Fault diagnosis consists in synthesizing a diagnoser that observes a given plant through a set of observable events, and identifies faults which are not observable as soon as pos...
Abstract-- In this paper we extend the work on dynamic observers for fault diagnosis [1], [2], [3] to timed automata. We study sensor minimization problems with static observers an...
Abstract--We present in this paper a case study of the probabilistic approach to model-based diagnosis. Here, the diagnosed system is a real-world electrical power system (EPS), i....
Ole J. Mengshoel, Mark Chavira, Keith Cascio, Scot...
The purpose of this article is to present a method for industrial process diagnosis with Bayesian network, and more particularly with Conditional Gaussian Network (CGN). The inter...
A rule-based Decision Support System is presented for the diagnosis of Coronary Artery Disease. The generation of the decision support system is realized automatically using a thr...
Markos G. Tsipouras, Themis P. Exarchos, Dimitrios...