Application of Real-Time Estimation Techniques for Stability Monitoring of Fishing Vessels

This work presents a comparative study of two signal processing methods for the estimation of the roll natural frequency towards the real-time transverse stability monitoring of fishing vessels. The first method is based on sequential application of the Fast Fourier Transform (FFT); the second method combines the Empirical Mode Decomposition (EMD) and the Hilbert-Huang Transform (HHT). The performance of the two methods is analysed using roll motion data of a stern trawler. Simulated time series from a one degree-of-freedom nonlinear model, and experimental time series obtained from towing tank tests are utilized for the evaluation. In both cases, beam waves are considered but, while irregular waves are adopted in the simulated data, the towing tank tests are made in regular waves. Based on the available data the performance of both estimation methods is comparable, but the EMD-HHT method turns out slightly better than the sequential FFT. Finally, the use of a statistical change detector, together with the EMD-HHT methodology, is proposed as a possible approach for the practical implementation of an onboard stability monitoring system.