Route optimization of UAV in detecting marine fuel quality

  • ZHOU Yun-peng ,
  • FENG Xue-jun ,
  • XU Bo ,
  • SHEN Jin-xing
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  • (1a. College of Harbour, Costal and Offshore Engineering;1b.College of Civil and Transportation Engineering, Hohai University, Nanjing 210098, China; 2.Yangtze Institute for Conservation and Development, Nanjing 210098, China)

Received date: 2020-04-13

  Revised date: 2020-05-13

  Online published: 2020-05-13

Abstract

With the development of China’s ship emission control area (SECA) from coastal areas to inland rivers, the detection of sulfur content in marine fuel oil based on unmanned aerial vehicle(UAV) and sniffer method is becoming a research hotspot in the industry. Based on the theory of moving target traveling salesman (MTTSP) and in consideration of detection characteristics, a track prediction method was proposed to establish a route optimization model of UAV automatic inspection (D-SSP) . A genetic algorithm was designed to solve the model. Based on the historical data of AIS information service platform, the model was tested and analyzed in 12 different scenes. The results show that with the increase of the  ships number, the optimal path time of TSP model is 2.0~79.5 times that of D-SSP model, which proves the scientificity of D-SSP model. The results of example analysis can provide reference for the establishment of UAV automatic inspection system.

Cite this article

ZHOU Yun-peng , FENG Xue-jun , XU Bo , SHEN Jin-xing . Route optimization of UAV in detecting marine fuel quality[J]. Journal of Dalian Maritime University, 2020 , 46(3) : 95 -100 . DOI: 10.16411/j.cnki.issn1006-7736.2020.03.011

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