摘要
为了实现输变配设备的跨专业无人机(UAV)自动巡检,提出了一种考虑到输变配不同巡检频率的固定机巢巡检策略。基于集合覆盖模型建立了固定机巢选址模型;通过改进k-means聚类算法设计了巡检任务分配模型;将无人机路径规划问题建模为带时间窗的多旅行商问题(MTSPTW),设计了自适应大邻域搜索(ALNS)算法完成求解;并且使用某实际运维区域进行大规模数据的实例验证。结果表明:某机巢的无人机通过130次起降、703余千米的总飞行距离完成了一个月内共计1838次输变配混合巡检任务。提出的该方法打破了单个机巢单专业巡视思路,具有大规模巡检场景下的实用性和有效性。
To achieve automated inspection of power transmission towers,substations and distribution poles,a fixed unmanned aerial vehicle(UAV)nest was proposed based strategy that accounts for varying inspection frequencies.A fixed UAV nest deployment model was established based on a set cover problem,and the task assignment model for inspections was developed by enhancing the k-means clustering algorithm.The UAV path planning problem was formulated as a Multi-trip Traveling Salesman Problem with Time Windows(MTSPTW),and solved with an Adaptive Large Neighborhood Search(ALNS)algorithm.The real-world data validation was verified by utilizing a real operational and maintenance environment as an example.The results show that a single UAV nest completes 1838 mixed inspection tasks over one month,with 130 takeoffs and a total flight distance of over 703 km.The proposed method overcomes the limitations of single-type inspections,proving effective for large-scale scenarios.
作者
黄郑
王红星
杜彪
高嵩
高峰
HUANG Zheng;WANG Hongxing;DU Biao;GAO Song;GAO Feng(State Grid Jiangsu Electric Power Co.,Ltd.,Nanjing 210024,China;School of Transportation Science and Engineering,Beihang University,Beijing 102206,China)
出处
《汽车安全与节能学报》
CAS
CSCD
北大核心
2024年第5期670-679,共10页
Journal of Automotive Safety and Energy
基金
国网江苏省电力有限公司科技项目(J2023055)。
