The real-time monitoring of underwater risers, cables, and mooring lines by multiple sensors is in great demand but still very challenging. In this study, a new real-time riser monitoring method based on an Extended Kalman Filter (EKF) is proposed. It estimates the overall shape of riser in real-time utilizing the measured signals from multiple bi-axial (inclination and heading) inclinometers along the riser. The novel EKF algorithm is shown to be robust against sensor noises and successfully reproduces the actual riser profiles at each time step, which has been verified by multiple tests through numerical simulations. For verification, a turret-moored FPSO (Floating Production Storage and Offloading) with a SCR (Steel Catenary Riser) is employed in four different random waves and currents. Subsequent algorithms are also developed so that the corresponding bending and axial stresses along the riser can also be estimated in real time from the obtained riser shape, which can further be used for the real-time estimation of fatigue-damage accumulation.

迫切需要通过多个传感器对水下立管，电缆和系泊缆进行实时监控，但仍然非常困难。在这项研究中，提出了一种新的基于扩展卡尔曼滤波器（EKF）的实时立管监控方法。它利用沿立管的多个双轴（倾斜和航向）测斜仪的测量信号实时估算立管的整体形状。新颖的EKF算法显示出对传感器噪声的鲁棒性，并成功地再现了每个时间步长的实际立管轮廓，已通过数值模拟的多次测试对此进行了验证。为了进行验证，在四个不同的随机波和海流中使用了带有SCR（钢悬链提升管）的塔楼系泊FPSO（浮动产品存储和卸载）。