摘要
为了保证管道安全,及时发现管道周围的非法作业和地质灾害,管道公司需要定期组织人员对管道进行巡检作业。山区地势陡峭,植被茂密,人工巡检效率极低,主观影响较大,难以及时发现管道周围的危险因素。针对这种情况,文章以定点飞行技术、图像识别技术和4G通信技术为基础,提出一种基于无人机的山区天然气管道智能巡检系统,将管道周围可能存在的危险因素作为特征样本库,然后把无人机航拍图片与样本库中的资料进行对比,从而发现管道周围的危险源,可以大幅降低一线员工的负担,提高管道安全管理水平。
In order to ensure pipeline safety and timely detect illegal operations and geological disasters around the pipeline,pipeline companies need to regularly organize personnel to inspect the pipeline.Mountainous areas with steep terrain,dense vegetation,low efficiency of manual inspection,subjective influence,it is difficult to find the risk factors around the pipeline.In view of this situation,based on the fixed-point flight technology,image recognition technology and 4G communication technology,this paper proposes an intelligent inspection system for natural gas pipelines in mountainous areas based on UAV.The possible risk factors around the pipeline are taken as the characteristic sample library,and then the UAV aerial photographs are compared with the data in the sample library,so as to find the risk factors around the pipeline,which can greatly reduce the burden of front-line staff and improve the safety management level of the pipeline.
作者
田明亮
TIAN Ming-liang(Zhejiang Zhenergy Natural Gas Operation Co.,Ltd.,Hangzhou 310000,China)
出处
《化工管理》
2023年第1期135-137,共3页
Chemical Engineering Management
关键词
管道
无人机
智能巡检系统
特征样本库
危险源
pipeline
UAV
intelligent inspection system
characteristic sample library
risk factors
作者简介
田明亮(1991-),男,汉族,河南商丘人,工学硕士,现任浙江浙能天然气运行有限公司科创中心无人机组研发组长,负责无人机巡检系统研发工作。
