Towards a model-based condition assessment of complex marine machinery systems using systems engineering



Published Jul 5, 2016
Alexandros S. Zymaris Øystein Åsheim Alnes Knut Erik Knutsen Nikolaos M.P. Kakalis


In the present paper, a systems engineering methodology is presented for the analysis and condition assessment of complex marine machinery systems. Two important characteristics of these systems are (i) that they comprise of a multitude of subcomponents which influence the overall system condition/performance and (ii) the continuously varying operating and environmental conditions. The methodology presented herein is capable to evaluate the system level effects of component degradation and faulty states under realistic system operation. By virtue of this, it is employed along with sensor signal data for the identification of degraded states and the allocation of the problem to specific system components. The modelling platform used in this work is the DNVGL COSSMOS (Complex Ship System Modelling & Simulation).
At the methodological level, an automated model-based sensitivity analysis is conducted with respect to a set of component degradation/failure modes. The latter is used along with a clustering algorithm for the precise allocation of the failure to specific components and system particulars. The selected case-study is the Diesel-electric marine propulsion system of a 2300 tonnes DWT (deadweight tonnage) anchor handling vessel embedded with its cooling network. Based on the results, the approach is capable to successfully identify faults at various subcomponents of the cooling network system including pumps, regulating valves, heat exchangers and piping. Due to the fact that the system is treated in an integrated manner, a fault can be identified in a component using sensor signals placed in other system locations.

How to Cite

Zymaris, A. S., Alnes, Øystein Åsheim, Knutsen, K. E., & Kakalis, N. M. (2016). Towards a model-based condition assessment of complex marine machinery systems using systems engineering. PHM Society European Conference, 3(1).
Abstract 522 | PDF Downloads 178



condition monitoring, systems engineering, sensitivity analysis, Model-based diagnosis, Marine Propuslion and cooling systems, SOMs

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