Reasoning about models: detecting and isolating abnormalities in diagnostic systems

155 Pages·2012·2.74 MB·English

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MmeSylvieDELPRAT(Examinatrice)
M.DidierMAQUIN(Examinateur)
M.JoãoPAVAOMARTINS(Examinateur)

Reasoning about Models:
Detecting and Isolating Abnormalities in Diagnostic Systems
Nuno Belard

Acknowledgements
This thesis marks the end of my Ph.D. journey; a journey that was long but memorable,
challenging but rewarding, difficult but exciting. It is at the end, when all is said and done,
that I write these lines to those that were by my side along the richest period of my life.
MyfirstwordsgotoMichelCombacauandYannickPencolé, myacademicsupervisorswho
guided me through my research. By encouraging me and defying my crazy ideas they made
me think and evolve. If, research-wise, I am more mature today, it is clearly and without any
doubt due to them.
Christophe Bordry, Denys Bernard, Nathalie Bergé and Vincent Cheriere will also be stay-
ing in my mind. I will never forget that white board where Christophe, Denys and Vincent
shared their ideas and let me enter their world. Along with Nathalie who kept pushing me
to become stronger and stronger, they truly were my inspiration. Myriam Fedaoui and Sylvie
Delprat are also not to be forgotten. In an industrial context, Myriam trusted me to follow
my ideas and was more honest to me than what I could have ever expected. Sylvie had the
patience to go through all my work with a critical yet supportive point of view. In the hostile
environment of my thoughts this is an achievement by itself.
I will also want to thank M. Didier Maquin, M. João Pavão Martins, Mme. Marie-Odille
Cordier,M.PierreMarquisandLouiseTravé-Massuyès. Thefirstfour,foracceptingtobecome
a part of my jury and for sharing their insights about my work. As for Louise, by accepting
me with open arms she provided me with a working environment that many would envy.
A Ph.D. is also about those whose friendship is there for you, not only in the happy and
exciting moments, but also in the tough ones. While writing a full list of names is certainly
an impossible task, I cannot complete the last page of my thesis without thanking Almeida,
Camille, Cassiano, Cristina, Erica, Inês, Iñigo, Jose, Lucia, Mafalda, Margaux, Pauline, Ri-
cardo, Rita, Té and Tete. Each one of them knows exactly what they mean to me. Kudos.
Finally, I will probably not have another opportunity to publicly acknowledge my family.
I am honestly grateful for everything we have shared. The man I am today is a product of
every instant with them. From the bottom of my heart, thank you.

Abstract
In Model-Based Diagnosis, a set of inference rules is typically used to compute diagnoses using
a scientific and mathematical theory about a system under study and some observations.
Contrary to the classical hypothesis, it is often the case that these Models are abnormal with
respecttoaseriesofrequiredproperties, henceaffectingthequalityofthecomputeddiagnoses
with possibly huge economical consequences, in particular at Airbus.
A thesis on reality and cognition is firstly used to redefine the classic framework of model-
based diagnosis from a formal model-theoretic perspective. This, in turn, enables the formal-
isation of abnormalities and of their relation with the properties diagnoses.
Withsuchmaterialandtheideathatanimplementeddiagnosticsystemcanbeseenareal-
world artefact to be diagnosed, a theory of meta-diagnosis is developed, enabling the detection
and isolation of abnormalities in Models of diagnostic systems and explanation in general.
Such theory is then encoded in a tool, called MEDITO, and successfuly tested against Airbus
real-world industrial problems.
Moreover, as different heterogeneous implemented Airbus diagnostic systems, suffering
fromdistinctabnormalities,maycomputedifferentdiagnoses,methodsandtoolsaredeveloped
for: 1) checking the consistency between subsystem-level diagnoses and 2) validating and
comparing the performance of these diagnostic systems. Such work relies on an original bridge
between the Airbus framework of diagnosis and its academic counterpart.
Finally, meta-diagnosis is generalised to handle meta-systems other than implemented di-
agnostic systems.

Résumé
Dans le cadre du diagnostic à base de Modèle, un ensemble de règles d’inférence est ty-
piquement exploité pour calculer des diagnostics, ceci en utilisant une théorie scientifique et
mathématique sur le système à diagnostiquer, ainsi qu’un ensemble d’observations. Contraire-
ment aux hypothèses classiques, les Modèles sont souvent anormaux vis-à-vis d’un ensemble
de propriétés requises. Naturellement, cela affecte la qualité des diagnostics [à Airbus].
Une théorie sur la réalité, l’information et la cognition est créé pour redéfinir, dans une
perspective basée sur la théorie des modèles, le cadre classique de diagnostic à base de Modèle.
Ceci rend possible la formalisation des anomalies et de leur relation avec des propriétés des
diagnostics.
Aveccetravailetavecl’idéequ’unsystèmedediagnosticimplémentépeutêtrevucommeun
objet à diagnostiquer, une théorie de méta-diagnostic est développée, permettant la détection
et isolation d’anomalies dans les Modèles des systèmes de diagnostic. Cette théorie est mise
en pratique à travers d’un outil, MEDITO; et est testée avec succès à travers un ensemble de
problèmes industriels, à Airbus.
CommedesdifférentssystèmesdediagnosticAirbus,souffrantd’anomaliesvariées,peuvent
calculer des diagnostics différents, un ensemble de méthodes et outils et développé pour: 1)
déterminer la cohérence entre diagnostics et 2) valider et comparer la performance de ces
systèmes de diagnostic. Ce travail dépend d’un pont original entre le cadre de diagnostic
Airbus et son équivalent académique.
Finalement,lathéoriedeméta-diagnosticestgénéraliséepourprendreencomptedesméta-
systèmes autres que des systèmes de diagnostic implémentés.