Abstract
Monitoring the condition of mooring systems is essential for the safe operation and timely
maintenance of the wave energy converter. However, mooring dynamics are nonlinearity related to the wave forcing, and are complicated by its coupling with the wave energy converter. These nonlinear and coupling effects pose challenges in accurately identifying the condition of the mooring. In this study, we introduce a data-driven approach for condition monitoring that uses wavelet filtering and dynamic modeling to address these challenges. Initially, a wavelet filter is applied to separate the low-frequency surge motion, attributed to the nonlinear and coupling effects, from the surge at the wave frequencies. Then a linear ARX model is used to build the dynamic relationship between the filtered surge motion and wave surface elevation for monitoring purposes. The effectiveness of this method is demonstrated through its application to two different mooring system configurations within a multi-float wave energy converter. Comprehensive testing across eleven wave conditions confirms the effectiveness of the proposed method.
maintenance of the wave energy converter. However, mooring dynamics are nonlinearity related to the wave forcing, and are complicated by its coupling with the wave energy converter. These nonlinear and coupling effects pose challenges in accurately identifying the condition of the mooring. In this study, we introduce a data-driven approach for condition monitoring that uses wavelet filtering and dynamic modeling to address these challenges. Initially, a wavelet filter is applied to separate the low-frequency surge motion, attributed to the nonlinear and coupling effects, from the surge at the wave frequencies. Then a linear ARX model is used to build the dynamic relationship between the filtered surge motion and wave surface elevation for monitoring purposes. The effectiveness of this method is demonstrated through its application to two different mooring system configurations within a multi-float wave energy converter. Comprehensive testing across eleven wave conditions confirms the effectiveness of the proposed method.
| Original language | English |
|---|---|
| Title of host publication | 6th International Conference on Renewable Energies Offshore 19 - 21 November 2024, Lisbon, Portugal |
| Publication status | Accepted/In press - 1 Jun 2024 |
