Prediction of Flooded Compartment Damage Locations in Ships by Using Spectrum Analysis of Ship Motions in Waves

Abstract

Considering the nature of marine accidents, even a single accident can result in significant damage to the environment and property, as well as loss of life. Therefore, the initial response should be rapid and accurate, and various decision support systems have been developed to achieve this. Research on simulating progressive flooding on board immediately after an accident is being actively conducted, but this requires high levels of computing power. In this study, a methodology for converting simulated ship motion data into a ship motion database is presented. The model of a training ship from the Korea Institute of Maritime and Fisheries Technology and KRISO in-house code SMTP was used for ship motion computations. The short-time Fourier transform was used to convert time-series motion data into a spectrogram motion database. A methodology for deriving a predicted location of the damage center is presented. The candidate locations of the damage centers were obtained by comparing the root mean square error values of the ship motion database from the simulation and real-time ship motion data. Finally, a probability function was suggested to confirm the predicted location of the damage center. Using 100 randomly selected test cases, our method showed 95% accuracy.

A Review of Methods for Modelling Flooding, Its Progression and Outcome in Damaged Ships

“…Other studies have introduced hybrid or multi-level real-time flooding risk evaluation [124]. Furthermore, recent studies have shown the potential for the application of data-driven techniques to the problem based on pre-calculated progressive flooding simulations [125][126][127][128][129].…”

Ship Motion-Based Prediction of Damage Locations Using Bidirectional Long Short-Term Memory

“…It can be used for decision-making in case of progressive flooding simulation or accident response by predicting the location of damage with high accuracy without using flood sensors or direct searching by a crew member. In the prior study (Son et al, 2021), an algorithm for predicting the location of damage was developed using the short time Fourier transform (STFT) to obtain the case most similar to the real-time ship motion data among the damaged ship simulation data in various scenarios. Time-series data was transformed to a spectrogram matrix using STFT, and the real-time motion data converted under the same conditions were compared with all simulated scenarios to predict the damage location.…”