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Abstract Mooring systems in offshore applications primarily use chains to connect floaters to anchors. However, these systems are vulnerable to corrosion and fatigue, leading to failures. The offshore renewable energy industry will benefit from cost-effective condition monitoring instrumentation packages that help to lower overall operations and maintenance costs. While direct mooring load measurements are typically preferred, their frequent failures make them less reliable. This paper presents a robust and cost-effective Mooring Condition Monitoring System (MCMS) for offshore floaters, that can be widely deployed and can monitor the mooring line loads in near real-time. This system consists of primary reliable sensors that include redundant Differential Global Positioning System (DGPS) units, tri-axial accelerometers, and angular rate sensors. These sensor systems have the advantage of being low-cost, and do not interfere with the mooring system operation. The measurements from the MCMS are accessed and post-processed through an analytics platform, BMT DEEP, harnessing the benefits of Digital Twin Technology and bringing in data from all sources into a common time reference and enabling to synthesize and monitor the asset mooring system from any remote location through the mooring monitoring dashboard. The data from the floater marine monitoring system are quality controlled and fed to a mooring solver engine to generate a time history of each component tension loads from motions at termination points. This will be in turn used to obtain cyclic load severity for fatigue damage accumulation and remaining life evaluation. The solver engine implements a combination of quasi-static and dynamic mooring models along with the defined properties of component weights, elastic properties, and segment cross-sectional areas. The material properties are periodically updated to include loss of material due to prescribed corrosion rates and material component creep. Comparisons can be made between as measured and predicted fatigue damage rates from the mooring system design. The challenges faced in this process are highlighted, along with the steps taken to overcome those. The mooring monitoring dashboard will leverage background data analytics from remote monitoring, supporting proactive and predictive maintenance through automated alarms, and thus lowering operations and maintenance costs.
Das et al. (Sun,) studied this question.