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HYBRID
2001
Springer

Diagnosis of Physical Systems with Hybrid Models Using Parametrized Causality

11 years 5 months ago
Diagnosis of Physical Systems with Hybrid Models Using Parametrized Causality
Efficient algorithms exist for fault detection and isolation of physical systems based on functional redundancy. In a qualitative approach, this redundancy can be captured by a temporal causal graph (TCG), a directed graph that may include temporal information. However, in a detailed continuous model, time constants may be present that are beyond the bandwidth of the data acquisition system, which leads to incorrect fault isolation because of a difference in observed and modeled behavior. To solve this, the modeled time constants can be taken to be infinitely small, which results in a model with mixed continuous/discrete, hybrid behavior that is difficult to analyze because the causality of the directed graph may change. In this paper, to avoid the combinatorial explosion when using a bank of TCGs in parallel, causal paths are parametrized by the state of local switches. The result is a hybrid model that produces parametrized predictions that can be efficiently matched against observ...
Pieter J. Mosterman
Added 29 Jul 2010
Updated 29 Jul 2010
Type Conference
Year 2001
Where HYBRID
Authors Pieter J. Mosterman
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