Open AccessApplication of Artificial Neural Network on Health Monitoring of Offshore Mooring System
Author(s) -
X. E. Yee,
Muhammad Azfar Mohamed,
O.A. Montasir
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1144/1/012035
Subject(s) - submarine pipeline , mooring , artificial neural network , marine engineering , engineering , computer science , artificial intelligence , geotechnical engineering
The amount of floating offshore structures had been grown rapidly over these few years due to deepwater exploration and production activities, and this increase in number is predicted to remain over the coming years. Due to the catastrophic consequences from offshore mooring system failure and the limitation on the traditional method for failure detection, there is a need for alternative methods for health monitoring of the offshore mooring system. Artificial Intelligence (AI) has acquired recognition in these few years for petroleum engineering approach, especially Artificial Neural Network (ANN) thanks to its potential to solve complex problems with less time-consuming and effort. A review of the application of ANNs on health monitoring of offshore mooring system had been presented in this paper. The ANNs system had demonstrated its capability as a health monitoring tool for offshore floating structures to detect any damaged or broken mooring system.