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电力巡检无人机固定机巢多阶段选址研究

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为满足日益增长的无人机电力巡检需求,克服现有无人机巡检方式效率与自动化水平仍偏低的问题,研究基于固定机巢的巡检模式,并提出多阶段的无人机固定机巢选址方法.使用CIPS(圆交叉点集法)确定设施候选点.考虑到机巢的阶段性开放特征,建立多目标多阶段机巢选址模型.设计NSGA-Ⅲ算法,基于徐州市的实际案例,验证模型和算法.实验结果表明,NSGA-Ⅲ算法有着稳定的求解质量优势.最终选址方案的需求覆盖率高达94.7%,需求重复覆盖率仅为14.5%.因此,该无人机巢选址方法能够在节约建设成本的同时,实现无人机巡检需求的较优覆盖,并避免了需求重复覆盖,对于电力巡检部门在机巢选址方面具有一定实用价值.
Multistage Drone Dock Location Problem for Electric Power Inspection
In response to the growing demand of drone power inspections and overcome the defects of ex-isting inspection methods,this paper proposes and studies a multi-stage drone dock site selection meth-od.First,the CIPS method is used to identify candidate sites.Secondly,a multi-objective and multi-stage drone dock location model was established considering the stage-opening characteristics of the nest.Fi-nally,the NSGA-Ⅲ algorithm is applied to solve this model using the real world case of Xuzhou City.Re-sults show that the demand coverage rate of the final site selection plan is as high as 94.7%,and the de-mand duplication coverage rate is only 14.5%.Therefore,the location problem proposed in this article can achieve optimal coverage of inspection,while saving construction costs,which is of some practical val-ue for the electric power inspection department in the nest location.

drone inspectiondrone dock locationmulti-stage locationmulti-objective optimizationNS-GA-Ⅲ algorithm

黄祥、吴涛、吴媚

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江苏方天电力技术有限公司,江苏南京 211000

无人机巡检 机巢布点 多阶段选址 多目标优化 NSGA-Ⅲ算法

2024

航空计算技术
中国航空工业西安航空计算技术研究所

航空计算技术

CSTPCD
影响因子:0.316
ISSN:1671-654X
年,卷(期):2024.54(6)