Failure diagnosis using discrete-event models

Abstract

Abstruct-Detection and isolation of failures in large, complex systems is a crucial and challenging task. The increasingly stringent requirements on performance and reliability of complex technological systems have necessitated the development of sophisticated and systematic methods for the timely and accurate diagnosis of system failures. We propose a discrete-event systems (DES) approach to the failure diagnosis problem. This approach is applicable to systems that fall naturally in the class of DES; moreover, for the purpose of diagnosis, continuous-variable dynamic systems can often be viewed as DES at a higher level of abstraction. We present a methodology for modeling physical systems in a DES framework and illustrate this method with examples. We discuss the notion of diagnosability, the construction procedure of the diagnoser, and necessary and sufficient conditions for diagnosability. Finally, we illustrate our approach using realistic models of two different heating, ventilation, and air conditioning (HVAC) systems, one diagnosable and the other not diagnosable. While the modeling methodology presented here has been developed for the purpose of failure diagnosis, its scope is not restricted to this problem; it can also be used to develop DES models for other purposes such as control. A detailed treatment of the theory underlying our approach can be found in a companion paper [27].

Diagnosis and opacity problems for infinite state systems modeled by recursive tile systems

“…It is composed of a (possibly infinite) set of states (or configurations) Diagnosability PTIME Undecidable EXPTIME (Sampath et al 1996) (Morvan and Pinchinat 2009) and transitions between those states, labeled by actions representing the atomic evolution of the system.…”

Primary and secondary diagnosis of multi-agent plan execution

“…To make a diagnosis using the coupled DESs two main approaches exist. The oldest approach combines the FSMs modeling the components into a global FSM of the whole system [28]. Unfortunately, the number of states of the global finite state machine grows exponentially with the number of components, making it infeasible for modeling large systems.…”

Modular Fault Diagnosis Based on Discrete Event Systems

“…Therefore, the proposed method of failure diagnosis (Sampath et al, 1995(Sampath et al, , 1996 is applicable not only to systems that can be classified as DES, but also to systems traditionally classified as dynamic continuous systems and modelled by differential equations. One of the interesting advantages of the proposed method is that it does not require a detailed modelling of the system to be diagnosed.…”