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.
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
Last changed: 16.12.2022 13:12