Saving Energy and High-Efficient Inspection to Offshore Wind Farm by the Comprehensive-Assisted Drone

Abstract

Facing the method’s limitations of the existing drone inspection on offshore wind farms, we adopt a new comprehensive-assisted drone automated inspection scheme under the comprehensive assistance. Our objectives are saving energy and high-efficient inspection. The such inspection is used to formulating the two mixed-integer nonlinear programming problems based on two new drone basic models: the mobile edge computing driven drone computation system model and the drone flight model. To solve the problems, we split them into four subproblems, and a new improved heuristic algorithm is created to address. In turns, the waypoints, total inspection time, inspection energy consumption, and traveling distance of unmanned aircraft vehicle (UAV) and the traveling distance of boat are obtained by $K$-means algorithm and the smallest enclosing circle (SEC) algorithm, the Lin-Kernighan Heuristic 3 (LKH-3) algorithm, and the LKH. Finally, conducting the comprehensive optimization and simulation, the simulation numeric results are gotten. The simulation results demonstrate that as for the two aspects of the total energy consumption and inspection efficiency under different data amount and average wind speed, the scheme improves at most 44% and 23.5% than the current other three; the scheme achieves the objective of saving energy and high-efficient inspection.