A Safe Diagnosis Method of Pattern Faults of Stochastic Discrete-event Systems Under Dynamic Observations

In many practical applications, faults are frequently caused by the occurrence of specific events in succession (i.e., pattern faults) rather than a single failure event. The safe diagnosis method based on pattern faults can diagnose the event string that triggers faults. However, the static observation of the original system may not be able to fully capture system faults for complex systems due to the pre-defined and fixed set of observable and unobservable events, leading to the omission of the fault diagnosis. The purpose of this research is to address the limitations of traditional static observation methods. For this reason, a safe diagnosis method based on the dynamic observation of pattern faults in stochastic discrete-event systems (SDESs) is proposed. First, the concepts of S-type and T-type pattern safe diagnosability for SDESs under dynamic observations are formally introduced. Then,a pattern-safe diagnoser and a forbidden language recognizer are constructed to diagnose the pattern faults. Finally, the necessary and sufficient conditions for pattern-safe diagnosability of SDESs under dynamic observations are presented, and an example is provided to illustrate the results.