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Structural health monitoring for TLP-FOWT (floating offshore wind turbine) tendon using sensors
Abstracts In this paper, a new algorithm for the real-time structural health monitoring of TLP (tension-leg platform) tendons is presented. The algorithm is based on bi-axial sensors installed along the tendon and top tension-meter. Then, the tension and bending moment along the line can be estimated by using the developed algorithm. For bending moment, a generalized-coordinate-based FEA (Finite Element Analysis) formulas with cubic interpolation are derived. For tension, analytical formulas with small angle assumption are derived. Hull-mooring-riser fully coupled software is used as a simulation tool to generate the corresponding numerical-sensor signals. To validate the developed algorithms, several case studies are conducted, considering variations in sensor spacing, line-failure detection, different boundary conditions, and ocean-storm conditions. The results show that the proposed algorithms can monitor the actual variations of tensions and bending moments (or axial and bending stresses) along the tendon with high accuracy, which means that the real-time monitoring of accumulated fatigue damage at hot-spots is also possible. The developed algorithm can also detect various line-failure scenarios by observing the change of stress signals. Its capability of real-time stress tracing in 10-yr and 100-yr storm conditions is also demonstrated.
Structural health monitoring for TLP-FOWT (floating offshore wind turbine) tendon using sensors
Abstracts In this paper, a new algorithm for the real-time structural health monitoring of TLP (tension-leg platform) tendons is presented. The algorithm is based on bi-axial sensors installed along the tendon and top tension-meter. Then, the tension and bending moment along the line can be estimated by using the developed algorithm. For bending moment, a generalized-coordinate-based FEA (Finite Element Analysis) formulas with cubic interpolation are derived. For tension, analytical formulas with small angle assumption are derived. Hull-mooring-riser fully coupled software is used as a simulation tool to generate the corresponding numerical-sensor signals. To validate the developed algorithms, several case studies are conducted, considering variations in sensor spacing, line-failure detection, different boundary conditions, and ocean-storm conditions. The results show that the proposed algorithms can monitor the actual variations of tensions and bending moments (or axial and bending stresses) along the tendon with high accuracy, which means that the real-time monitoring of accumulated fatigue damage at hot-spots is also possible. The developed algorithm can also detect various line-failure scenarios by observing the change of stress signals. Its capability of real-time stress tracing in 10-yr and 100-yr storm conditions is also demonstrated.
Structural health monitoring for TLP-FOWT (floating offshore wind turbine) tendon using sensors
Chung, Woo Chul (author) / Pestana, G. Rafael (author) / Kim, MooHyun (author)
Applied Ocean Research ; 113
2021-05-30
Article (Journal)
Electronic Resource
English
Real-time monitoring , Structure health monitoring , Stress-monitoring algorithm , Bi-axial inclinometers , Top-tension-meter , Tendon , TLP , FOWT , FEA , Bending moment , Tension , Line-failure detection , Fully-coupled simulation , Tension Leg Platform , Floating Offshore Wind Turbine , Finite Element Analysis , NDT , Non Destructive Test , VIV , Vortex Induced Vibration , VCG , Vertical Center of Gravity , ANN , Artificial Neural Network , MWL , Mean Water Level , B.C. , Boundary Conditions , JONSWAP , Joint North Sea Wave Project , GOM , Gulf of Mexico
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