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Laboratoire d’analyse et d’architecture des systèmes

Publications de l'équipe DISCO

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16125
24/10/2017

Root cause analysis of actuator fault based on invertibility of interconnected system

M.ZHANG, Z.LI, M.CABASSUD, B.DAHHOU

LGC, GUIZHOU, DISCO

Revue Scientifique : International Journal of Modelling, Identification and Control, Vol.27, N°4, pp.256-270, Octobre 2017 , N° 16125

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Abstract

This paper addresses the problem of root cause analysis (RCA) of actuator fault. By considering an actuator as an individual dynamic subsystem connected with process dynamic subsystem in cascade, an interconnected system is then constituted. The fault detection and diagnosis (FDD) algorithm is carried out in actuator subsystem and aims at identifying the root causes of actuator faults. According to real plant, outputs of the actuator subsystem are assumed inaccessible and are reconstructed by measurements of the global system, thus providing a means of monitoring and diagnosis of the plant at both local and global level. A condition of invertibility of the interconnected system is first developed to guarantee that faults occurring in the actuator subsystem will affect the measured output of the global system distinguishably. For that, a necessary and sufficient condition is proposed to ensure invertibility of the interconnected system. Effectiveness of the proposed approach is demonstrated on an intensified HEX reactor.

141340
17373
18/10/2017

Alarm management via temporal pattern learning

J.VASQUEZ, A.SUBIAS, L.TRAVE-MASSUYES, F.JIMENEZ

DISCO, Univ. de Los Andes

Revue Scientifique : Engineering Applications of Artificial Intelligence, Vol.65, pp.506-516, Octobre 2017 , N° 17373

Lien : https://hal.laas.fr/hal-01611635

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Abstract

Industrial plant safety involves integrated management of all the factors that may cause accidents. Process alarm management can be formulated as a pattern recognition problem in which temporal patterns are used to characterize different typical situations, particularly at startup and shutdown stages. In this paper we propose a new approach of alarm management based on a diagnosis process. Assuming the alarms and the actions of the standard operating procedure as discrete events, the diagnosis step relies on situation recognition to provide the operators with relevant information on the failures inducing the alarm flows. The situation recognition is based on chronicle recognition where we propose to use the hybrid causal model of the system and simulations to generate the representative event sequences from which the chronicles are learned using the Heuristic Chronicle Discovery Algorithm Modified (HCDAM). An extension of this algorithm is presented in this article where the expertise knowledge is included as temporal restrictions which are a new input to HCDAM. An illustrative example in the field of petrochemical plants is presented.

141255
13403
01/10/2017

Improved solutions for ill-conditioned problems involved in set-membership estimation for fault detection and isolation

L.RAVANBOD, C.JAUBERTHIE, N.VERDIERE, L.TRAVE-MASSUYES

Université du Havre, DISCO

Revue Scientifique : Journal of process control, Vol.58, pp.139-151, Octobre 2017 , N° 13403

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Abstract

Set-membership (SM) estimation implies that the computed solution sets are guaranteed to contain all the feasible estimates consistent with the bounds specified in the model. Two issues often involved in the solution of SM estimation problems and their application to engineering case studies are considered in this paper. The first one is the estimation of derivatives from noisy signals, which in a bounded uncertainty framework means obtaining an enclosure by lower and upper bounds. In this paper, we improve existing methods for enclosing derivatives using Higher-Order Sliding Modes (HOSM) differentiators combining filtering. Our approach turns the use of high order derivatives more efficiently especially when the signal to differentiate has slow dynamics. The second issue of interest is solving linear interval equation systems, which is often an ill-conditioned problem. This problem is reformulated as a Constraint Satisfaction Problem and solved by the combination of the constraint propagation Forward Backward algorithm and the SIVIA algorithm. The two proposed methods are tested on illustrative examples. The two methods are then used in a fault detection and isolation algorithm based on SM parameter estimation that is applied to detect abnormal parameter values in a biological case study.

140912
17153
29/09/2017

A learning algorithm for episodes

T;OBRY, A.SUBIAS, L.TRAVE-MASSUYES

DISCO

Manifestation avec acte : International Workshop on Principles of Diagnosis ( DX ) 2017 du 26 septembre au 29 septembre 2017, Brescia (Italie), Septembre 2017, 5p. , N° 17153

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141134
17154
29/09/2017

Diagnosis of supervision patterns on bounded labeled Petri nets by model checking

Y.PENCOLE, A.SUBIAS

DISCO

Manifestation avec acte : International Workshop on Principles of Diagnosis ( DX ) 2017 du 26 septembre au 29 septembre 2017, Brescia (Italie), Septembre 2017, 9p. , N° 17154

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141133
17327
26/09/2017

Chronicle modeling and analysis for diagnosis

Y.PENCOLE, A.SUBIAS

DISCO

Rapport LAAS N°17327, Septembre 2017, 33p.

