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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.
AI Communications – IOS Press
Published: Jan 1, 2001
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