Graph-Theoretic Analysis of Residual Generation Under Computational Constraints

TL;DR

This paper introduces a structural framework for model-based fault diagnosis that accounts for computational constraints, extending existing methods to identify suitable residuals and fault signatures.

Contribution

It develops a unified framework incorporating residual generation constraints, introduces new set concepts, and provides algorithms for fault isolability analysis under computational limits.

Findings

The framework generalizes MTES-based analysis to constrained residual generation.

An operator $M^*$ extracts the largest testable PSO set compatible with residual methods.

The approach is demonstrated on a linear DAE model with low differential index.

Abstract

A unified structural framework is presented for model-based fault diagnosis that explicitly incorporates both fault locations and constraints imposed by the residual generation methodology. Building on the concepts of proper and minimal structurally overdetermined (PSO/MSO) sets and Test Equation Supports (TES/MTES), the framework introduces testable PSO sets, Residual Generation (RG) sets, irreducible fault signatures (IFS), and Irreducible RG (IRG) sets to characterize which submodels are suitable for residual generation under given computational restrictions. An operator $M^*$ is defined to extract, from any model, the largest testable PSO subset consistent with a specified residual generation method. Using this operator, an algorithm is developed to compute all RG sets, and it is shown that irreducible fault signature sets form the join-irreducible elements of a join-semilattice of sets and fully capture the multiple-fault isolability properties in the method-constrained setting. The approach is exemplified on a semi-explicit linear DAE model, where low structural differential index can be used to define $M^*$. The results demonstrate that the proposed framework generalizes MTES-based analysis to residual generation scenarios with explicit computational limitations.