Abstract
In this paper, we present a unified framework for distributed diagnosis. We first introduce the concepts of global and local consistency in terms of supremal global and local supports, then present two distributed diagnosis problems based on them. After that, we provide algorithms to achieve supremal global and local supports respectively, and discuss in detail the advantages and disadvantages of each. Finally, we present an industrial example to demonstrate our distributed diagnosis approach.
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