Arild Bergesen Husebø
- Office:
- D3063 ( Jon Lilletuns vei 9, Grimstad )
Arild received his bachelor’s and master’s degree in Renewable Energy engineering from the University of Agder in 2017 and 2019, respectively. During his M.Sc. he started exploring the use of machine learning for autonomous condition based monitoring of electromechanical machinery which would become the initial stepping stones for his PhD research.
Research interests
My current research at UiA is the continuation of what I started during my M.Sc. However, I realised quite early in my PhD that current state-of-the-art machine learning can not be the solution to everything encompassing condition based monitoring of machinery. Rather, machine learning could be a useful tool that excels in specialised problems that are close to impossible to solve analytically. From here, my focus mainly shifted towards rolling element bearings in which the university already had researched over the years.
Therefore I have access to state-of-the-art equipment which allows me to conduct various experiments to test my algorithms. Now, I am combining machine learning with analytical approaches to condition monitoring problems in order to harness the best of both worlds.
My research interests are:
• Statistical Signal Processing
• Applied Mathematics
• Machine Learning
• Mechanical Modelling
• Condition Based Monitoring
Scientific publications
- Husebø, Arild Bergesen; Huynh, Khang; Robbersmyr, Kjell Gunnar; Klausen, Andreas (2022). Classification of Mechanical Fault-Excited Events Based on Frequency. Intelligent Technologies and Applications: 4th International Conference, INTAP 2021, Grimstad, Norway, October 11–13, 2021, Revised Selected Papers. ISBN: 978-3-031-10524-1. Springer. chapter. s 380 - 392.
- Husebø, Arild Bergesen; Klausen, Andreas; Huynh, Khang; Robbersmyr, Kjell Gunnar (2021). A Simple Time Domain-Based Method for Estimating the Resonance Frequency of a Bearing. 2021 24th International Conference on Electrical Machines and Systems (ICEMS). ISBN: 978-8-9865-1021-8. IEEE conference proceedings. chapter.
- Husebø, Arild Bergesen; Kandukuri, Surya Teja; Klausen, Andreas; Huynh, Khang; Robbersmyr, Kjell Gunnar (2020). Rapid Diagnosis of Induction Motor Electrical Faults using Convolutional Autoencoder Feature Extraction. Proceedings of the European Conference of the Prognostics and Health Management Society (PHME). ISSN: 2325-016X. 5 (1).
- Husebø, Arild Bergesen; Huynh, Khang; Pawlus, Witold (2019). Diagnosis of Incipient Bearing Faults using Convolutional Neural Networks. 2019 IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD). ISBN: 978-1-5386-8107-7. IEEE conference proceedings. chapter. s 143 - 149.
- Husebø, Arild Bergesen; Huynh, Khang; Robbersmyr, Kjell Gunnar; Klausen, Andreas (2021). Classification of Mechanical Fault-Excited Events based on Frequency.
Last changed: 16.12.2022 13:12