1Researcher, Research Institute of Middle and Small Ship Building, South Korea
2Researcher, Research Institute of Middle and Small Ship Building, South Korea
3Researcher, Research Institute of Middle and Small Ship Building, South Korea
*Author correspondence: Forth Author, Head of Ocean & Ship ICT Convergence Centre, Korea Marine Electronics Industry Promotion Association, Email: yungyu@kmou.ac.kr
Online published on 25 August, 2021.
Recently smart and autonomous ship are appeared as hot issues internationaly because shipbuilding industry tries to look for way out of economic depression and environmental requirements of IMO with smart ship. Simultanously IMO tries to expel autonomous ship. A fault detection and diagnosis system is one of most important function in smart and autonomous ship. There are many methods to detect faults and diagnose in machine such as AI and big data treatment, but these methods have difficulties to train system, especially engines onboard are operated under very different situation and environment. This paper propose how to detect faults in running diesel engine without additional sonsor using CCs (Correation Coefficient) between the vital items. Over 10,000 operating data sets from engine room log book of 24 container ships, of which ages are spread out from new built ship to 21 years old ship, during 6 months are used in this paper. This paper develops fault detection and diagnosis sytem using statictical method based on collected data set.
Fault detection and diagnosis, Correlation Coefficient, Without additional sonsors, Smart and autonomous ship, Engine room machineries
