Design and Application of UAV Intelligent Inspection System for Transmission Lines Based on Cloud and Fog-edge Heterogeneous Collaborative Computing Architecture

doi:10.11930/j.issn.1004-9649.201907167

Abstract

Abstract: To solve the problems of the low computing capacity and low integration degree of the data processing platform of the existing unmanned aerial vehicle (UAV) inspection systems for transmission lines, a new UAV inspection system is proposed based on cloud and fog-edge heterogeneous collaborative computing architecture, and a detail introduction is made to the system architecture, network architecture and operation process. Through integration of the advanced artificial intelligence technology and the specific functions of UAV patrol inspection, an overall UAV inspection solution scheme is given based on the artificial intelligence technology, with such three main functions as the independent path planning, multi-UAV multi-task synergy and intelligent recognition being displayed. The proposed system can comprehensively upgrade the intelligent level and independent running ability of UAVs, and improve the efficiency and quality, of power transmission line inspection and reduce the operational cost.

Key words: cloud and fog-edge heterogeneous collaborative computing, unmanned aerial vehicle, intelligent inspection, path planning, intelligent defect identification

HUANG Zheng, WANG Yongqiang, WANG Hongxing, GAO Chao, BAI Cang. Design and Application of UAV Intelligent Inspection System for Transmission Lines Based on Cloud and Fog-edge Heterogeneous Collaborative Computing Architecture[J]. Electric Power, 2020, 53(4): 161-168.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.201907167

