摘要：To ensure the safe operation of static and dynamic devices in a limited platform space and prevent security threats caused by accidents and external intruders, the unmanned aerial vehicle (UAV) is becoming an important tool to monitor and reduce the operational risk of unattended offshore oil platforms. However, UAVs may encounter location errors, adversely affecting patrol efficiency and accuracy. Therefore, the optimal UAV path planning is vital to ensure complete monitoring routes and reduce the risk presented by the marine environment, devices, and employees on unattended offshore platforms. This paper established a multi-objective mathematical model with the shortest flight path and minimum correction times for the intelligent UAV patrol of unattended offshore platforms. An intelligent algorithm with large-scale constraints for UAV path planning was proposed based on non-dominated sorting genetic algorithms. A flight path length of 8076.11 m and 25 correction times presented the optimal solution. The results indicated that the proposed algorithm could be used to plan an effective and accurate three-dimensional (3D) UAV flight path according to the size of the offshore oil platform. This is highly significant for the intelligent risk monitoring of unattended offshore platforms in practical engineering in the future.(c) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.

关键字：Unattended offshore platform; Flight path planning; NSGA-II; Error correction; Genetic operator

ISSN号：0957-5820

卷、期、页：卷: 160页: 13-24

发表日期：2022-04-01

影响因子：6.158000

期刊分区（SCI为中科院分区）：二区

收录情况：SCI（科学引文索引印刷版）,EI（工程索引）,SCIE（科学引文索引网络版）

发表期刊名称：PROCESS SAFETY AND ENVIRONMENTAL PROTECTION

参与作者：李昱奇,尹丰,王文涛

通讯作者：孙海波,李健昌,张珂

第一作者：王莹莹

论文类型：期刊论文

论文概要：王莹莹,李昱奇,尹丰,王文涛,孙海波,李健昌,张珂，An intelligent UAV path planning optimization method for monitoring the risk of unattended offshore oil platforms，PROCESS SAFETY AND ENVIRONMENTAL PROTECTION，2022，卷: 160页: 13-24

论文题目：An intelligent UAV path planning optimization method for monitoring the risk of unattended offshore oil platforms