A fuzzy Bayesian network risk assessment model for analyzing the causes of slow-down processes in two-stroke ship main engines.
An object of class bn.fit. Refer to the documentation of bnlearn for details.
A discrete Bayesian network to assess the factors contributing to the engine's slow-down processes. The probabilities were given in the referenced paper. The vertices are:
Oil mist high density (yes, no);
Scavenge air box fire (yes, no);
Piston cooling oil non flow (yes, no);
Cylinder lube oil non flow (yes, no);
Cylinder cooling fresh water low pressure (yes, no);
Cylinder cooling fresh water high temperature (yes, no);
Main lube oil low pressure (yes, no);
Thrust pad high temperature (yes, no);
Piston cooling oil high temperature (yes, no);
Exhaust gas high temperature (yes, no);
Stern tube bearing high temperature (yes, no);
(yes, no);
Bashan, V., Yucesan, M., Gul, M., & Demirel, H. (2024). A fuzzy Bayesian network risk assessment model for analyzing the causes of slow-down processes in two-stroke ship main engines. Ships and Offshore Structures, 19(5), 670-686.