Unobservable fuzzy Petri net diagnosis technique

The purpose of this paper is to resolve the problem of complex system diagnosis with unobservable events such as Hall thruster.

Fault 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.

Using 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.

The relationship between unobservable events must be known.

The method shows its superiority when it is applied to unobservable systems such as spacecraft.

A novel fuzzy Petri net framework for unobservable system multi‐fault diagnosis is put forward which introduces some new ideas.