Spilios D Fassois

University of Patras, Dept of Mechanical Engineering and Aeronautics, Faculty Member

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S.D. Fassois is Professor & Director of the Stochastic Mechanical Systems and Automation (SMSA) Laboratory at the University of Patras, Greece. His research interests are in the area of stochastic mechanical & aeronautical systems and structures, with emphasis on non-stationary random vibration modeling, stochastic structural identification, identification and time series methods, fault diagnosis, and Structural Health Monitoring. He has authored more than 250 technical papers in major journals, conference proceedings, and chapters in books and technical encyclopedias. His work has been supported by the private sector as well as European and national funds. He is active in international lecturing, short course organization, and international technical and conference committees. He has been keynote speaker at major international conferences and has served on the editorial board of various international journals.
Phone: +302610969495
Address: Stochastic Mechanical Systems and Automation Laboratory
Dept of Mechanical Engineering and Aeronautics
University of Patras
26504 Patras, Greece

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Vibration–Based Damage Detection for a Population of Nominally Identical Structures: Unsupervised Multiple Model (MM) statistical time series type methods

by Kyriakos Vamvoudakis-Stefanou and Spilios D Fassois

Mechanical Systems and Signal Processing, 2018

The problem of vibration–based damage detection for a population of nominally identical structure... more The problem of vibration–based damage detection for a population of nominally identical structures is considered via unsupervised statistical time series type methods. For this purpose a population sample comprising 31 nominally identical composite beams with significant beam–to–beam variability in the dynamics is employed, with impact–induced damage at various positions and two distinct energy levels. Two Multiple Model, MM, based statistical time series type methods are postulated, assessed, and compared with two ’conventional’ methods. The assessment is based on a comprehensive and systematic procedure, making use of thousands of test cases via a ’rotation’ procedure, with the results presented in the form of Receiver Operating Characteristic, ROC, curves. These indicate that ’conventional’ methods are mostly ineffective, especially with low impact energy damages. On the other hand, the postulated Multiple Model parameter based methods achieve significantly improved performance, characterized as very good and providing overall correct damage detection rates approaching 100% for false alarm rates at or above 5%.

A Statistical Method for the Detection of Sensor Abrupt Faults in Aircraft Control Systems

by Spilios D Fassois, John S. Sakellariou, and George Fouskitakis

IEEE Transactions on Control Systems Technology, 2000

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