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Paper details
Number 2 - June 2018
Volume 28 - 2018
From structural analysis to observer-based residual generation for fault detection
Sebastian Pröll, Jan Lunze, Fabian Jarmolowitz
Abstract
This paper combines methods for the structural analysis of bipartite graphs with observer-based residual generation. The
analysis of bipartite structure graphs leads to over-determined subsets of equations within a system model, which make
it possible to compute residuals for fault detection. In observer-based diagnosis, by contrast, an observability analysis
finds observable subsystems, for which residuals can be generated by state observers. This paper reveals a fundamental
relationship between these two graph-theoretic approaches to diagnosability analysis and shows that for linear systems the
structurally over-determined set of model equations equals the output connected part of the system. Moreover, a condition
is proved which allows us to verify structural observability of a system by means of the corresponding bipartite graph. An
important consequence of this result is a comprehensive approach to fault detection systems, which starts with finding the
over-determined part of a given system by means of a bipartite structure graph and continues with designing an observer-based residual generator for the fault-detectable subsystem found in the first step.
Keywords
fault diagnosis, structural analysis, observer-based diagnosis, diagnosability analysis