Journal ArticleDOI
Minimal Structurally Overdetermined sets for residual generation: A comparison of alternative approaches
Joaquim Armengol,Anibal Bregon,Teresa Escobet,Esteban R. Gelso,Mattias Krysander,Mattias Nyberg,Xavier Olive,Belarmino Pulido,Louise Travé-Massuyès +8 more
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TLDR
In this article, the issue of residual generation using structural analysis has been studied by several authors, and four recently proposed algorithms that solve this problem are presented and compared, and compared with each other.About:
This article is published in IFAC Proceedings Volumes.The article was published on 2009-01-01. It has received 60 citations till now. The article focuses on the topics: Residual & Overdetermined system.read more
Citations
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Journal ArticleDOI
Active Model-Based Fault Diagnosis in Reconfigurable Battery Systems
TL;DR: A model-based fault diagnosis algorithm is developed and validated that uses the switches of an RBS to improve the fault isolability and it is shown simulatively and experimentally that additional faults are isolated by the presented active approach.
Journal ArticleDOI
A Combined Data-Driven and Model-Based Residual Selection Algorithm for Fault Detection and Isolation
Daniel Jung,Christofer Sundström +1 more
TL;DR: An algorithm for residual selection that combines model-based and data-driven methods to find a set of residual generators that maximizes fault detection and isolation performance is proposed.
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Bridging control and artificial intelligence theories for diagnosis: A survey
TL;DR: This paper presents diagnosis as it is understood in the Control and Artificial Intelligence fields, and exemplifies how different theories of these fields can be synergistically integrated to provide better diagnostic solutions and to achieve improved fault management in different environments.
Journal ArticleDOI
An event-based distributed diagnosis framework using structural model decomposition
Anibal Bregon,Matthew Daigle,Indranil Roychoudhury,Gautam Biswas,Xenofon Koutsoukos,Belarmino Pulido +5 more
TL;DR: Using Possible Conflicts, a structural model decomposition method from the Artificial Intelligence model-based diagnosis (DX) community, a distributed diagnoser design algorithm is developed to build local event-based diagnosers that are constructed based on global diagnosability analysis of the system.
A Structural Algorithm for Finding Testable Sub-models and Multiple Fault Isolability Analysis
TL;DR: This paper presents a meta-modelling architecture suitable for isolability analysis and finding testable sub-models for Analytical Redundancy Relatio (ARR) in the discrete-time environment.
References
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Journal ArticleDOI
A theory of diagnosis from first principles
TL;DR: The theory accommodates diagnostic reasoning in a wide variety of practical settings, including digital and analogue circuits, medicine, and database updates, and reveals close connections between diagnostic reasoning and nonmonotonic reasoning.
Book
Constraint Processing
TL;DR: Rina Dechter synthesizes three decades of researchers work on constraint processing in AI, databases and programming languages, operations research, management science, and applied mathematics to provide the first comprehensive examination of the theory that underlies constraint processing algorithms.
Journal ArticleDOI
Coverings of Bipartite Graphs
A. L. Dulmage,N. S. Mendelsohn +1 more
TL;DR: In this paper, the concept of exterior coverings is introduced for decomposing bipartite graphs into two parts, an inadmissible part and a core, and then decomposing the core into irreducible parts and thus obtaining a canonical reduction of the graph.
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Analytical redundancy relations for fault detection and isolation in algebraic dynamic systems
TL;DR: The analytical redundancy techniques, well developed for linear systems, are extended to FDI in non-linear dynamic systems modeled by polynomial differential algebraic equations, and the design of robust structured residuals is addressed.
Journal ArticleDOI
Conflicts versus analytical redundancy relations: a comparative analysis of the model based diagnosis approach from the artificial intelligence and automatic control perspectives
Marie-Odile Cordier,Philippe Dague,François Lévy,Jacky Montmain,Marcel Staroswiecki,Louise Travé-Massuyès +5 more
TL;DR: A formal framework is proposed in order to compare the two approaches and the theoretical proof of their equivalence together with the necessary and sufficient conditions is provided.