###
计算机系统应用:2018,27(12):40-46
本文二维码信息
码上扫一扫!
基于卷积神经网络的无人机油气管线巡检监察系统
刘松林1, 朱永丰1,2, 张哲2, 牛俊伟3
(1.信息工程大学, 郑州 450001;2.河南浩宇空间数据科技有限责任公司, 郑州 450001;3.郑州信大先进技术研究院, 郑州 450001)
UAV Oil/Gas Pipeline Inspection System Based on Convolutional Neural Network
LIU Song-Lin1, ZHU Yong-Feng1,2, ZHANG Zhe2, NIU Jun-Wei3
(1.Information Engineering University, Zhengzhou 450001, China;2.Henan Haoyu Spatial Information Technology Co. Ltd., Zhengzhou 450001, China;3.Zhengzhou Xinda Institute of Advanced Technology, Zhengzhou 450001, China)
摘要
图/表
参考文献
相似文献
本文已被:浏览 29次   下载 19
投稿时间:2018-05-02    修订日期:2018-05-24
中文摘要: 为满足深埋式油气管道巡检监察需求,以及解决常规人工巡检手段效率低、时效性差、安全性低等问题,通过结合人机飞行平台、卷积神经网络算法及计算机系统集成技术,设计并开发了一套基于卷积神经网络的人机油气管线巡检监察系统,为油气管线的巡检监察工作提供技术支撑.本文首先介绍了巡检监察系统的总体设计方案、及作业流程进行了介绍;其次对系统组成进行了详细介绍,整个系统由人机飞行平台、神经网络目标检测系统、人机巡检监察管理系统以及人机巡检执法终端四大子系统组成,人机飞行平台以油动固定翼人机为飞行载体,搭载高清相机进行数据采集,神经网络目标检测系统对影像数据进行自动检测、识别、搜索沿线工程车辆和管线隐患的目标,人机巡检监察管理系统实现数据信息的存储管理及分发推送,人机巡检执法终端接收隐患目标推送信息并进行现场快速执法;最后,对该系统的应用情况及后续的发展方向进行了总结和展望.目前,该系统成功应用于河南、甘肃等省份的油气管线巡检监察作业中,结果表明系统满足油气管线巡检监察的业务需求.
Abstract:To address the needs of deep-buried oil and gas pipeline inspection and supervision, as well as the problems of low efficiency, poor timeliness, and low safety of conventional manual inspections, we design and develop a UAV oil/gas pipeline inspection system which combines UAV, convolutional neural network algorithms, and computer system integration technologies. Firstly, we introduce the overall design plan and operation flow of the patrol inspection system. Secondly, we present the system components. The system consists of four subsystems:UAV flight platform, neural network target detection system, UAV inspection management system, and enforcement terminals. The UAV flight platform uses oil-moving fixed-wing UAVs as the flight carrier, carries high-definition cameras for data acquisition, and the neural network target detection system automatically reads the image data, to detect, identify, and search the hidden dangers of engineering vehicles and pipelines along the route. The UAV inspection management system realizes the storage, management, and distribution of data information. The enforcement terminals receive hidden target information and perform rapid on-site enforcement. Finally, the application of the system and the subsequent development direction are summarized and forecasted. The system has been successfully applied to oil and gas pipeline inspection and supervision operations in Henan, Gansu, and other provinces. The results show that the system meets the field needs of oil and gas pipeline inspection and supervision.
文章编号:     中图分类号:    文献标志码:
基金项目:
引用文本:
刘松林,朱永丰,张哲,牛俊伟.基于卷积神经网络的无人机油气管线巡检监察系统.计算机系统应用,2018,27(12):40-46
LIU Song-Lin,ZHU Yong-Feng,ZHANG Zhe,NIU Jun-Wei.UAV Oil/Gas Pipeline Inspection System Based on Convolutional Neural Network.COMPUTER SYSTEMS APPLICATIONS,2018,27(12):40-46

用微信扫一扫

用微信扫一扫