Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence
Artificial Intelligence
Artificial Intelligence
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Finding stable causal interpretations of equations
Recent advances in qualitative physics
Qualitative circuit models in failure analysis reasoning
Artificial Intelligence
A comprehensive methodology for building hybrid models of physical systems
Artificial Intelligence
Model-based systems in the automotive industry
AI Magazine
Simulating electrical devices with complex behaviour
AI Communications
Reasoning about linear circuits; a model-based approach
AI Communications
A language for functional interpretation of model based simulation
Advanced Engineering Informatics
A layered approach to automated electrical safety analysis in automotive environments
Computers in Industry
Towards a qualitative lagrangian theory of fluid flow
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Multiple fault diagnosis from FMEA
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Sensor Placement for Fault Diagnosis
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Automated FMEA based diagnostic symptom generation
Advanced Engineering Informatics
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This paper presents a structured power and energy-flow-based qualitative modelling approach that is applicable to a variety of system types including electrical and fluid flow. The modelling is split into two parts. Power flow is a global phenomenon and is therefore naturally represented and analysed by a network comprised of the relevant structural elements from the components of a system. The power flow analysis is a platform for higher-level behaviour prediction of energy related aspects using local component behaviour models to capture a state-based representation with a global time. The primary application is Failure Modes and Effects Analysis (FMEA) and a form of exaggeration reasoning is used, combined with an order of magnitude representation to derive the worst case failure modes. The novel aspects of the work are an order of magnitude(OM) qualitative network analyser to represent any power domain and topology, including multiple power sources, a feature that was not required for earlier specialised electrical versions of the approach. Secondly, the representation of generalised energy related behaviour as state-based local models is presented as a modelling strategy that can be more vivid and intuitive for a range of topologically complex applications than qualitative equation-based representations. The two-level modelling strategy allows the broad system behaviour coverage of qualitative simulation to be exploited for the FMEA task, while limiting the difficulties of qualitative ambiguity explanation that can arise from abstracted numerical models. We have used the method to support an automated FMEA system with examples of an aircraft fuel system and domestic a heating system discussed in this paper.