The International Maritime Organization (IMO) provides criteria to assess the vulnerability of ships toward the phenomenon of parametric roll. Such long-term vulnerability assessments permit to qualify statistically the ships vulnerability regarding parametric roll. However, it does not permit to assess the risk of parametric roll in real time. Thus, researchers and private company have developed methods and software to evaluate this risk using the real-time ship motions provided by the onboard inertial unit. Those methods detect parametric roll events when it appears and warn the officer of the watch of the immediate danger. This paper presents an innovative real-time detection method and its validation. The detection method considers physical conditions required for parametric roll to appear. Especially, it considers the coupling between the roll and pitch motions. The method and its associated parametric roll alarm are entirely described. The results show that the method correctly identifies parametric roll in regular longitudinal waves and do not lead to false detection in regular beam waves. A statistical study in irregular waves based on simulated data presents very promising results with a parametric roll detection rate in head seas above 80% when heavy roll motions appear and a false detection rate in beam seas below 4%. Finally, a 2.5-day full-scale validation on a container ship provides promising results.


The container ships, with typical hull shape presenting flat stern and pronounced bow flare, are especially subject to parametric roll. Operationally, several accidents which have led to the loss of containers at sea may be imputed to this phenomenon (France et al. 2003; Carmel 2006; MAIB 2020; DMAIB 2022). Following the accidents of the C11-class container ship (France et al. 2003) and of the Maersk Carolina (Carmel 2006), both due to parametric roll, insurers asked the shipowners to take measures to avoid such failure to appear (Dølhie 2006). Two solutions are rapidly developed to answer this request. The first one is developed by SeaSense and named SeaSense Monitoring (Nielsen et al. 2006).

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