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Failure Diagnosis of Discrete Event Systems with Lineartime Temporal Logic Fault Specifications
 IEEE Transactions on Automatic Control
, 2001
"... Failure diagnosis problem of discrete event systems with lineartime temporal logic specications is studied in this paper. Diagnosability of discrete event systems in the temporal logic setting is dened. The problem of testing diagnosability is reduced to the problem of model checking. An algorit ..."
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Cited by 53 (8 self)
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Failure diagnosis problem of discrete event systems with lineartime temporal logic specications is studied in this paper. Diagnosability of discrete event systems in the temporal logic setting is dened. The problem of testing diagnosability is reduced to the problem of model checking. An algorithm for the test of diagnosability and the synthesis of a diagnoser is obtained. Finally, a simple example is given for illustration. The contributions of the paper are summarized as follows: (i) For the rst time an algorithm, of complexity polynomial in the number of states of the system and the number of specications, for the diagnoser synthesis is derived in the temporal logic setting; (ii) Usage of temporal logic makes the specication specifying process easier and userfriendly since natural language specications can be easily translated to temporal logic specications (when compared to formal language/automatabased specications), yet there are computational savings in the design of diagnoser (compared to that of formal language/automatabased specications); (iii) LTLbased failure diagnosis method can capture the failures representing violation of liveness properties which can not be captured by prior formal language/automatonbased failure diagnosis methods, which can only capture failures representing violation of safety properties (such as occurrence of a faulty event, or reaching a faulty state, etc.); (iv) By reducing the problem of testing diagnosability to that of model checking (and using the model checking to test the diagnosability) , a polynomial algorithm for testing diagnosability is obtained naturally; whence by using symbolic model checking we may test the diagnosability of large systems more eciently; (v) We relaxed the requirement...
Supervision patterns in discrete event systems diagnosis
 IN 8TH INTERNAT. WORKSHOP ON DISCRETE EVENT SYST
, 2006
"... In this paper, we are interested in the diagnosis of discrete event systems modeled by finite transition systems. We propose a model of supervision patterns general enough to capture past occurrences of particular trajectories of the system. Modeling the diagnosis objective by a supervision pattern ..."
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Cited by 33 (13 self)
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In this paper, we are interested in the diagnosis of discrete event systems modeled by finite transition systems. We propose a model of supervision patterns general enough to capture past occurrences of particular trajectories of the system. Modeling the diagnosis objective by a supervision pattern allows us to generalize the properties to be diagnosed and to render them independent of the description of the system. We first formally define the diagnosis problem in this context. We then derive techniques for the construction of a diagnoser and for the verification of the diagnosticability based on standard operations on transition systems. We show that these techniques are general enough to express and solve in a unified way a broad class of diagnosis problems found in the literature, e.g. diagnosing permanent faults, multiple faults, fault sequences and some problems of intermittent faults.
Diagnosability of stochastic discreteevent systems,”
 IEEE Trans. Automatic Control,
, 2007
"... AbstractWe investigate diagnosability of stochastic discreteevent systems where the observation of certain events is unreliable, that is, there are nonzero probabilities of the misdetection and misclassification of events based on faulty sensor readings. Such sensor unreliability is unavoidable ..."
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Cited by 20 (0 self)
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AbstractWe investigate diagnosability of stochastic discreteevent systems where the observation of certain events is unreliable, that is, there are nonzero probabilities of the misdetection and misclassification of events based on faulty sensor readings. Such sensor unreliability is unavoidable in applications such as nuclear energy generation. We propose the notions of uAand uAAdiagnosability for stochastic automata and demonstrate their relationship with the concepts of Aand AAdiagnosabilty defined in [1]. We extend the concept of the stochastic diagnoser to the unreliable observation paradigm and find conditions for uAand uAAdiagnosability.
Diagnosability Analysis of Distributed Discrete Event Systems
"... This paper addresses the diagnosability problem of distributed discrete event systems. Until now, the problem of diagnosability has always been solved by considering centralised approaches, monolithic systems. These approaches do not use the fact that real monitored systems are generally modelled in ..."
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Cited by 18 (3 self)
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This paper addresses the diagnosability problem of distributed discrete event systems. Until now, the problem of diagnosability has always been solved by considering centralised approaches, monolithic systems. These approaches do not use the fact that real monitored systems are generally modelled in a distributed manner. In this paper, we propose a framework for the diagnosability analysis of such systems: we study the diagnosability of the system using the fact that it is based on a set of communicating components. In the case where the system is not diagnosable, we also want to provide more accurate information in order to better understand the causes.
Comparing diagnosability in continuous and discreteevent systems
 In Proceedings of the 17th International Workshop on Principles of Diagnosis, DX'06
, 2006
"... This paper is concerned with diagnosability analysis, which proves a requisite for several tasks during the system’s life cycle. The ModelBased Diagnosis (MBD) community has developed specific approaches for Continuous Systems (CS) and for Discrete Event Systems (DES) in two distinct and parallel t ..."
