An important scientific announcement has been published from academic faculty members of Cyprus University of Technology.  Dr Kyriakos Deliparaschos and Dr Konstantinos Michail, from Department of Electrical Engineering, Computer Engineering and Informatics, developed a new approach of industrial fault detection based on Artificial Intelligence. Professor Spyridon Tzafestas from National Technical University Athens, and Dr Argyrios Zolotas from the School of Engineering, University of Lincoln, UK also collaborated in the research work.

Researchers analyzed control system reliability using Maglev trains - a transport method that employs magnetic levitation to move vehicles without touching the ground, reducing friction and allowing higher speeds. The fastest commercial Maglev train named ‘Shanghai Maglev Train’ operates in China and can reach speeds of up to 430km/h (although higher speeds have been recorded on other non-commercial trains and tests).

The results show that fault detection in industrial systems based on Artificial Intelligence methods could be less complex and of significantly lower computational cost than current technologies. It has strong potential to replace multiple estimators used in fault detection and isolation schemes in various industrial applications.

The research has been published in the academic journal IEEE Transactions on Control Systems Technology, one of the elite  journals in the field of Control Systems Engineering research.