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140996
17304
18/09/2017

ARMISCOM: self-healing service composition

J.VIZCARRONDO, J.AGUILAR, E.EXPOSITO, A.SUBIAS

CENDITEL, Andes, LIUPPA, DISCO

Revue Scientifique : Service Oriented Computing and Applications, Vol.11, N°3, pp.345-365, Septembre 2017 , N° 17304

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Abstract

In the domain of the service composition, the failure of a service generates error propagation in the other services, and therefore, it can generate the failure of the entire system. Usually, these failures cannot be detected and corrected only with local information. Normally, it is required the development of architectures that enable the diagnosis and correction of faults, both locally (elementary service) as well as globally (service composition). This paper presents a reflexive middleware architecture based on autonomic computing, which allows the distributed diagnosis of faults in the service composition, called ARMISCOM. This middleware has not a central diagnoser, instead the diagnosis of failures is carried out through the interaction of local diagnosers present in each service of the composition. These local diagnoses use a distributed chronicle approach proposed in previous works, which allows the recognition of fully distributed patterns of the classic failures in the SOA systems. In addition, the repair strategies are defined through consensus of the repairers, equally distributed between the services of the composition. The repair strategies use the concept of “equivalent regions” defined in this paper, for the fault correction in a SOA application.

140857
17363
21/08/2017

Analyse structurelle pour le diagnostic des systèmes distribués

C.PEREZ

DISCO

Doctorat : INSA de Toulouse, 21 Août 2017, 149p., Président: A.MORAN, Rapporteurs: V.COCQUEMPOT, A.RIOS-BOLIVAR , Directeurs de thèse: L.TRAVE-MASSUYES, E.CHANTHERY, J.SOTOMAYOR , N° 17363

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Abstract

This thesis focuses on fault detection and isolation. Among the different methods to generate diagnosis tests by taking advantage of analytical redundancy, this thesis adopts the approach based on analytical redundancy relations (ARRs). Given a model of the system in the form of a set of differential equations, ARRs are relations that are obtained from the model by eliminating non measured variables. This can be performed in an analytical framework using elimination theory. Another way of doing this is to use structural analysis. Structural analysis is based on a structural abstraction of the model that only retains a representation of which variables are involved in which equations. Despite the rusticity of the abstract model, structural analysis provides a set of powerful tools, relying on graph theory, to analyze and infer information about the system. Interestingly, it applies indifferently to linear or nonlinear systems. This thesis proposes efficient algorithms based on structural analysis for the diagnosis of decentralized and distributed continuous systems as well as for the choice of an optimal set of tests. These algorithms were tested on two industrial case studies.

Résumé

Cette thèse porte sur la détection et l’isolation de fautes. Parmi les différentes méthodes pour générer des tests de diagnostic utilisant la redondance analytique, cette thèse adopte l’approche par relations de redondance analytique (RRA). Étant donné un modèle du système sous la forme d’un ensemble d’équations différentielles, les RRA sont des relations obtenues à partir du modèle en éliminant les variables non mesurées. Ceci peut être effectué dans un cadre analytique en utilisant la théorie de l’élimination. Une autre solution consiste à utiliser l’analyse structurelle. L’analyse structurelle est basée sur une abstraction du modèle qui ne conserve que les liens entre variables et équations. Malgré son apparente simplicité, l’analyse structurelle fournit un ensemble d’outils puissants, s’appuyant sur la théorie des graphes, pour analyser et inférer des informations sur le système. Par ailleurs, elle a l’avantage de s’appliquer indifféremment sur les systèmes linéaires ou non linéaires. Cette thèse propose des algorithmes efficaces basés sur l’analyse structurelle pour le diagnostic des systèmes continus decentralisés et distribués ainsi que pour le choix d’un ensemble de tests optimal. Ces algorithmes on été testés sur deux cas d’étude industriels.

Mots-Clés / Keywords
Diagnostic à base de modèles; Analyse structurelle; Architectures décentralisées et distribuées; Algorithmes de planification; A*; Model based fault diagnosis; Structural analysis; Decentralized and distributed architectures; Planning algorithms;

141213
17155
17/08/2017

Diagnostic de motifs de comportements dans les systèmes temporels

Y.PENCOLE, A.SUBIAS

DISCO

Rapport LAAS N°17155, Août 2017, 14p.

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140158
17141
26/07/2017

Unknown input reconstruction: a comparison of system inversion and sliding mode observer based techniques

M.ZHANG, Z.LI, M.CABASSUD, B.DAHHOU

GUIZHOU, LGC, DISCO

Manifestation avec acte : Chinese Control Conference ( CCC ) 2017 du 26 juillet au 28 juillet 2017, Dalian (Chine), Juillet 2017, 7p. , N° 17141

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