Abstract
In this paper the issue of utilising multiple models for diagnosis of dynamic systems is explored. Models are defined by their properties; which are selected from the three categories: variables, relations, and structures. Also, Model-based Diagnosis is generally perceived to consist of three tasks: fault detection, fault isolation, and fault identification, dealing with the existence, location, and degree of a fault, respectively. In order to utilise multiple models for diagnosis it is necessary to have a correlation between the model properties and the diagnostic tasks. This provides a coherent means of guiding the switching process according to the task to be performed. A proof of concept of the process is demonstrated with reference to fault identification of a laboratory scale process system rig.
Original language | English |
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Pages (from-to) | 93-104 |
Number of pages | 11 |
Journal | AI Communications |
Volume | 14 |
Issue number | 2 |
Publication status | Published - Jan 2001 |