智能机器人巡检油气管道异常状态激光点云定位预警方法  

Laser Point Cloud Positioning and Early Warning Method for Intelligent Robot Inspection of Abnormal State of Oil and Gas Pipelines

作　　者：李明昊 杜楠 Li Minghao;Du Nan(College of Mechanical and Transportation Engineering China University of Petroleum,Beijing 102249,China;Department of Computer Science and Technology,Tangshan Normal University,Tangshan 063000,China;School of Communications and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[1]中国石油大学(北京)机械与储运工程学院,北京102249 [2]唐山师范学院计算机科学技术系,唐山063000 [3]重庆邮电大学通信与信息工程学院,重庆400065

出　　处：《兵工自动化》2025年第2期100-105,共6页Ordnance Industry Automation

基　　金：重庆市教育委员会科学技术研究项目(KJQN202300615);中国石油大学(北京)创新创业计划项目(D202405181654079601)。

摘　　要：针对智能巡检方法难以有效应对复杂环境而导致巡检效率低下、漏检率高的问题,提出智能机器人巡检油气管道异常状态激光点云定位预警方法。设计智能巡检机器人,包括机械摇臂、密封舱和框架结构模块。采用3维激光扫描仪收集管道数据,3维激光同时定位与地图构建(simultaneous localization and mapping,SLAM)技术中激光雷达里程计与建图系统(lightweight and ground-optimized lidar odometry and mapping,LeGO-LOAM)算法进行改进,实现机器人同步定位与建图,结合卷积神经网络评估管道状态并预警定级。实验结果表明,该方法能准确检测管道防腐层状况、裂缝和变形等异常,检测数量与实际一致,巡检率、预警率超99.8%,漏检率和虚警率低于0.3%,路径规划高效,整体巡检性能优异。In order to solve the problems of low efficiency and high missed detection rate caused by the difficulty of intelligent inspection method to effectively deal with complex environment,a laser point cloud positioning and early warning method for abnormal state of oil and gas pipeline inspection by intelligent robot was proposed.An intelligent inspection robot is designed,including mechanical rocker arm,sealed cabin and frame structure module.3D laser scanner was used to collect pipeline data,and 3D laser simultaneous localization and mapping simultaneous local ization and mapping(SLAM),the algorithm of laser radar odometry and mapping system lightweight and ground and optimized lidar odometry and mapping(LeGO-LOAM),in SLAM technology is improved to realize synchronous localization and mapping of robots.Convolutional neural network is combined to evaluate the pipeline status and early warning and grading.The experimental results show that the method can accurately detect the pipeline coating condition,cracks,deformation and other abnormalities,the number of detection is consistent with the actual,the inspection rate and early warning rate are more than 99.8%,the missing rate and false alarm rate are less than 0.3%,the path planning is efficient,and the overall inspection performance is excellent.

关 键 词：无缆自主管道巡检机器人 3维激光SLAM技术 油气管道 安全状态巡检 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]