International Journal of applied mathematics and computer science

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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

DOI
10.2478/amcs-2018-0017