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Cited by 16 (2 self)
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This paper is concerned with diagnosability analysis, which proves a requisite for several tasks during the system’s life cycle. The ModelBased Diagnosis (MBD) community has developed specific approaches for Continuous Systems (CS) and for Discrete Event Systems (DES) in two distinct and parallel tracks. In this paper, the correspondences between the concepts used in CS and DES approaches are clarified and it is shown that the diagnosability problem can be brought back to the same formulation using the concept of signatures. These results bridges CS and DES diagnosability and open perspectives for hybrid model based diagnosis. 1
Scalable diagnosability checking of eventdriven system
 In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI07
, 2007
"... Diagnosability of systems is an essential property that determines how accurate any diagnostic reasoning can be on a system given any sequence of observations. Generally, in the literature of dynamic eventdriven systems, diagnosability analysis is performed by algorithms that consider a system as a ..."
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Cited by 16 (4 self)
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Diagnosability of systems is an essential property that determines how accurate any diagnostic reasoning can be on a system given any sequence of observations. Generally, in the literature of dynamic eventdriven systems, diagnosability analysis is performed by algorithms that consider a system as a whole and their response is either a positive answer or a counter example. In this paper, we present an original framework for diagnosability checking. The diagnosability problem is solved in a distributed way in order to take into account the distributed nature of realistic problems. As opposed to all other approaches, our algorithm also provides an exhaustive and synthetic view of the reasons why the system is not diagnosable. Finally, the presented algorithm is scalable in practice: it provides an approximate and useful solution if the computational resources are not sufficient. 1
Tripakis / Fault Diagnosis with Static and Dynamic Observers 41 [16
 IEEE Transactions on Automatic Control
, 1995
"... HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte p ..."
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Cited by 12 (6 self)
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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et a ̀ la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
Types of Asynchronous Diagnosability and the RevealsRelation in Occurrence Nets
"... We consider asynchronous diagnosis in (safe) Petri net models of distributed systems, using the partial order semantics of occurrence net unfoldings. Both the observability and diagnosability properties will appear in two different forms, depending on the semantics chosen: strong observability and ..."
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Cited by 12 (9 self)
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We consider asynchronous diagnosis in (safe) Petri net models of distributed systems, using the partial order semantics of occurrence net unfoldings. Both the observability and diagnosability properties will appear in two different forms, depending on the semantics chosen: strong observability and diagnosability are the classical notions from the state machine model and correspond to interleaving semantics in Petri nets. By contrast, the weak form is linked to characteristics of nonsequential processes, and requires an asynchronous progress assumption on those processes. We give algebraic characterizations for both types, and give verification methods. The study of weak diagnosability leads us to the analysis of a relation in occurrence nets, first presented in [15]: given the occurrence of some event a that reveals b, the occurrence of b is inevitable. Then b may already have occurred, be concurrent to, or even in the future of a. We show that the revealsrelation can be effectively computed recursively for each pair, a suitable finite prefix of bounded depth is sufficient, and show its use in asynchronous diagnosis. Based on this relation, a decomposition of the Petri net unfolding into facets is defined, yielding an abstraction technique that preserves and reflects maximal partially ordered runs.
Predictability of Sequence Patterns in Discrete Event Systems
, 2008
"... The problem of predicting the occurrences of a pattern in a partiallyobserved discreteevent system is studied. The system is modeled by a labeled transition system. The pattern is a set of event sequences modeled by a finitestate automaton. The occurrences of the pattern are predictable if it is ..."
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Cited by 9 (2 self)
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The problem of predicting the occurrences of a pattern in a partiallyobserved discreteevent system is studied. The system is modeled by a labeled transition system. The pattern is a set of event sequences modeled by a finitestate automaton. The occurrences of the pattern are predictable if it is possible to infer about any occurrence of the pattern before the pattern is completely executed by the system. A novel offline algorithm to verify the property of predictability is presented. The verification is polynomial in the number of states of the system. An online algorithm to track the execution of the pattern during the operation of the system is also presented. This algorithm is based on the use of a diagnoser automaton.
Assistance for the design of a diagnosable componentbased system
 In 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI’05
, 2005
"... Diagnosability of componentbased systems is a property that characterises the ability to diagnose fault events given a flow of observations. In this paper, we use modelbased reasoning techniques and we propose a theoretical framework to analyse diagnosability in a decentralised way. We then introdu ..."
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Cited by 8 (4 self)
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Diagnosability of componentbased systems is a property that characterises the ability to diagnose fault events given a flow of observations. In this paper, we use modelbased reasoning techniques and we propose a theoretical framework to analyse diagnosability in a decentralised way. We then introduce an algorithm that performs diagnosability analyses and provides useful information for the design of a diagnosable componentbased system. 1.