Blar i NTNU Open på forfatter "Ellefsen, Andre"
-
A Comprehensive Survey of Prognostics and Health Management based on Deep Learning for Autonomous Ships
Ellefsen, Andre; Ushakov, Sergey; Æsøy, Vilmar; Zhang, Houxiang (Journal article; Peer reviewed, 2019)The maritime industry widely expects to have autonomous and semiautonomous ships (autoships) in the near future. In order to operate and maintain complex and integrated systems in a safe, efficient, and cost-beneficial ... -
A Step-wise Feature Selection Scheme for a Prognostics and Health Management System in Autonomous Ferry Crossing Operation
Cheng, Xu; Ellefsen, Andre; Li, Guoyuan; Holmeset, Finn Tore; Chen, Shengyong; Zhang, Houxiang (Chapter, 2019)Developing a reliable algorithm to detect faults automatically within critical components in autonomous ferries is essential for safe and cost-beneficial maritime operations. Autonomous ferries are equipped with hundreds ... -
An Unsupervised Reconstruction-Based Fault Detection Algorithm for Maritime Components
Ellefsen, Andre; Bjørlykhaug, Emil Dale; Æsøy, Vilmar; Zhang, Houxiang (Journal article; Peer reviewed, 2019)In recent years, the reliability and safety requirements of ship systems have increased drastically. This has prompted a paradigm shift toward the development of prognostics and health management (PHM) approaches for these ... -
Automatic Fault Detection for Marine Diesel Engine Degradation in Autonomous Ferry Crossing Operation
Ellefsen, Andre; Cheng, Xu; Holmeset, Finn Tore; Ushakov, Sergey; Æsøy, Vilmar; Zhang, Houxiang (IEEE International Conference on Mechatronics and Automation;, Chapter, 2019)The maritime industry generally anticipates having semi-autonomous ferries in commercial use on the west coast of Norway by the end of this decade. In order to schedule maintenance operations of critical components in a ... -
A Novel Densely Connected Convolutional Neural Network for Sea State Estimation Using Ship Motion Data
Cheng, Xu; Li, Guoyuan; Ellefsen, Andre; Chen, Shengyong; Hildre, Hans Petter; Zhang, Houxiang (Peer reviewed; Journal article, 2020)Sea state estimation is a fundamental problem in the development of autonomous ships. Traditional methods such as wave buoy, satellites, and wave radars are limited by locations, clouds and costs, respectively. Model-based ... -
Online Fault Detection in Autonomous Ferries: Using fault-type in-dependent spectral anomaly detection
Ellefsen, Andre; Han, Peihua; Cheng, Xu; Holmeset, Finn Tore; Æsøy, Vilmar; Zhang, Houxiang (Peer reviewed; Journal article, 2020)Enthusiasm for ship autonomy is flourishing in the maritime industry. In this context, data-driven Prognostics and Health Management (PHM) systems have emerged as the optimal way to improve operational reliability and ... -
Remaining useful life predictions for turbofan engine degradation using semi-supervised deep architecture
Ellefsen, Andre; Bjørlykhaug, Emil; Æsøy, Vilmar; Ushakov, Sergey; Zhang, Houxiang (Journal article; Peer reviewed, 2018)In recent years, research has proposed several deep learning (DL) approaches to providing reliable remaining useful life (RUL) predictions in Prognostics and Health Management (PHM) applications. Although supervised DL ... -
Validation of Data-Driven Labeling Approaches Using a Novel Deep Network Structure for Remaining Useful Life Predictions
Ellefsen, Andre; Ushakov, Sergey; Æsøy, Vilmar; Zhang, Houxiang (Journal article; Peer reviewed, 2019)Today, most research studies that aim to predict the remaining useful life (RUL) of industrial components based on deep learning techniques are using piecewise linear (PwL) run-to-failure targets to model the degradation ...