Wave Tank Experiment for Sea State Monitoring with Distributed Acoustic Sensing

Monitoring sea states across the offshore wind farm areas is essential to keep their structures safe, efficiently operate the systems, and assess the environmental effects of wind turbines. Conventional sea state sensors like buoys limit their observable coverage; therefore, installing many sensors across the wide area is necessary to obtain sufficient sea state information. However, such a situation is not practical in terms of cost. Instead, the study proposes utilising optical fibres, which is embedded in existing power cables for telecommunications on the seabed, as sea state monitoring sensors with distributed acoustic sensing (DAS). DAS is a vibration-sensing technology along optical fibres based on the Rayleigh backscattering of the injected laser. It measures the dynamic strain of the optical fibre in real time at each spatial bin, which is called a "channel" along the fibre. In power cables on the seabed, time-varying water pressure due to waves is expected to exert dynamic strain. This hypothesis motivates us to validate whether the application of DAS for power cables can estimate sea state, such as wave period, height, and the direction of arrival. Hence, the authors carried out a wave tank experiment with a programmable wave generator. An actual power cable is installed under the same condition as the bottom-mounted offshore wind turbines. The experimental results show that (i) the wave period can be accurately estimated from the frequency-domain analysis. (ii) The strong linearity between DAS vibration power and the wave height is found. (iii) The direction of arrival of waves can be estimated with the error of 1.5$^\circ$ when there are at least two laying angles of the cable in parallel with the estimation of wavelength. These outcomes promote the feasibility of utilising the existing power cables across offshore wind farms as sea state monitoring sensors.

Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing

This study proposes an anomaly-detection framework for monitoring exposure-length variations in submarine free-span cables using Distributed Acoustic Sensing (DAS), which is one of the distributed fiber-optic sensing technologies. To address environmental variability and limited training data in offshore environments, a regression-based feature extraction method was introduced to derive low-dimensional latent representations that retain exposure length-dependent vibration characteristics while suppressing environmental influences. The extracted features were used for one-class Support Vector Machine (SVM)-based anomaly detection. The proposed framework was evaluated through wave-tank experiments with exposure lengths ranging from 2 to 10 m. Experimental results showed that anomaly scores decreased approximately monotonically with increasing exposure-length change, exhibiting a strong correlation ($r = -0.83$). The binary classification achieved an F1 score of 0.82 despite training with only small-sample datasets. These findings demonstrate that exposure-length variations can be reliably detected under severe data limitations, supporting the potential of DAS-based cable condition monitoring.