Intelligent Information Processing in the Problem of Propulsion System Condition Monitoring

Author:

Bondarenko Oleksiy1,Fukuda Tetsugo1,Miyachi Ken2

Affiliation:

1. National Maritime Research Institute

2. Mitsui E&S Machinery

Publisher

The Japan Institute of Marine Engineering

Subject

Religious studies,Cultural Studies

Reference11 articles.

1. 1) Man, Y., Lundh, M. & MacKinnon, S.N. Managing unruly technologies in the engine control room: from problem patching to an architectural thinking and standardization. WMU J Marit. Affairs Vol.:17, pp.497–519 (2018).

2. 2) WinGD: WiDE WinGD Integrated Digital Expert. https://www.wingd.com/getattachment/Digital-solutions/WiDE/WiDE_Brochure_8pp_FINAL.pdf/?lang=en-GB

3. 3) Introduction of ship maintenance management system ClassNK CMAXS (in Japanese), https://classnkcs.co.jp/archive/pdf/seminar01.pdf

4. 4) Coraddu A, Oneto L, Ghio A, Savio S, Anguita D, Figari M. Machine learning approaches for improving condition-based maintenance of naval propulsion plants. In Proc.: the Institution of Mechanical Engineers, Part M: J. of Eng. for the Mar. Env. 2016; 230(1): 136-153.

5. 5) Gkerekos C., Lazakis I., and Theotokatos G. Ship Machinery Condition Monitoring Using Performance Data Through Supervised Learning. In Proc.: Smart Ship Technology Conference. Royal Institute of Naval Architects, London, (2017), pp.105-111

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