MEC-Driven UAV-Enabled Routine Inspection Scheme in Wind Farm Under Wind Influence
MEC-Driven UAV-Enabled Routine Inspection Scheme in Wind Farm Under Wind Influence
复制标题
DOI：
10.1109/access.2019.2958680
复制
发表时间：
2019
期刊：
影响因子：
3.9
通讯作者：
Peng Cao;Yi Liu;Chao Yang;Shengli Xie;Kan Xie
中科院分区：
文献类型：
--
作者：
Peng Cao;Yi Liu;Chao Yang;Shengli Xie;Kan Xie
风电作为一种很有前途的替代能源选择，在未来的能源互联网中将占能源发电的主要部分。随着风电的开发，多台风电机组被部署在偏远和恶劣的地区，恶劣的工作环境可能会导致巨大的风电机组运维成本。在风电场部署无人机进行WT检测和传感数据处理被认为是降低成本和提高检测效率的一项很有前途的技术。提出了一种由移动边缘计算(MEC)驱动的无人机常规检测方案，无人机不仅可以进行多架次的检测，还可以提供计算和卸载服务。为了提供无缝通信服务，无人机可以最优地将传感数据卸载到地面站或卫星。在保证数据处理精度的同时，对无人机航迹和计算操作进行了联合优化，使总完成时间最小。在该方案中，为了克服风对无人机航迹规划的影响，首先设计了一种低复杂度的小波变换常规航迹检测和无人机调度方法。然后，通过寻找最优卸货轨迹和计算卸货参数，提出了一种最小化计算过程能耗的迭代优化方法。最后，仿真结果表明，该方案能有效提高无人机例行检查系统的效率。
As a promising choice of alternative energy, wind power will account for a major part of energy generation in future Energy Internet. With the exploitation of wind power, multiple wind turbines (WTs) are deployed at remote and harsh areas, in which the adverse working environment may lead to enormous WT operating and maintenance costs. Deploying unmanned aerial vehicles (UAVs) for WT detection and sensory data processing in wind farms has been considered as a promising technology to reduce the costs and improve inspection efficiency. In this paper, a mobile edge computing (MEC) driven UAV routine inspection scheme is proposed, in which the UAV not only detects WTs in multiple sorties, but also provides computing and offloading services. To provide seamless communication service, UAV can offload the sensory data to the ground station or satellite optimally. In order to minimize the total completion time, we jointly optimize the UAV trajectory and computation operations, while guaranteeing the data processing accuracy. In the proposed scheme, in order to overcome the influence of wind on UAV trajectory planning, a low complexity WT routine inspection trajectory and UAV scheduling approach is designed firstly. Then, we present an iterative optimization solution to minimize the energy consumption of computation processing, via finding the optimal offloading trajectory and computation offloading parameters. Finally, simulation results show that the proposed scheme can effectively improve the efficiency of UAV routine inspection system performance.