Apparatus and method for a real-time-monitoring of a riser and mooring of floating platforms
AssigneeThe Texas A&M University System
InventorsMoo-Hyun Kim, Hansung Kim, Chungkuk Jin
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Abstract
An apparatus, method and system for real-time monitoring of underwater risers, cables, and mooring lines based on a Kalman filter. In an embodiment, the system is formed with sensors configured to sense an inclination of a riser segment between riser nodes of the riser between the upper end and the lower end. A data processing system is configured to employ a Kalman filter algorithm to produce real-time estimates of a deformed shape and a stress of the riser segment using the sensed inclination between the riser nodes.
Claims20
A system operable with a riser having an upper end coupled to a platform and a lower end coupled to a seabed, wherein said riser comprises a plurality of riser segments collectively interconnected by a plurality of nodes each joining a corresponding pair of said riser segment, said system comprising:
- sensors including bi-axial inclinometers each positioned in a middle of a corresponding one of a subset of said riser segments and configured to sense and output a signal indicative of vertical inclination and azimuthal heading measurements at said middle of said corresponding riser segment in real-time;
- and
- a data processing system configured to employ a nonlinear “extended” Kalman filter (“EKF”) algorithm to produce real-time estimates of a deformed shape and a stress of said riser, and of each individual riser segment, using known locations of said upper and lower ends and said vertical inclination and azimuthal heading measurements by reproducing a profile of each riser segment at each of a plurality of time steps, wherein:
- said EKF algorithm reduces a sensor error and a prediction error of the real-time estimates of said deformed shape and said stress of each riser segment via a recursive calculation process;
- said EKF algorithm produces said real-time estimates of each riser segment, in a portion outside of a location of said corresponding bi-axial inclinometer, via a machine-learning algorithm executing on said data processing system;
- said data processing system is further configured to estimate bending, tension, and axial stresses of said riser segments based on said estimated deformed shape of said riser and said riser segments;
- and
- said data processing system is further configured to detect malfunctions, damages, and accumulated fatigue of said riser segments using said real-time estimates of said deformed shape and said stresses of said riser segments.
A method operable with a riser having an upper end coupled to a platform and a lower end coupled to a seabed, wherein said riser comprises a plurality of riser segments collectively interconnected by a plurality of nodes each joining a corresponding pair of said riser segment, said method comprising:
- sensing vertical inclination and azimuthal heading measurements at a middle of each of a subset of said riser segments in real-time with sensors including bi-axial inclinometers each positioned in the middle of the corresponding one of said subset of riser segments;
- and
- operating a data processing system to:
- employ a nonlinear “extended” Kalman filter (“EKF”) algorithm to produce real-time estimates of a deformed shape and a stress of said riser, and of each individual riser segment, segments using known locations of said upper and lower ends and said vertical inclination and azimuthal heading measurements by reproducing a profile of each riser segment at each of a plurality of time steps, wherein:
- said EKF algorithm reduces a sensor error and a prediction error of the real-time estimates of said deformed shape and said stress of each riser segment via a recursive calculation process;
- said EKF algorithm produces said real-time estimates of each riser segment, in a portion outside of a location of said corresponding bi-axial inclinometer, via a machine-learning algorithm executing on said data processing system;
- and
- said data processing system is further configured to estimate bending, tension, and axial stresses of said riser segments based on said estimated deformed shape of said riser and said riser segments;
- and
- detect malfunctions, damages, and accumulated fatigue of said riser segments using said real-time estimates of said deformed shape and said stresses of said riser segments.
Dependencies are inferred from the claim text.