Artificial intelligent techniques for failure detection in ships

• Main Author: Koh, Yee Sin
• Other Authors: Wang Youyi
• Format: Final Year Project
• Language: English
• Published: 2017
• Subjects: DRNTU::Engineering::Electrical and electronic engineering
• Online Access: http://hdl.handle.net/10356/70896
• Institution: Nanyang Technological University

Tunnel thruster subsystem provides the ship with the capability to maneuver a turn-around in tight spaces and to move sideways towards the port for docking. For the tunnel thruster to be able to perform the mentioned operations, it requires the components that are inter-connected in the circuit to be in normal working condition. With the occurrence of fault at the motor that supplies power to the propeller of the tunnel thruster, the motor protection within the component will be activated thus cutting off the power supply. Components that are connected to the motor will also experience the effects of the failure. All the 6 Artificial Intelligent (AI) techniques have their own strengths and weakness and as such, a combination of both techniques for diagnosing of fault are common. For the machine to be able to learn and find a pattern through the AI technique, it is important to perform the extraction of features on the raw data generated from MATLAB.