https://www.electricpower.com.cn/EN/Y2020/V53/I4/161

References

[1] 施孟佶, 秦开宇, 李凯, 等. 高压输电线路多无人机自主协同巡线设计与测试[J]. 电力系统自动化, 2017, 41(10): 117–122
SHI Mengji, QIN Kaiyu, LI Kai, et al. Design and testing on autonomous multi-UAV cooperation for high-voltage transmission line inspection[J]. Automation of Electric Power Systems, 2017, 41(10): 117–122
[2] 张文, 彭向阳, 陈锐民, 等. 基于无人机红外视频的输电线路发热缺陷智能诊断技术[J]. 电网技术, 2014, 38(5): 1334–1338
ZHANG Wen, PENG Xiangyang, CHEN Ruimin, et al. Intelligent diagnostic techniques of abnormal heat defect in transmission lines based on unmanned helicopter infrared video[J]. Power System Technology, 2014, 38(5): 1334–1338
[3] 吴功平, 曹珩, 皮渊, 等. 高压多分裂输电线路自主巡检机器人及其应用[J]. 武汉大学学报(工学版), 2012, 45(1): 96–102
WU Gongping, CAO Heng, PI Yuan, et al. An autonomous inspection robot for high voltage bundled transmission line and its application[J]. Engineering Journal of Wuhan University, 2012, 45(1): 96–102
[4] 彭向阳, 梁福逊, 钱金菊, 等. 基于机载红外影像纹理特征的输电线路绝缘子自动定位[J]. 高电压技术, 2019, 45(3): 922–928
PENG Xiangyang, LIANG Fuxun, QIAN Jinju, et al. Automatic recognition of insulator from UAV infrared image based on periodic textural feature[J]. High Voltage Engineering, 2019, 45(3): 922–928
[5] 王振华, 黄宵宁, 梁焜, 等. 基于四旋翼无人机的输电线路巡检系统研究[J]. 中国电力, 2012, 45(10): 59–62
WANG Zhenhua, HUANG Xiaoning, LIANG Kun, et al. Study on the transmission line inspection system based on quadrotor UAVs[J]. Electric Power, 2012, 45(10): 59–62
[6] 金立军, 王恒, 王文华, 等. 基于机器视觉和激光测距的输电线故障定位[J]. 同济大学学报(自然科学版), 2018, 46(12): 1745–1753
JIN Lijun, WANG Heng, WANG Wenhua, et al. Transmission line fault location based on machine vision and laser ranging[J]. Journal of Tongji University (Natural Science), 2018, 46(12): 1745–1753
[7] YEGANEH H, SALAHI A, POURMINA M A. A novel cost optimization method for mobile cloud computing by capacity planning of green data center with dynamic pricing[J]. Canadian Journal of Electrical and Computer Engineering, 2019, 42(1): 41–51.
[8] SARKAR S, CHATTERJEE S, MISRA S. Assessment of the suitability of fog computing in the context of internet of things[J]. IEEE Transactions on Cloud Computing, 2018, 6(1): 46–59.
[9] WEI F, CHEN S X, ZOU W X. A greedy algorithm for task offloading in mobile edge computing system[J]. China Communications, 2018, 15(11): 149–157.
[10] 罗隆福, 李冬, 钟杭. 基于改进RRT的无人机电力杆塔巡检路径规划[J]. 湖南大学学报(自然科学版), 2018, 45(10): 80–86
LUO Longfu, LI Dong, ZHONG Hang. Path planning of unmanned aircraft inspection for electric towers based on advanced RRT algorithm[J]. Journal of Hunan University (Natural Science), 2018, 45(10): 80–86
[11] 尹高扬, 周绍磊, 祁亚辉. 多无人机协同多任务分配研究[J]. 电光与控制, 2017, 24(1): 46–50,75
YIN Gaoyang, ZHOU Shaolei, QI Yahui. Cooperative multi-task assignment for multiple UAVs[J]. Electronics Optics & Control, 2017, 24(1): 46–50,75
[12] 田震, 王晓芳. 基于多基因遗传算法的异构多无人机协同任务分配[J]. 飞行力学, 2019, 37(1): 39–44
TIAN Zhen, WANG Xiaofang. Cooperative multiple task assignment for heterogeneous multi-UAVs with multi-chromosome genetic algorithm[J]. Flight Dynamics, 2019, 37(1): 39–44
[13] 武少华, 高岳林. 粒子群算法的改进与比较研究[J]. 合肥工业大学学报(自然科学版), 2019, 42(2): 184–188,194
WU Shaohua, GAO Yuelin. Improvement and comparison of particle swarm optimization[J]. Journal of Hefei University of Technology (Natural Science), 2019, 42(2): 184–188,194
[14] 刘壮, 杜勇, 陈怡, 等. ±500 kV直流输电线路直线塔无人机巡检安全距离仿真与试验[J]. 高电压技术, 2019, 45(2): 426–432
LIU Zhuang, DU Yong, CHEN Yi, et al. Simulation and experiment on the safety distance of typical +500 kV DC transmission lines and towers for UAV inspection[J]. High Voltage Engineering, 2019, 45(2): 426–432
[15] AIAA. Aircraft conflict detection and resolution using mixed geometric and collision cone approaches[R]. Aiaa Journal, 2004.
[16] MAKHDOOM I H, QIN S. Simultaneous arrival of multiple UAVs under imperfect communication[J]. Aircraft Engineering & Aerospace Technology, 2012, 84(1): 37–50.
[17] 彭向阳, 刘洋, 王柯, 等. 利用卷积神经网络进行绝缘子自动定位[J]. 武汉大学学报(信息科学版), 2019, 44(4): 563–569
PENG Xiangyang, LIU Yang, WANG Ke, et al. An automatically location method for insulator object based on CNNs[J]. Geomatics and Information Science of Wuhan University, 2019, 44(4): 563–569
[18] 许可.卷积神经网络在图像识别上的应用的研究[D]. 杭州: 浙江大学, 2012.
XU Ke. Study of convolutional neural network applied on image recognition[D]. Hangzhou: Zhejiang University, 2012.
[19] 陈文浩, 姚利娜, 李丰哲. 无人机电网巡检中的绝缘子缺陷检测与定位[J]. 计算机应用, 2019, 39(增刊1): 210–214
CHEN Wenhao, YAO Lina, LI Fengzhe. Insulator detection and location in UAV grid inspection[J]. Journal of Computer Applications, 2019, 39(S1): 210–214