Using Neural Network Approaches to Detect Mooring Line Failure

The mooring systems give stability to the floating platforms against environmental conditions, stabilizing platform with lines attached seabed. are among main components that guarantee safety of staff and various operations carried out on platforms. current approaches used monitor inefficient as line tension sensors expensive install, maintain, have durability problems. This article presents development two neural network-based machine learning systems: a Multilayer Perceptron (MLP) Long Short-Term Memory (LSTM). They able detect failure in near real-time based comparison between measured predicted motion. implemented were trained evaluated simulated motion data generated using real conditions Campos Basin, Rio de Janeiro, Brazil. results showed MLP LSTM models lines, increasing difference motions when there is breakage. A revealed model performed better at predicting platform.