Unobservable fuzzy Petri net diagnosis technique

Abstract

PurposeThe purpose of this paper is to resolve the problem of complex system diagnosis with unobservable events such as Hall thruster.Design/methodology/approachFault class is defined by unobservable transitions subset. Every fault class is departed into four levels of alarm. The level of alarm for a fault class is identified by constructing basis reachability graph and computing j vector and basis marking. Certain factor values of diagnosis results are given by introducing two fuzzy operators. A two‐directional reasoning strategy is adopted which are forward reasoning and backward reasoning.FindingsUsing basis reachability graph and notions of basis marking and j vector, fuzzy Petri net with unobservable transitions can resolve the diagnosis problems with high accuracy and efficiency.Research limitations/implicationsThe relationship between unobservable events must be known.Practical implicationsThe method shows its superiority when it is applied to unobservable systems such as spacecraft.Originality/valueA novel fuzzy Petri net framework for unobservable system multi‐fault diagnosis is put forward which introduces some new ideas.