Model based diagnosis of large continuous dynamic systems requiring quantitative simulation has a high computational cost, which can be reduced by distributing the computation. Distribution can be obtained partitioning the original diagnosis problem into the analysis of simpler subproblems. In this work, Possible Conflicts are used to partition a system because they provide a systematic way to decompose a system. How- ever, a requirement of any decomposition method is that the resulting subsystems are observable. This paper focuses on structural observability, a powerful concept because it allows analyzing the observability of a system in terms of its configuration, i.e., independently of system parameter values. However, the literature provides different definitions of structural observability, adapted to different modeling formalisms: equations, bipartite graphs and bond graphs. This paper shows that definitions for these formalisms are equivalent. The three tank system benchmark and a spring-mass system are used to illustrate the definitions and their equivalence. Then, it will be applied through Possible Conflicts to build independent subsystems that can be used for monitoring and diagnosis.
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