An Investigation into the Operational Characteristics of High-Speed Crew Boat Based on Artificial Neural Network

S. Riyadi*, I. K.A.P. Utama, W. D. Aryawan, R. Rulaningtyas, G. A. Thomas

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

Estimating shaft power of a crew boat is very important to be analysed because it has high-speed operational characteristics along with limited routes. To understand the phenomena, 3 sister crew-boats with operational distance about 40-60 nautical miles every day are investigated. The daily operational time is 8 hours and the configurations are: 4.04% full speed, 13.63% economical speed, 1.81% slow speed, 7.65% snatching, 1.25% manoeuvring, 5.29% idle, and the remaining time is in standby condition. The crew boats are fitted with a monitoring system namely SHIMOS®, in which data is sent to a server in the centre office every 2 minutes. The data consists of time capture, boat position (latitude and longitude), speed, left and right RPM engine, left and right flow-meter data engine, and average of fuel consumption data in everyday operation. Three years of data has been collected for the vessel. The present study proposed characteristics of crew-boat shaft power, which affected by external factors using Artificial Neural Network (ANN) back propagation method and optimisation in 4 hidden layers and 40 neurons with relative error 6.2%. The results demonstrates good agreement with previous popular method that using statistical models.

Original languageEnglish
Article number012054
JournalIOP Conference Series: Earth and Environmental Science
Volume557
Issue number1
DOIs
Publication statusPublished - 14 Sept 2020
Event2nd Maritime Safety International Conference, MASTIC 2020 - Surabaya, Indonesia
Duration: 18 Jul 2020 → …

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