MODELING PROCESSES FROM TIMED OBSERVATIONS

Cemagref, Unite´ Ouvrages Hydrauliques et Hydrologie, Aix en Provence, Franceemilie.masse@cemagref.fr, corinne.curt@cemagref.frKeywords: Multi modeling, diagnosis reasoning, dynamic systemAbstract: Thispaper presents amodelling approach of dynamic process for diagnosis that iscompatible withthe Stochas-tic Approach framework for discovering temporal knowledge from the timed observations contained in adatabase. The motivation is to define a multi-model formalism that is able to represent both the knowledgeof these two sources. The aim is to model the process at the same level of abstraction that an expert uses todiagnose the process. The underlying idea is that at this level of abstraction, the model is simple enough toallow an efficient diagnosis. The proposed formalism repres ents the knowledge in four models: a structuralmodel defining the components and the connection relations o f the process, a behavioural model defining thestates and the transitions states of the process, a functional model containing the logical relations between thevalues of the process’s variables, which are defined in the pe rception model. The models are linked with theprocess’s variables. This point facilitates the analysis of the consistency of the four models and is the basis ofthe corresponding knowledge modelling methodology. The formalism and the methodology is illustrated withthe model of a hydraulic dam of Cublize (France).