What is it about?
Detection of a change in sensor coefficient, which can be translated as fault using the Bayesian framework.
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Why is it important?
Bayesian fault detection, Markov jump system, RLS, Smith-Gelfand re-sampling, Yao’s Prior setting.
Perspectives
Hamed Habibi has been a Ph.D. student at Curtin University, Perth, Australia from 2015. He received his B.Sc. and M.Sc. degrees in Mechanical Engineering from Khaje Nasir University and University of Tehran, both in Tehran, Iran, in 2010 and 2013, respectively. His current research interests include wind turbine control systems, fault detection, isolation, identification, accommodation, and fault tolerant control systems with applications on wind turbines.
mr Hamed Habibi
Curtin University
Read the Original
This page is a summary of: Bayesian Sensor Fault Detection in a Markov Jump System, Asian Journal of Control, February 2017, Wiley,
DOI: 10.1002/asjc.1458.
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