With the development trend of intelligent ship and shipping as well as accumulation of ship big data, it is urgent to build a special model of navigation economic analysis through data-driven means to solve the problem of energy consumption evaluation and optimization and maximize ship energy efficiency. In this paper, combined with the relationship between ship's sailing conditions and main engine's fuel consumption characteristics, and considering the factors of draft and relative wind speed, K-means clustering analysis method is used to realize the division of different sailing conditions of the influencing factors of fuel consumption. The historical data of a VLCC are used to verify the actual application. Based on the data of ship's voyage loading and external environment weather conditions, the classification analysis of navigation conditions and the determination of influencing factor parameter interval under each working condition are realized, which provides a more refined analysis basis for the construction of matching model of marine main engine fuel consumption by different working conditions.
TAN Xiao
,
GUAGN Wenyuan
,
LI Han
,
LI Yongjie
,
XUE Chen
. Classification method of ship navigation condition based on clustering analysis[J]. Science & Technology Review, 2020
, 38(21)
: 91
-95
.
DOI: 10.3981/j.issn.1000-7857.2020.21.011
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