioning[J]. Electric Power, 2019, 52(7): 24–30
[2] 吴欣, 高正浩, 陈俣霏, 等. 基于RFID与三维可视化技术的固定资产管理系统设计[J]. 电子设计工程, 2018, 26(18): 107–112
WU Xin, GAO Zhenghao, CHEN Yufei, et al. Design of fixed assets management system based on RFID and 3D visualization technology[J]. Electronic Design Engineering, 2018, 26(18): 107–112
[3] 章兵, 魏永, 郑春着. 基于ESB的电网GIS平台与生产管理系统集成实现与应用[J]. 能源与环保, 2017(10): 204–207
ZHANG Bing, WEI Yong, ZHENG Chunzhuo. Integration implementation and application of power grid GIS platform and production management system based on ESB[J]. China Energy and Environmental Protection, 2017(10): 204–207
[4] 王浩, 韩敏, 董杰. 基于Android平台的车载视频智能监控系统的研究[J]. 电子技术应用, 2016, 42(6): 121–123, 127
WANG Hao, HAN Min, DONG Jie. Research of vehicle intelligent video surveillance system based on Android platform[J]. Application of Electronic Technique, 2016, 42(6): 121–123, 127
[5] 郭键. 基于GPS的物流车辆智能监控系统设计[J]. 计算机测量与控制, 2017, 25(9): 87–90, 109
GUO Jian. Design of intelligent monitoring system for logistics vehicle based on GPS[J]. Computer Measurement & Control, 2017, 25(9): 87–90, 109
[6] 徐军, 杨雄, 陈怡佳, 等. 一种双模控制的自主跟随机器人系统设计[J]. 自动化仪表, 2018, 39(3): 48–51
XU Jun, YANG Xiong, CHEN Yijia, et al. Design of the autonomous following robot system with dual-mode control[J]. Process Automation Instrumentation, 2018, 39(3): 48–51
[7] 张巨, 陈宏盛, 刘雨. 车辆GPS定位的一般性问题研究[J]. 国防科技大学学报, 2000, 22(1): 31–35
ZHANG Ju, CHEN Hongsheng, LIU Yu. Universal problems of vehicle GPS positioning technique[J]. Journal of National University of Defense Technology, 2000, 22(1): 31–35
[8] 马宗正, 马海舒, 马涛, 等. 基于射频识别技术的工件定位系统设计与实现[J]. 现代制造工程, 2017(7): 109–113, 104
MA Zongzheng, MA Haishu, MA Tao, et al. Application of RFID technology to the workpiece localization[J]. Modern Manufacturing Engineering, 2017(7): 109–113, 104
[9] 付余路, 张华, 刘冉, 等. 融合RFID相位与激光的快速动态目标定位[J]. 计算机工程, 2018, 44(8): 308–314
FU Yulu, ZHANG Hua, LIU Ran, et al. Fast dynamic object localization fusing with RFID phase and laser[J]. Computer Engineering, 2018, 44(8): 308–314
[10] 罗文慧, 董宝田, 王泽胜. 基于车路协同的车辆定位算法研究[J]. 西南交通大学学报, 2018, 53(5): 1072–1077
LUO Wenhui, DONG Baotian, WANG Zesheng. Algorithm based on cooperative vehicle infrastructure systems[J]. Journal of Southwest Jiaotong University, 2018, 53(5): 1072–1077
[11] 陶波, 龚泽宇, 丁汉. 机器人无标定视觉伺服控制研究进展[J]. 力学学报, 2016, 48(4): 767–783
TAO Bo, GONG Zeyu, DING Han. Survey on uncalibrated robot visual servoing control[J]. Chinese Journal of Theoretical and Applied Mechanics, 2016, 48(4): 767–783
[12] 魏巍, 老松杨, 康来, 等. 基于三维光场的静态场景前景分割[J]. 北京航空航天大学学报, 2015, 41(7): 1330–1336
WEI Wei, LAO Songyang, KANG Lai, et al. 3D light fields based foreground segmentation in static scenes[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(7): 1330–1336
[13] 张俊雄, 王凯, 张良, 等. 横移对行控制系统设计与试验分析[J]. 江苏大学学报(自然科学版), 2017, 38(4): 423–427
ZHANG Junxiong, WANG Kai, ZHANG Liang, et al. Design and experimental analysis of side-shift row-follow control system[J]. Journal of Jiangsu University(Natural Science Edition), 2017, 38(4): 423–427
[14] 洪学海, 汪洋. 边缘计算技术发展与对策研究[J]. 中国工程科学, 2018, 20(2): 20–26
HONG Xuehai, WANG Yang. Edge computing technology: development and countermeasures[J]. Engineering Science, 2018, 20(2): 20–26
[15] 郭风顺, 郭海波. 电力系统视频监控和图像识别的现状与展望[J]. 电视技术, 2013, 37(z2): 437–439
GUO Fengshun, GUO Haibo. Status and prospect of video monitoring and image recognition in electric power system[J]. Video Engineering, 2013, 37(z2): 437–439
[16] 杨文柱, 刘晴, 王思乐, 等. 基于深度卷积神经网络的羽绒图像识别[J]. 郑州大学学报(工学版), 2018, 39(2): 11–17
YANG Wenzhu, LIU Qing, WANG Sile, et al. Down image recognition based on deep convolution neural networks[J]. Journal of Zhengzhou University(Engineering Science), 2018, 39(2): 11–17
[17] AKINLAR C, TOPAL C. Edlines: real-time line segment detection by edge drawing (Ed)[C]//2011 18th IEEE International Conference on Image Processing, September 11-14, 2011. Brussels, Belgium. IEEE, 2011: 2837-2840.
[18] HAN J Q. From PID to active disturbance rejection control[J]. IEEE Transactions on Industrial Electronics, 2009, 56(3): 900–906.
[19] 宋朋涛, 李超, 徐莉婷, 等. 基于个人计算机的智能家居边缘计算系统[J]. 计算机工程, 2017, 43(11): 1–7
SONG Pengtao, LI Chao, XU Liting, et al. Edge computing system for smart home based on personal computer[J]. Computer Engineering, 2017, 43(11): 1–7
[20] 张佳乐, 赵彦超, 陈兵, 等. 边缘计算数据安全与隐私保护研究综述[J]. 通信学报, 2018, 39(3): 1–21
ZHANG Jiale, ZHAO Yanchao, CHEN Bing, et al. Survey on data security and privacy-preserving for the research of edge computing[J]. Journal on Communications, 2018, 39(3): 1–21
[21] 张琪, 胡宇鹏, 嵇存, 等. 边缘计算应用: 传感数据异常实时检测算法[J]. 计算机研究与发展, 2018, 55(3): 524–536
ZHANG Qi, HU Yupeng, JI Cun, et al. Edge computing application: real-time anomaly detection algorithm for sensing data[J]. Journal of Computer Research and Development, 2018, 55(3): 524–536

基于全自动跟拍的多功能车载巡检技术

Multifunctional Vehicle Inspection Technology Based on Full-Automatic Tracking

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基于全自动跟拍的多功能车载巡检技术

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