内河船舶尾气监测的多无人机路径规划研究  

Research and Planning on Multiple UAV Paths for Monitoring Exhaust Emissions of Inland Waterway Vessels

作　　者：王广生 孙祎峥 孙海军 鱼童 张铖[2] 周云鹏 Wang Guangsheng;Sun Yizheng;Sun Haijun;Yu Tong;Zhang Cheng;ZhouYunpeng(China Harbour Engineering Co.,Ltd.,Beijing 100027,China;College of Harbour Coastal and Offshore Engineering,Hohai University,Nanjing Jiangsu 210098,China)

机构地区：[1]中国港湾工程有限责任公司,北京100027 [2]河海大学港口海岸与近海工程学院,江苏南京210098

出　　处：《港口航道与近海工程》2024年第1期93-98,共6页Port,Waterway and Offshore Engineering

基　　金：国家重点研发计划(2021YFB2600203)。

摘　　要：由于高、低硫油价格的较大差距,低硫油高昂的使用成本使得内河船舶高硫燃油使用的违规率依然较高,给有关部门的监管与防治工作带来了不小的挑战。为降低内河船舶活动产生的大气污染物排放对航道沿线地区的空气质量的影响,如何通过非接触式取样检测船舶燃油质量成为重要问题。针对内河船舶尾气排放监测的多无人机协同路径规划问题,构建了多无人机巡检路径规划模型,并提出基于K-means++和混合模拟退火遗传算法构成的两阶段算法进行求解。结果表明,该两阶段算法能够在不同条件下合理均衡地分配巡检任务,为内河船舶尾气排放监测的无人机巡检系统的建立提供理论支撑。Due to big difference in price between high and low sulfur fuel,the use of high sulfur fuel for inland waterway vessels still got out of line,which brought great challenges to the supervision and prevention by relevant departments.In order to reduce the effect of exhaust emissions generated by inland waterway vessels on air quality,it was necessary to apply non-contact sampling in fuel quality detection.Thus a multiple UAV path planning(MUPP)model was built for monitoring the exhaust emissions of inland waterway vessels,and a two-phase algorithm(TPA)based on K-means++plus SAGA was proposed for solution.The results show that TPA method supports reasonable and even allocation of monitoring assignments under different conditions,which lays theoretical basis for the establishment of UAV monitoring system.

关 键 词：无人机路径规划 内河船舶尾气排放监测 移动目标旅行商 K-means++ 

分 类 号：U698.7[交通运输工程—港口、海岸及近海工程]