In recent years, the floating production industry has paid a lot of attention to the integrity of their mooring systems, and live monitoring of the station keeping performance and the condition of the anchor legs (with a primary focus on line-failure detection) has taken a prominent role. The requirement for having a mooring monitoring system is now reflected in most regulatory codes, standards, classification rules, and project specifications, but clear guidance on the functional requirements or proper implementation is missing.
This paper introduces a Mooring Monitoring System (MMS) approach that is designed to evaluate both the station keeping performance of the mooring system as well as the individual anchor legs, while ensuring the monitoring system is both robust, reliable and in-situ maintainable. Further, it does not only focus on complete anchor leg failure, but also on deterioration of individual anchor leg performance, such as polyester rope elongation, or uneven load sharing within clustered anchor legs. It relies on a thorough understanding of mooring system's station keeping characteristics, and on combining data from the DGPS with feedback data from the anchor leg profile under different conditions. Digital advancements can be applied (such as machine learning algorithms), but the principles can also be used deterministically based on design or as-installed data.