André Listou Ellefsen
Background and activities
- 08/2017 - 06/2020: Department of Ocean Operations and Civil Engineering, NTNU Aalesund, Norway. Major: Data-Driven Prognostics and Health Management Solution for Autonomous Ships, Ph.D. Main supervisor: Houxiang Zhang.
- 08/2016 - 06/2017: Department of International Business, NTNU Aalesund, Norway. Major: Business Management, One year programme.
- 08/2014 - 06/2016: Department of Mechanical and Industrial Engineering, NTNU Trondheim, Norway. Major: Subsea technology - operation and maintenance, M.Sc.
- 08/2011 - 06/2014: Department of ICT and Natural Sciences, NTNU Aalesund, Norway. Major: Science in Engineering - Automation, B.Sc.
- 2020 - present: Milestone project Norwegian Research Council
- 2020 - present: NTNU Discovery main project
- 2019 - 2019: Predictions of environmental quality in Geiranger.
- 2018 - 2020: KPN, "Digital Twins for Vessel Life Cycle Service (TwinShip)".
- 07/2020 - present: Department of Ocean Operations and Civil Engineering, NTNU Aalesund, Norway. Postdoc - IV Innovation scholarship
- 03/2017 - 08/2017: Vendanor AS, Stryn, Norway. Automation Engineer.
- Artificial intelligence
- Deep learning
- Digital twins
- Fault diagnostics
- Failure prognostics
- Predictive maintenance
- Prognostics and health management
Detailed information can be found from the Intelligent Systems Lab:
Scientific, academic and artistic work
A selection of recent journal publications, artistic productions, books, including book and report excerpts. See all publications in the database
- (2020) A Novel Densely Connected Convolutional Neural Network for Sea State Estimation Using Ship Motion Data. IEEE Transactions on Instrumentation and Measurement. vol. 69 (9).
- (2020) Online Fault Detection in Autonomous Ferries: Using fault-type in-dependent spectral anomaly detection. IEEE Transactions on Instrumentation and Measurement. vol. 69 (10).
- (2020) A Data-Driven Prognostics and Health Management System for Autonomous and Semi-Autonomous Ships. 2020.
- (2019) An Unsupervised Reconstruction-Based Fault Detection Algorithm for Maritime Components. IEEE Access. vol. 7.
- (2019) Remaining useful life predictions for turbofan engine degradation using semi-supervised deep architecture. Reliability Engineering & System Safety. vol. 183.
- (2019) Validation of Data-Driven Labeling Approaches Using a Novel Deep Network Structure for Remaining Useful Life Predictions. IEEE Access. vol. 7.
- (2019) A comprehensive survey of prognostics and health management based on deep learning for autonomous ships. IEEE Transactions on Reliability. vol. 68 (2).
- (2019) A Step-wise Feature Selection Scheme for a Prognostics and Health Management System in Autonomous Ferry Crossing Operation. Proceedings of 2019 IEEE International Conference on Mechatronics and Automation August 4 - 7, Tianjin, China.
- (2019) Automatic Fault Detection for Marine Diesel Engine Degradation in Autonomous Ferry Crossing Operation. Proceedings of 2019 IEEE International Conference on Mechatronics and Automation August 4 - 7, Tianjin, China.